Citation
Rotary pursuit performance in children with attention deficit hyperactivity disorder

Material Information

Title:
Rotary pursuit performance in children with attention deficit hyperactivity disorder
Creator:
Colvin, Andrew
Publication Date:
Language:
English
Physical Description:
viii, 169 leaves : ; 29 cm.

Subjects

Subjects / Keywords:
Attention deficit disorder ( jstor )
Attention deficit hyperactivity disorder ( jstor )
Child psychology ( jstor )
Control groups ( jstor )
Hyperactivity ( jstor )
Learning ( jstor )
Learning disabilities ( jstor )
Medications ( jstor )
Motor ability ( jstor )
Symptomatology ( jstor )
Attention ( mesh )
Attention Deficit Disorder with Hyperactivity -- Child ( mesh )
Attention Deficit Disorder with Hyperactivity -- Infant ( mesh )
Data Collection ( mesh )
Data Interpretation, Statistical ( mesh )
Department of Clinical and Health Psychology thesis Ph.D ( mesh )
Dissertations, Academic -- College of Health Professions -- Department of Clinical and Health Psychology -- UF ( mesh )
Motivation ( mesh )
Motor Skills ( mesh )
Practice (Psychology) ( mesh )
Research ( mesh )
Reward ( mesh )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph.D.)--University of Florida, 1996.
Bibliography:
Bibliography: leaves 151-168.
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Andrew Colvin.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
002286965 ( ALEPH )
49346323 ( OCLC )
ALP0116 ( NOTIS )

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Full Text











ROTARY PURSUIT PERFORMANCE IN CHILDREN
WITH ATTENTION DEFICIT HYPERACTIVITY DISORDER



















By

ANDREW COLVIN


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1996














ACKNOWLEDGEMENTS


The hard work and support of my committee was helpful

to me throughout this project. Eileen Fennell's advice and

encouragement was invaluable as I conceptualized this study.

Russell Bauer's knowledge of pursuit rotor methodology and

statistics aided me in formulating the protocol. Ernest

Bordini and the parents of the North Florida Chapter of the

Children and Adults with ADD were very supportive of this

research. Bernard Maria was very helpful in allowing access

to patients of the Children's Medical Services neurology

clinic. Wes Corbett of P.K. Yonge Developmental Research

School is thanked for allowing access to his students. Jack

Saarella of the University Lutheran Church is thanked for

allowing me to contact the families in his church. Tara

Saia's hard work and persistence during data collection were

outstanding, as she was extremely conscientious throughout

her work as a graduate assistant. Amy Perwien and Ryan

Bernstein were also extremely helpful during data

collection. My family was very supportive throughout this

ii









project. Without the love, understanding and patience of my

wife, Cheryl Colvin, this dissertation would not have been

completed.
















TABLE OF CONTENTS


ACKNOWLEDGMENTS . . .

ABSTRACT . .

CHAPTERS

1. CHILDREN WITH ADHD . .

Prevalence . .
History . .
Current Diagnostic Criteria . .
ADHD With and Without Hyperactivity .
Characteristics of ADHD . .
Assessment and Treatment . .

2. CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD

Impact of Right Hemisphere Dysfunction on
ADHD . . .
Morphological Differences in Children with
ADHD . . .
Cerebral Blood Flow in Children with ADHD .
Brain Metabolism in Children with ADHD .
Issues of Subject Selection . .
Neuropsychological Testing of Children with
ADHD . .
Neuroanatomy of Attention . .

3. THE PURSUIT ROTOR AND MOTOR SKILL
ACQUISITION . .

The Pursuit Rotor . .
Motor Skill Acquisition in Children with
ADHD . . .

iv


* ii

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1

1
. 2
. 6
10
.17
S42

S59



59

60
64
65
67

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74



. 80

80


. 87










Neuroanatomy of Motor Systems


4. SUMMARY AND RATIONALE .


Summary . .
Specific Aims and Hypotheses


5. DESIGN .


6. PROCEDURE AND METHODS .


Subjects .
Measures .
Procedure . .


7. RESULTS . .


Initial Analyses .
Neuropsychological Measures .
Analyses of Pursuit Rotor Perf


8. DISCUSSION .


Sample Characteristics .
Rotary Pursuit Performance
Secondary Analyses .
Implications .
Limitations .
Summary and Directions for Fut


APPENDICES


A BACKGROUND INFORMATION .....


B BEHAVIOR CHECKLIST ......


REFERENCES ..........


BIOGRAPHICAL SKETCH .. .........


. 89


. 93


.. 93
. . 95


98


. 100


100
102
107


114


114
. 116
ormance 117


. 131


. 132
. 133
. 135
137
. 142
ure Research 144















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

ROTARY PURSUIT PERFORMANCE IN CHILDREN WITH
ATTENTION DEFICIT HYPERACTIVITY DISORDER

By

Andrew Colvin

December, 1996


Chairperson: Eileen B. Fennell
Major Department: Clinical and Health Psychology




Attention deficit hyperactivity disorder (ADHD) is a

disruptive behavior disorder characterized by inattention,

impulsivity, and motor overactivity. Motor delays and

incoordination are also commonly associated with ADHD, and

these problems may impact children's social and academic

functioning. However, the incoordination seen in these

children is often attributed to impulsivity and inattention,

and little research has investigated the causes of these

motor problems. Neural structures involved in the

development of motor programs have been identified as being

vi








abnormal in children with ADHD. The major hypothesis of

this study was that children with ADHD would have difficulty

forming motor programs through practice. The photoelectric

pursuit rotor was used to compare the motor learning of

children with ADHD to that of normal controls. Small

rewards have been found to increase the performance of

children with ADHD without the use of medication; therefore,

a reward condition was used to control for motivation and

attention. There were 64 subjects in the current study (31

ADHD, 33 control). Neuropsychological measures of

attention, impulsivity, fine motor coordination, and spatial

judgement were administered and significant differences in

impulsivity and fine motor coordination with the non-

dominant hand were found between the ADHD and control

groups. Children were randomly assigned either to a reward

or no reward condition, for a total of four groups

(ADHD/Reward, ADHD/No Reward, Control/Reward, Control/No

Reward). Six blocks of five, 30-second pursuit rotor trials

were administered, in a manner consistent with distributed

practice. Repeated measures ANOVAs indicated that the ADHD

group had deficits in motor learning compared with the

control group. Multiple regression analysis performed for

vii








the entire sample suggested that impulsivity may be a

significant predictor of pursuit rotor performance, but this

was not found for either group separately. The motor

programming deficits found in the children with ADHD were

discussed in terms of their relationship to neural

structures.


viii














CHAPTER 1
CHILDREN WITH ADHD


Prevalence


Attention deficit hyperactivity disorder (ADHD) is one

of the most common childhood psychiatric disorders. It is

estimated that 3%-5% of school-age children meet criteria

for ADHD (American Psychiatric Association, 1994), but the

prevalence may be as high as 12% (Trites, Dugas, Lynch, &

Ferguson, 1979). Depending on the population studied, four

to nine times as many boys as girls are diagnosed with ADHD

(American Psychiatric Association, 1994). A child's age has

not been shown to have a significant effect on the diagnosis

of ADHD, although there may a trend towards fewer symptoms

as the child ages (Szatmari, Offord, & Boyle, 1989a).

Children with ADHD are estimated to be 30% to 40% of

referrals to clinicians (Barkley, 1990) and so research into

ADHD is critical as a basis for clinical work.










History


Still (1902) described "morbid defects of moral

control" in 20 children with no intellectual impairments or

brain injury. These children demonstrated symptoms that are

now associated with ADHD such as inattention, impulsivity,

lack of inhibition, aggression, and defiance of authority

figures. These symptoms were compared with those of

children who had suffered epilepsy, traumatic brain injury,

or encephalitis. The similar symptom picture led to the

belief that although there was no history of brain injury or

disease, children with a defect of moral control had an

underlying neurological deficit (Still, 1902). Family

psychopathology and minor physical anomalies noted in these

children were also cited as evidence for the existence of

minimal brain damage, which was the first primary diagnosis

given to children who displayed the symptoms of ADHD

(Cantwell & Baker, 1991). This diagnosis lost its clinical

utility as evidence accumulated that minor brain damage

actually resulted in multiple, nonspecific symptom pictures

(Spreen et al. 1984; Barkley, 1990).










Although inattention continued to be recognized as a

symptom of the disorder, motor overactivity was the basis

for the next diagnostic schema, hyperkinetic reaction of

childhood (American Psychiatric Association, 1968; Cantwell

& Baker, 1992). However, inattention and impulsivity were

often essential characteristics of these children' symptoms

and the diagnostic nomenclature was changed to reflect this

(Goodyear & Hynd, 1992). Attention deficit disorder (ADD),

a diagnosis that included the three essential features of

inattention, impulsivity, and hyperactivity, was recognized

in the third edition of the Diagnostic and Statistical

Manual of Mental Disorders (DSM-III; American Psychiatric

Association, 1980). Two subtypes of ADD were described in

the DSM-III; the first included all three behavioral

characteristics, with emphasis on motor hyperactivity

(ADD/H), and the second group was characterized by attention

deficits, with little or no overactivity (ADD/WO). The

existence of ADD/WO was the subject of considerable debate

following publication of the DSM-III and during development

of the next diagnostic system, the DSM-III-R (American

Psychiatric Association, 1987). Attention deficit disorder

without hyperactivity is a rare symptom cluster (Szatmari,








4

Offord, & Boyle, 1989a), making research with this group of

children difficult. The scarcity of data on children with

ADD/WO led the developers of the DSM-III-R (American

Psychiatric Association, 1987) to recognize only Attention

Deficit Disorder with hyperactivity as a diagnostic category

(Goodyear & Hynd, 1992). The diagnostic criteria for ADHD

in the DSM-III-R were as follows:

Attention Deficit Hyperactivity Disorder

Note: Consider a criterion met only if the behavior is
considerably more frequent than that of most people of
the same mental age.

A. A disturbance of at least six months during which
at least eight of the following are present:

(1) often fidgets with hands or feet or squirms in seat
(in adolescents may be limited to subjective feelings
of restlessness)

(2) has difficulty remaining seated when required to do
so

(3) is easily distracted by extraneous stimuli

(4) has difficulty awaiting turn in games or group
situations

(5) often blurts out answers to questions before they
have been completed

(6) has difficulty following through on instructions
from others (not due to oppositional behavior or
failure of comprehension), e.g., fails to finish chores











(7) has difficulty sustaining attention in tasks or
play activities

(8) often shifts from one uncompleted activity to
another

(9) has difficulty playing quietly

(10) often talks excessively

(11) often interrupts or intrudes on others, e.g.,
butts into other children's games

(12) often does not seem to listen to what is being
said to him or her

(13) often loses things necessary for tasks or
activities at school or at home (e.g., toys, pencils,
books, assignments)

(14) often engages in physically dangerous activities
without considering possible consequences (not for the
purpose of thrill-seeking), e.g., runs into street
without looking

B. Onset before the age of seven

C. Does not meet the criteria for a Pervasive
Developmental Disorder

Criteria for the severity of Attention-Deficit
Hyperactivity Disorder:

Mild: Few, if any symptoms in excess of those required
to make the diagnosis and only minimal or no impairment
in school and social functioning.

Moderate: Symptoms or functional impairment
intermediate between "mild" and "severe."

Severe: Many symptoms in excess of those required to
make the diagnosis and significant and pervasive











impairment in functioning at home and school and with
peers.

(DSM-III-R, 50-53)

Considerable research, to be discussed below, provided

strong data in support of multiple subtypes and Attention

deficit disorder was again divided into subtypes with the

appearance of the DSM-IV American Psychiatric Association,

1994).


Current Diagnostic Criteria


The Fourth Edition of the Diagnostic and Statistical

Manual for Mental Disorder (DSM-IV; American Psychiatric

Association, 1994) recognizes three subtypes of ADHD; ADHD-

combined type, ADHD-predominantly inattentive type, and

ADHD-predominantly hyperactive/impulsive type. Children who

meet criteria for the predominantly inattentive type do not

meet hyperactive/impulsive criteria, while children who fall

into the hyperactive/impulsive category are overactive, but

not distractible. The complete DSM-IV diagnostic criteria

are as follows:

DSM-IV Criteria for Attention Deficit/Hyperactivity
Disorder











A. Either (1) or (2):

(1) six (or more) of the following symptoms of
inattention have persisted for at least 6 months to a
degree that is maladaptive and inconsistent with
developmental level:

Inattention

(a) often fails to give close attention to details or
makes careless mistakes in schoolwork, work, or other
activities

(b) often has difficulty sustaining attention in tasks
or play activities

(c) often does not seem to listen when spoken to
directly

(d) often does not follow through on instructions and
fails to finish schoolwork, chores, or duties in the
workplace (not due to oppositional behavior or failure
to understand instructions)

(e) often has difficulty organizing tasks and
activities

(f) often avoids, dislikes, or is reluctant to engage
in tasks that require sustained mental effort (such as
schoolwork or homework)

(g) often loses things necessary for tasks or
activities (e.g., toys, school assignments, pencils,
books, or tools)

(h) is often easily distracted by extraneous stimuli

(i) is often forgetful in daily activities

(2) six (or more) of the following symptoms of
hyperactivity-impulsivity have persisted for at least 6
months to a degree that is maladaptive and inconsistent
with developmental level:











Hyperactivity

(a) often fidgets with hands or feet or squirms in seat

(b) often leaves seat in classroom or in other
situations in which remaining seated is expected

(c) often runs about or climbs excessively in
situations in which it is appropriate (in adolescents
or adults, may be limited to subjective feelings of
restlessness)

(d) often has difficulty playing or engaging in leisure
activities quietly

(e) is often "on the go" or often acts if "driven by a
motor"
(f) often talks excessively

Impulsivity

(g) often blurts out answers before questions have been
completed

(h) often has difficulty awaiting turn

(i) often interrupts or intrudes on others (e.g., butts
into conversations or games)

B. Some hyperactive-impulsive or inattentive symptoms
that caused impairment were present before age 7 years.

C. Some impairment from the symptoms is present in two
or more settings (e.g., at school [or work] and at
home).

D. There must be clear evidence of clinically
significant impairment in social, academic, or
occupational functioning.

E. The symptoms do not occur exclusively during the
course of a Pervasive Developmental Disorder,
Schizophrenia, or other Psychotic Disorder and are not










better accounted for by another mental disorder (e.g.,
Mood Disorder, Anxiety Disorder, Dissociative Disorder,
or a Personality Disorder).

Code based on type:

314.01 Attention-Deficit/Hyperactivity Disorder,
Combined Type: if both Criteria Al and A2 are met for
the past 6 months

314.00 Attention-Deficit/Hyperactivity Disorder,
Predominantly Inattentive Type: if Criterion Al is met
but Criterion A2 is not met for the past 6 months

314.01 Attention-Deficit/Hyperactivity Disorder,
Predominantly Hyperactive-Impulsive Type: if Criterion
A2 is met but Criterion Al is not met for the past 6
months

(DSM-IV, 78-85)

This nomenclature represents a return to consideration of

each of the three behavioral elements equally, unlike DSM-

III-R criteria (American Psychiatric Association, 1987),

which included only the ill-defined category of

undifferentiated attention deficit disorder to classify

predominantly inattentive children. As noted above,

significant differences have been found between the ADHD-

combined group and children who primarily displayed

inattentive symptoms (Goodyear & Hynd, 1992).











ADHD With and Without Hyperactivity


Comparison Studies of Children
with ADD/H and ADD/WO


Groups of children with ADD, with and without

hyperactivity, differed significantly in several respects

(Lahey et al., 1987). Children with ADD/H were more

impulsive, younger at the time of clinic referral, and had

significantly higher rates of overt conduct problems than

children with ADD/WO. Children with ADD/H were more likely

to be placed in a classroom for children with severe

behavior problems (Barkley, DuPaul, & McMurray, 1990). Both

groups of children experience social isolation, but children

with ADD/H have been found to experience rejection by peers,

while children with ADD/WO are withdrawn (Cantwell & Baker,

1992). ADD/H children also had less self-control and

significantly higher ratings of both internalizing and

externalizing behaviors on the CBCL than their ADD/WO

counterparts (Barkley, DuPaul, & McMurray, 1990).

The symptoms of children with ADD/H were often

considered more disruptive by teachers and parents,

resulting in earlier referral to clinics (Lahey et al.,








11

1987). In fact, research has indicated that children with

ADD/H were referred to clinics one year earlier than

children with ADD/WO (Goodyear & Hynd, 1992), and clinic

referrals of ADD/H children resulted from their disruptive

behaviors (Cantwell & Baker, 1992). ADD/WO children were

more likely to be referred for academic difficulties and

depression, symptoms that could be secondary to attention

deficits (Cantwell & Baker, 1992).

Children with ADD/WO have been rated by their teachers

as having a slower cognitive tempo, or speed of problem

solving (Lahey et al. 1987; Lahey, Schaughency, Frame, &

Strauss, 1985). Other researchers have described these

children as daydreamy, confused, and lost in thought

(Barkley, DuPaul, & McMurray, 1990). Symptoms of

internalizing behavior problems, such as anxiety,

depression, and obsessive-compulsive behaviors, were found

in children with ADD/WO by (Lahey et al., 1987), a result

confirmed in later studies (Barkley, DuPaul, & McMurray,

1990). Children with ADD/H had significantly more overt

conduct problems, but the two groups did not have

significant differences in the number of covert problems

such as lying and truancy.










Sluggish cognitive tempo in children with ADD/WO has

been a consistent finding in the research (Lahey et al.,

1988; Barkley, DuPaul, and McMurray, 1990). A factor-

analytic investigation of both the teacher-completed SNAP

checklist (Pelham, Atkins, & Murphy, 1981) and a set of

clinician-rated symptoms provided evidence for slowed

cognitive tempo, inattention, and disorganization in

children with ADD/WO (Lahey et al., 1988). The SNAP yielded

two factors, inattention-disorganization and motor

hyperactivity-impulsivity, suggesting that inattention can

be separated from hyperactivity, resulting in at least two

distinct behavioral syndromes involving attention. In

addition to inattention-disorganization and hyperactivity-

impulsivity, a factor identified as sluggish cognitive tempo

emerged from the clinician ratings of clinic-referred

children. Slowed cognitive tempo may not have been

identified on the SNAP because no items on the checklist are

related to this symptom cluster (Lahey et al., 1988).

Sluggish cognitive tempo was related to the drowsiness and

forgetfulness that had been previously identified (Lahey,

Schaughency, Frame, & Strauss, 1985) in teacher ratings of

children with ADD/WO. In addition, slowed tempo is










consistent with teacher ratings that identified ADD/WO

children as daydreamy, apathetic, and lethargic (Barkley,

DuPaul, & McMurray, 1990).

The slowed tempo, daydreaminess, and lethargy displayed

by children with ADD/WO may result from a greater

preoccupation with internal stimuli, rather than the

disinhibition that characterizes children with ADD/H

(Barkley, DuPaul, & McMurray, 1990). Although children of

both subtypes were rated as inattentive in school, children

with ADD/H exhibited more disruptive behaviors, while

children with ADD/WO were more often seen as unmotivated

(Barkley, DuPaul, & McMurray, 1990). There were also

differences between the family psychiatric histories of the

two groups. Relatives of children with ADD/WO were more

likely to have a history of anxiety disorder, while

relatives of children with ADD/H had a higher incidence of

aggressive behavior and substance abuse (Barkley, DuPaul, &

McMurray, 1990). This was consistent with the conclusions

of a review that suggested an

"attentional/cognitive/anxiety" constellation of symptoms in

ADD/WO, rather than the "attentional/behavioral/impulsive"

characteristics of ADD/H (Goodyear & Hynd, 1992).












Neuropsychological Studies of ADD/H
and ADD/WO Children


Differences between ADD/H and ADD/WO children have been

found to exist on neuropsychological measures, but the exact

nature of these differences was not always clear.

Methodological difficulties, especially the relative rarity

of children with ADD/WO made it difficult to carry out these

studies (Goodyear & Hynd, 1992). Some authors suggested

that behavioral, rather than neuropsychological, criteria

should be used to differentiate between the subtypes (Hynd,

et al., 1989). These researchers found that children with

attention deficits and clinic-referred controls had similar

performances on simple reaction time tasks. A task

requiring speeded matching of letter strings, the most

difficult task in the study, did discriminate between

children with attention deficits and clinic-referred

controls, with the ADD children performing worse than the

control children. However, there was no significant

difference in the performance of ADD/H and ADD/WO children

on these tasks, suggesting little difference in the

neuropsychology of the subtypes (Hynd et al., 1989).











Recent changes in methodology have resulted in more

consistent findings of cognitive differences between the

attention deficit subtypes, differences that are consistent

with the behavior pattern of each group (Goodyear & Hynd,

1992). A review of the literature indicated that there were

differences in information processing styles between the

subtypes (Goodyear & Hynd, 1992). Children with ADD/H were

hypothesized to have input difficulties related to their

attention deficits, while ADD/WO children were believed to

have output problems related to their slower rate of

cognition, and deficits in automatized information

processing similar to those of children with learning

disabilities. Support for this view came from findings that

children with ADD/H were impaired on tests of sustained

attention and behavioral inhibition, while children with

ADD/WO had deficits in focused attention and slowed

cognition (Barkley, DuPaul, & McMurray, 1990). These

authors reported differences between the two subtypes in the

performance of several tasks. ADD/WO children were found to

have significantly more difficulty than ADD/H children on

the WISC-R Coding subtest and on tests of long-term verbal

memory. Children with ADD/WO demonstrated lower levels of











off-task behaviors and less impulsivity during a vigilance

task, but their overall performance was similar to that of

children with ADD/H (Barkley, DuPaul, & McMurray, 1990).

Neuropsychological tests of fine motor speed, planning,

sequencing, and problem solving did not distinguish ADHD

subgroups in a study by Barkley, Grodzinsky, and DuPaul

(1992) or more recently in research by Barkley and

Grodzinsky (1994).

Overall, research has indicated that of the DSM-IV

subtypes, ADHD-Combined and ADHD-Primarily Inattentive have

sufficient empirical support. The evidence for the third

subtype, ADHD-Primarily Hyperactive/Impulsive, was not as

strong and the basis for this diagnosis was not clear. It

is the combination of motor hyperactivity and attentional

components that makes the children with ADHD-Combined type

of interest to the current study. Further references to

children with ADHD will include only this group of children.

The different cognitive style of children with ADD/WO may

introduce confounds into a study of motor learning and they

will be excluded from the current study.










Characteristics of ADHD


Sex Differences in Children with ADHD


Sex differences in the behavior of ADHD children have

generally not been supported by research (Breen, 1989),

although some behavioral and cognitive differences have been

found (Berry, Shaywitz, & Shaywitz, 1985). Boys with ADHD

were more aggressive and harder to control at school,

perhaps resulting in a higher rate of referral to clinics

than girls with ADHD (Berry, Shaywitz, & Shaywitz, 1985).

Girls with ADHD demonstrated significantly fewer aggressive

and disruptive behaviors, but significantly more cognitive

deficits and a higher likelihood of rejection by peers than

boys with ADHD (Berry, Shaywitz, & Shaywitz, 1985). Verbal

IQ was significantly lower in girls with ADHD and they were

rated as having more language difficulties than boys. No

significant sex differences were found in attention,

hyperactivity, or impulsivity, and the overall behavioral

profile for both ADHD boys and girls was similar. These

results suggested that, because of their less disruptive

behavior, girls with ADHD who do not have other academic or











psychiatric problems remain unreferred, and their needs

often remain unmet (Berry, Shaywitz, & Shaywitz, 1985).

Similar attention and behavioral profiles in boys and

girls with ADHD have been supported in the research (Breen,

1989). Boys and girls with ADHD were rated as more

disruptive than controls in a controlled academic setting,

but there were no significant differences in behavior

between boys and girls with ADHD (Breen, 1989). Consistent

with Berry, Shaywitz, and Shaywitz (1985), the severity of

disruptive behaviors exhibited by girls with ADHD in a

controlled parent-child interaction was not significantly

worse than normal controls nor significantly better than

boys with ADHD. Both boys and girls with ADHD were rated by

teachers as having more externalizing behaviors than

controls and had similar difficulties on a vigilance task.

This indicated that both boys and girls with ADHD have

significant difficulties in sustained attention (Breen,

1989). No contrasts were found on measures of overall

cognitive ability. Breen (1989) interpreted these results

as supporting the similarity of ADHD symptoms in boys and

girls.











Developmental Problems Reported
in Children with ADHD


Children with ADHD have presented with a number of

developmental problems such as delays in learning to talk,

and speech and language dysfunction (Szatmari, Offord, &

Boyle, 1989b; Barkley, DuPaul & McMurray, 1990). The speech

and language problems manifested by children with ADHD can

become serious enough to require later referral for speech

and language therapy (Cantwell & Baker, 1992). As infants,

children with ADHD may have difficulty in establishing

regular sleeping and eating schedules (Hartsough & Lambert,

1985). They have been found to be significantly more

restless and overactive as infants and may be more

persistent in their demands (Barkley, DuPaul, & McMurray,

1990).

Early motor difficulties and later coordination

problems are common in children with ADHD. They crawl at a

significantly later age compared with normal controls

(Hartsough & Lambert, 1985). Children with ADHD have been

found to be delayed in learning to walk and are reported by

parents to be clumsy as children (Szatmari, Offord, & Boyle,

1989b; Mitchell, Aman, Turbott, & Manku, 1987). Although










his review noted that research results conflict, Barkley

(1990) stated that up to 52% of children with ADHD may have

poor motor coordination, especially with fine motor skills.

In addition, children with ADHD have been shown to have

difficulties reproducing sequential hand movements (Breen,

1989). Compared with both normal controls and children with

learning disabilities, children with ADHD are significantly

more likely to be described as having poor coordination

(Barkley, DuPaul, & McMurray, 1990).


Accidents and Iniury Risk in
Children with ADHD


The impulsivity and aggressiveness of ADHD children may

lead them to engage in physically dangerous activities

(Barkley, 1990). Children with ADHD recognized dangerous

situations as well as controls. Nonetheless, they rated

themselves as more likely to engage in hazardous activities

than did normal controls and underestimated the potential

severity of injuries (Farmer & Peterson, 1995). They also

generated fewer avoidance behaviors, suggesting a lack of

knowledge about safety rules (Farmer & Peterson, 1995).

Fractures and accidental poisonings are common among










children with ADHD (Szatmari, Offord, & Boyle, 1989b).

Children with ADHD frequently suffer four or more serious

accidents during childhood, and these may include head, eye,

and tooth injuries (Hartsough & Lambert, 1985). Although

this characteristic of ADHD can be quite problematic for

caregivers, many of these accidents may be preventable if

parents are aware of the need for extra precautions

(Szatmari, Offord, & Boyle, 1989b).


Health Problems in Children with ADHD
and Their Mothers


Chronic health problems in infancy and childhood have

also been associated with ADHD (Hartsough & Lambert, 1985).

Controlling for medication prescribed to treat ADHD

symptoms, children with ADHD are prescribed medication

significantly more often than normal controls (Szatmari,

Offord, & Boyle, 1989b). Asthma, allergies, and ear

infections have all been found in ADHD children at a higher

rate than in normal controls (Hartsough & Lambert, 1985).

Barkley (1990) noted that minor physical anomalies, such as

increased head circumference, eyes placed farther apart than










normal, and fine hair are all significantly more common in

children with ADHD than in normal controls.

Mixed evidence exists concerning the influence of

maternal health and pre- and perinatal factors on the

incidence of ADHD. Poor maternal health, toxemia or

eclampsia during pregnancy, and a maternal age younger than

twenty were found to differentiate mothers of ADHD children

from mothers of normal controls (Hartsough & Lambert, 1985).

Significantly longer labor and later gestational age were

also correlated with ADHD in the child. Another study

(Barkley, DuPaul, & McMurray, 1990) found evidence for none

of these factors. Low birth weight was found to be

correlated with ADHD by Szatmari, Offord, and Boyle (1989b)

and Mitchell, Aman, Turbott, and Manku (1987), but was not

found to be significant by Hartsough and Lambert (1985) or

Barkley, DuPaul, and McMurray (1990). Research on the

effect of fetal distress at birth has also produced

contradictory findings, with some research indicating a

significant correlation with ADHD (Hartsough & Lambert,

1985), while others do not (Barkley, DuPaul, & McMurray,

1990). The existence of difficulties in toilet training has

also been disputed by investigators. Nevertheless, it








23

seemed that these problems are present in some ADHD children

and may be significantly more common than in children

without ADHD (Hartsough & Lambert, 1985).


Comorbid Psychiatric Diagnoses
in Children with ADHD


Hyperactivity is closely related to other disruptive

behavior disorders, as research has found that 40% to 60% of

children with ADHD have been found to have a comorbid

conduct disorder (Szatmari, Offord, & Boyle, 1989a; Barkley,

Fischer, Edelbrock, & Smallish, 1990). The Conduct Disorder

and Attention Problem subscales of the Revised Behavior

Problem Checklist (RBPC) had a shared variance of between 20

and 31 percent (Quay & Peterson, 1983). In addition there

were high correlations between attention-deficit and

antisocial behavior factors on both the Conners Teacher

Rating Scale (TRS) and the original Behavior Problem

Checklist (BPC; Arnold, Barneby, & Smeltzer, 1981). These

correlations emerged when these authors factor-analyzed

items from these scales, treating all 93 items as if they

constituted a single measure. The hyperkinetic factor on

the two scales correlated at r = .86, supporting the










criteria used for measuring hyperactivity (Arnold, Barneby,

& Smeltzer, 1981). The hyperkinetic factor on the TRS and

RBPC had correlations of between .69 and .77 with the

rebellious unsocialized and antisocial immature factors on

the TRS, indicating significant overlap between disruptive

behavior disorders (Arnold, Barneby, and Smeltzer, 1981).

Despite the high correlations between ADHD and other

disruptive behavior disorders, evidence supported ADHD as a

distinct diagnosis (Blouin, Conners, Seidel, & Blouin,

1989). Comparisons between groups of clinically referred

children have shown that inattention and impulsivity

separate ADHD children from conduct disordered or anxious

children (Halperin et al, 1993). The codiagnosis of

oppositional or conduct disorder is often given to children

with ADHD when they respond to conflicts in structured

situations with violations of major rules and laws (Barkley,

1990; Wells & Forehand, 1985). Comorbid conduct disorder

was associated with increased cigarette, alcohol, and

marijuana use in children with ADHD compared to controls

(Barkley, Fischer, Edelbrock, & Smallish, 1990).

Children with ADHD are also frequently diagnosed with a

comorbid mood disorder, such as depression or bipolar











disorder (Szatmari, Offord, & Boyle, 1989a). Attention

difficulties and psychomotor disturbances are overlapping

symptoms that may cause difficulty in making a differential

diagnosis between ADHD and a mood disorder (Milberger et

al., 1995). However, research has indicated that between 90

and 100 percent of children retain the diagnosis of ADHD

after controlling for this overlap (Milberger, et al.,

1995). This suggested that ADHD can be distinguished from

comorbid mood disorders and that treatment plans should

consider all comorbid diagnoses (Milberger et al., 1995).


Learning Problems in Children with ADHD


Children with ADHD are difficult for both parents and

teachers to control because of their inability to stay on

task, failure to follow instructions, and distractibility.

In addition, children with ADHD were rated by teachers as

displaying significantly more aggressive behaviors than

normal controls (Barkley, DuPaul & McMurray, 1990). Mild

ADHD symptoms in the home can become extremely problematic

in the structured environment of the classroom, and teachers

are likely to be the first to recognize ADHD in a child

(Szatmari, Offord, & Boyle, 1989a). Teachers often have








26

more experience in evaluating behaviors and deciding whether

or not they are age-appropriate, and they observe the impact

of a child's disruptive behavior (Simeon & Wiggins, 1993).

Disruptive classroom behaviors were coupled with

academic difficulties in children with ADHD, as they were

more likely than normal controls to have been held back in

school, placed in special education, or received tutoring

(Barkley, DuPaul & McMurray, 1990; Faraone et al., 1993).

Compared to the proportion of variance accounted for by

symptoms of ADHD alone, comorbid conduct disorders had

little additive effect on problems in school, although they

increased the risk of dropping out of school in adolescence

(Barkley, Fischer, Edelbrock, & Smallish, 1990). The

independent effect of ADHD symptoms was related to their

adverse impact on academic performance and the correlation

of these symptoms with cognitive deficits (Barkley, Fischer,

Edelbrock, & Smallish, 1990; Faraone et al., 1993).

There is a highly significant association between ADHD

and developmental learning disabilities (Cantwell & Baker,

1991), but the meaning of this association has been disputed

(McGee & Share, 1988). In a review of the literature

related to ADHD and academic difficulties, McGee and Share











(1988) downplayed organic or environmental common causes of

the disorders. Instead, they defined ADHD as a conduct

problem resulting from the learning disabled child's

inability to understand academic material (McGee & Share,

1988). Children with comorbid ADHD and reading disabilities

have been found to exhibit processing difficulties similar

to non-ADHD children with reading disabilities (Pennington,

Groisser, & Welsh, 1993). This finding appeared to support

the idea that academic difficulties are a causal factor in

some children diagnosed with both ADHD and LD.

Although children with learning disabilities have been

rated by their teachers as showing evidence of attention

problems (Barkley & Grodzinsky, 1994), the conclusion that

academic frustration is the primary causative factor in ADHD

is problematic. A dissociation has been found between the

symptoms of primary ADHD and those of reading disabilities

(Pennington, Groisser, & Welsh, 1993), and the link between

learning problems and ADHD often begins well before the

child enters school (Hinshaw, 1992). Inconsistent

definitions of both ADHD and learning disabilities have been

used in the research (Semrud-Clikeman et al., 1992) and

while learning disabilities may contribute to disruptive








28

behaviors, they are not necessarily causative of ADHD. For

example, the ADHD/LD children in the Pennington, Groisser,

and Welsh (1993) study displayed significant conduct

problems in addition to attention deficits. The children

with ADHD/LD also had significantly higher rates of family

instability and this combined with academic failure, rather

than a primary ADHD, may have led to disruptive behavior in

some of these children (Pennington, Groisser, & Welsh,

1993).

Further evidence against the causative link between

learning disabilities and ADHD was provided by findings that

preschoolers with ADHD have difficulties with independent

work and following rules in a structured setting

(Alessandri, 1992). Developmental problems related to ADHD

may cause cognitive impairments that lead to academic

difficulties, even when there is no co-occurring learning

disability diagnosis (Szatmari, Offord, & Boyle, 1989b).

Symptoms of ADHD are often present before 4 years of age

(Barkley, Fischer, Edelbrock, & Smallish, 1990) and academic

problems were linked to pre-existing impulsivity and

inattention in children with ADHD (Barkley,1990). Prior to

enrollment in school, or even if enrolled in preschool, a








29

child would be unlikely to experience the levels of academic

frustration described by McGee and Share (1988). Each child

should be evaluated independently and interventions should

be directed at the primary deficit (McGee & Share, 1988), as

comorbidity between learning disabilities and ADHD resulted

in greater learning problems than ADHD alone (Kataria, Hall,

Wong, & Keys, 1992).

As noted above, past comorbidity studies used

inconsistent criteria for defining learning disabilities,

resulting in considerably different conclusions (Semrud-

Clikeman et al., 1992). Children with ADHD are at

significant risk for school failure, and remediation of

academic deficits may be as important as treatment of

disruptive behaviors (Hinshaw, 1992). Research suggested

that, regardless of learning disability, children with ADHD

are more likely to be placed in a classroom for children

with disruptive behaviors, perhaps making them less likely

to receive academic remediation (Barkley, DuPaul, &

McMurray, 1990). Inconsistent criteria for defining

learning disabilities in the literature ranged from labeling

any academic deficit as a learning disability to extremely

stringent criteria limiting learning disabilities to those











children who scored in the borderline range on achievement

tests (Hinshaw, 1992). Shifting criteria may lead either to

overly inclusive and expensive academic interventions for

all children with academic deficits, or to a failure to

provide children with ADHD academic remediation because

their disruptive behavior prompts teachers to ignore

learning problems (Semrud-Clikeman et al., 1992). A

comparison of three increasingly exclusive definitions of

learning disability indicated that the moderate definition

of learning disability, provided for under Public Law 94-

142, was effective in correctly classifying children with

comorbid diagnoses (Semrud-Clikeman et al., 1992). Under

criteria for Public Law 94-142, children with ADHD were

shown to have significantly higher rates of both reading and

arithmetic learning disabilities compared to normal

controls, suggesting that careful academic screening of

these children is necessary (Semrud-Clikeman et al., 1992).

The impact of oppositional and conduct problem

behaviors on early academic difficulties is often

exacerbated by the presence of ADHD and attention deficits

increase the difficulty of remediation (Hinshaw, 1992). The

combination of ADHD with conduct disorder greatly increases











the risk of suspension, expulsion, dropping out of school,

and the development of adolescent delinquency (Barkley,

Fischer, Edelbrock, & Smallish, 1989; Hinshaw, 1992).

Academic remediation or behavior modification alone may

ameliorate disruptive behavior (McGee and Share, 1988), but

simultaneous treatment of academic and behavior problems has

been found to be more effective for children with ADHD/LD

(Hinshaw, 1992).


Social Relationships of Children with ADHD


Interpersonal relationships, whether with adults or

other children, have been found to be problematic for

children with ADHD (Szatmari, Offord, & Boyle, 1989b) and

rejection by peers is common (Barkley, 1990). In

interactions with adults, children with ADHD had significant

rates of noncompliance when asked to complete a task, and

they often did not finish assigned tasks (Alessandri, 1992).

In return, teachers disciplined children with ADHD more

frequently than they disciplined their non-ADHD counterparts

(Alessandri, 1992).

Preschoolers with ADHD were shown to have patterns of

social interaction and play that differed significantly from








32

normal controls (Alessandri, 1992). Preschoolers with ADHD

were less creative and developmentally advanced in their

play. They played alone more often than control children

and had significantly fewer conversations with peers. In

group situations, ADHD children failed to understand social

rules, became overstimulated, and lost control of their

behavior (Berry, Shaywitz, & Shaywitz, 1985). Peer

rejection likely has an increasingly negatively impact on a

child's self-esteem, leading to a higher frequency of

disruptive behaviors in older children with ADHD

(Alessandri, 1992).

The combination of ADHD and LD significantly increases

the risk for social rejection (Flicek, 1992). Peer

nomination identified ADHD children as disruptive, while LD

children were seen as having low peer popularity and few

leadership skills. The group of combined ADHD/LD children

was rejected by, and fought with, peers significantly more

often than normal controls, a finding that was not repeated

in the ADHD-only or LD-only groups (Flicek, 1992). Although

ADHD alone did not result in significant social rejection,

these children were rated as more disruptive. Children with

ADHD/LD may combine aggressive, disruptive ADHD symptoms











with deficient cognitive processing and incorrectly view

their peers as hostile and rejecting in all situations

(Flicek, 1992). This perception may lead to increased

conflict with, and rejection by, peers. Evaluations of

social problems may lead to more effective interventions if

they include both cognitive and behavioral factors (Flicek,

1992).


Long-Term Outcome of Children with ADHD


Studies have indicated that up to 80% of children

diagnosed with ADHD continue to show salient characteristics

of the disorder well into adolescence (Barkley, Fischer,

Edelbrock, and Smallish, 1990). Adolescents with ADHD were

significantly more likely than normal controls to have a

comorbid conduct disorder (Barkley, Fischer, Edelbrock, &

Smallish, 1990). Consistent with this, adolescents with

ADHD were more likely to have been involved in antisocial

activities, including theft, assault, and destruction of

others' property (Barkley, Fischer, Edelbrock, & Smallish,

1990). Adolescents with ADHD were somewhat more likely to

have been in auto accidents than control subjects, but the

risk was not significantly higher. Adolescents with











comorbid ADHD and conduct disorder were at significantly

greater risk for substance abuse (Barkley, Fischer,

Edelbrock, & Smallish, 1990).

Symptoms of ADHD may manifest themselves in college

students as poor study skills and learning difficulties, and

students with previously undiagnosed ADHD may feel that they

are not working up to their potential (Heiligenstein &

Keeling, 1995). Although college students with ADHD may

have developed compensatory strategies, they still have

noticeable problems in sustained attention (Heiligenstein &

Keeling, 1995). College students with a childhood diagnosis

of ADHD demonstrated poor concentration on a 20-minute

letter cancellation task (Shaw & Giambra, 1993). When

compared to control groups that included both normals and

students who reported some childhood ADHD symptoms, students

with ADHD reported more spontaneous thoughts unrelated to

the task, and were impulsive in their responses to the task.

The results suggested that symptoms of ADHD do not always

disappear with age, and adults with ADHD continue to have

poor modulation of internal processes, especially when bored

(Shaw & Giambra, 1993; Douglas, 1984). In an attempt to

relieve boredom and achieve an optimal level of stimulation,











regulatory mechanisms in students with ADHD fail to screen

spontaneous, unrelated thoughts (Douglas, 1983). These

thoughts then disrupt concentration and make completion of

experimental tasks or academic work more difficult (Shaw &

Giambra, 1993).

Although the continuation of ADHD symptoms into

adulthood has been a controversial subject, several studies

have provided evidence supporting adult ADHD (Mannuzza et

al., 1993; Biederman et al., 1993). Symptoms of ADHD have

been found to persist in at least 11% of subjects with a

childhood diagnosis of the disorder, a figure that the

authors believed to be an underestimate (Mannuzza et al.,

1993). The educational attainment and socioeconomic status

of adults with ADHD was significantly lower than achieved by

controls (Mannuzza et al., 1993; Biederman et al., 1993).

Although comorbid psychiatric diagnoses played some role in

adult educational and occupational status, history of ADHD

appeared to have a unique impact (Mannuzza et al., 1993).

Most adults who had been diagnosed as ADHD in childhood were

employed, but few held professional positions and compared

to controls, a greater proportion owned their own

businesses, perhaps to compensate for an inability to










conform to regular schedules and rules set by others

(Mannuzza et al., 1993). Compared to normal controls, a

greater percentage of adults with ADHD were diagnosed with a

comorbid psychiatric disorder, most commonly antisocial

personality disorder (Biederman et al., 1993). Similar to

the findings for educational and occupational status, adults

with uncomplicated ADHD were at greater risk for substance

abuse than controls (Mannuzza et al., 1993; Biederman et

al., 1995). Comorbid antisocial personality disorder added

greatly to this risk (Biederman et al., 1995).


Family Characteristics


Family and household variables, including urban

residence, family receiving public assistance, single parent

as head of household, and inadequate family functioning are

all significantly correlated with ADHD (Szatmari, Offord, &

Boyle, 1989b). In addition to these variables, children

with ADHD experience frequent changes in residence compared

to control children (Barkley, Fischer, Edelbrock, &

Smallish, 1990). Parents of children with ADHD have a

significantly greater incidence of psychiatric diagnoses











than parents of children with developmental delays (Roizen

et al., 1996).

Fathers of children with ADHD were reported to have

high rates of antisocial behavior and frequent changes in

employment (Barkley, Fischer, Edelbrock, & Smallish, 1990).

For example, fathers of children with ADHD engaged in

significantly more childhood antisocial behaviors and 11.2%

of these fathers were diagnosed as having antisocial

personality disorder, while only 1.6% of the fathers of

normal controls received this diagnosis. Fathers of

children with comorbid ADHD and conduct disorder had

somewhat higher rates of antisocial behaviors than fathers

of children with uncomplicated ADHD. However, this

difference did not reach significance, which indicated that

antisocial behavior in the father is an important correlate

of uncomplicated ADHD. Psychopathology in fathers of

children with ADHD may render the father ineffective as a

parent and produce an unstable environment for the child,

negatively impacting the child's behavior (Barkley, Fischer,

Edelbrock, & Smallish, 1990). Mothers of children with ADHD

have been found to be younger, less educated, and had a

higher rate of separation and divorce than mothers of











control children (Barkley, Fischer, Edelbrock, & Smallish,

1990). Married mothers of children with ADHD rated their

marriages as less satisfying than mothers of control

children (Barkley, Fischer, Edelbrock, & Smallish, 1991).

Family conflict was significantly more frequent in the

lives of children with ADHD than in children without

attention problems (Barkley, Fischer, Edelbrock, & Smallish,

1991). Mothers of ADHD children rated their family

environment as extremely stressful, with the impulsivity and

hyperactivity of the child playing an important role in

exacerbating this stress (Anastopoulos, Guevremont, Shelton,

& DuPaul, 1992). Aggressiveness in a child with ADHD added

to this stress, and comorbid oppositional-defiant disorder

led to higher levels of parenting stress than ADHD alone.

Health problems in childhood, often a characteristic of ADHD

(Hartsough & Lambert, 1985), was the final child-related

stressor identified in parents of children with ADHD

(Anastopoulos, Guevremont, Shelton, & DuPaul, 1992). These

findings were similar to parent ratings of the behavior of

adolescents with ADHD, who continue to have conflicts with

family members (Barkley, Fischer, Edelbrock, & Smallish,

1991). Although ADHD symptoms appeared to have an








39

independent contribution, comorbid oppositional-defiant or

conduct disorders made a significant contribution to family

conflicts (Anastopoulos, Guevremont, Shelton, & DuPaul,

1992).

Observed interactions between children with ADHD and

their mothers provided evidence that, in a neutral

situation, children with ADHD used a more negative

conversational style than controls (Barkley, Fischer,

Edelbrock, & Smallish, 1991). Mothers of children with

comorbid Oppositional-Defiant Disorder (ODD) and ADHD used

more commands and put-downs than mothers of normal controls

or of children with uncomplicated ADHD (Barkley, Fischer,

Edelbrock, & Smallish, 1991). Mothers of children with

comorbid ADHD/ODD also reported significantly more

subjective stress than mothers of children with

uncomplicated ADHD (Anastopoulos, Guevremont, Shelton, &

DuPaul, 1992). Symptoms of depression, anxiety,

somatization, and hostility were all found in the mothers of

aggressive ADHD children (Barkley, Fischer, Edelbrock, &

Smallish, 1991). Maternal psychopathology and increased

subjective stress may interact with the negative behavior of

the child to produce parent-child conflict (Anastopoulos,











Guevremont, Shelton, & DuPaul, 1992), while a positive

maternal style may avoid this outcome (Barkley, Fischer,

Edelbrock, & Smallish, 1991). As the interactions between

ADHD children and their parents are likely to remain stable

over time, early intervention is necessary to reduce or

avoid the development of oppositional symptoms (Barkley,

Fischer, Edelbrock, & Smallish, 1991).


Heritability of ADHD


Research has indicated that genetic factors make a

significant contribution to ADHD (Biederman et al., 1990).

Relatives of ADHD children were more likely to be diagnosed

with ADHD than are relatives of either normal or psychiatric

controls (Biederman et al., 1990). Antisocial personality

and mood disorders were also much more common among

relatives of ADHD children than in the control groups.

Consistent with the usual pattern of ADHD, male relatives

were given a diagnosis of ADHD more often than female

relatives, although the increased risk for ADHD compared to

controls occurred without regard to the sex of the relative.

Forty-four percent of the fathers and 19% of the mothers of

ADHD children met diagnostic criteria for ADHD,











significantly higher percentages than in control groups.

Siblings, and especially brothers, of children with ADHD

often had a diagnosis of ADHD (Biederman et al., 1990).

After controlling for socioeconomic status and

intactness of the family, relatives of children with ADHD

children were still significantly more likely than controls

to have a diagnosis of attention deficit disorder (Biederman

et al., 1990). However, these factors also increased the

risk for ADHD in the families of control groups, suggesting

that environmental factors do impact the development of ADHD

symptoms (Biederman et al., 1990). The high rates of

attention problems and increased risk for antisocial

behaviors in fathers of children with ADHD may explain the

high rates of separation and divorce in the homes of these

children (Barkley, Fischer, Edelbrock, & Smallish, 1991).

The heritability of ADHD was supported by twin studies.

Concordance rates for ADHD dizygotic twins are significantly

higher than those for monozygotic twins (Gillis, Gilger,

Pennington, & DeFries, 1992). This finding was stable for

both sexes, strengthening the hypothesis of ADHD

heritability. This study used reading-disabled twins, so it

was possible the findings were influenced by the








42

heritability of learning disabilities, but the authors noted

that the finding of ADHD heritability appeared robust.

Concordance results did not appear to be a result of the

parents confusing the behavior of identical twins (Gillis,

Gilger, Pennington, & DeFries, 1992). However, despite

evidence of a genetic component to ADHD, no research to date

has found a direct link with a particular gene (Alessi,

Hottois, & Coates, 1993). The discovery of a rare thyroid

condition was correlated with ADHD and directly linked with

a particular gene suggested that this gene may be identified

in the future (Alessi, Hottois, & Coates, 1993).

Nonetheless, no evidence has supported the linkage of all

forms of ADHD to a thyroid condition.


Assessment and Treatment


A variety of techniques are used to evaluate attention

deficits in children. Parent and teacher reports are often

used in the assessment of the behavioral aspects of ADHD.

Two of the most commonly used behavior checklists are the

Conners rating scales (Goyette, Conners, & Ulrich, 1978) and

the Child Behavior Checklist (CBCL Achenbach, 1991).

These rating scales have both parent and teacher forms in











order to fully evaluate a child's behavior. Checklists

require raters to report frequencies of various problem

behaviors in children and these ratings are then combined to

produce a profile of the child's behavior. The Conners

rating scales have been shown to be a valid measure of

hyperactive and inattentive behaviors (Trites, Blouin, &

Laprade, 1982). Children with ADHD tended to score highly

on the Externalizing Behaviors scale of the CBCL (Barkley,

1990) because of their overactivity and disruptive

behaviors.

It has been hypothesized that deficits in self-

regulation underlie the symptoms of ADHD (Douglas, 1983).

Poor self-regulation can be defined by four behavioral

components characteristic of children with ADHD (Douglas,

1984). An unusual need for immediate gratification, an

unwillingness to invest effort in demanding tasks, an

inability to inhibit impulsive responses, and a lack of

arousal modulation have all been found in children with

ADHD. The lack of self-regulation in ADHD children has a

number of effects on behavior. These children fail to

utilize knowledge and skills they are known to possess, an

inconsistency in performance often noted by teachers











(Barkley, 1990). Compared to normal children, they are

inefficient in their management of resources, and so they

have difficulty completing tasks even if well motivated

(Douglas, 1984). Self-regulation deficits may cause

deficiencies in sustained attention unrelated to increased

responsiveness to extraneous stimuli (Douglas, 1983). In

addition to impulsive responses to environmental changes,

children with ADHD have problems maintaining attention for

any task (Douglas, 1983).

Sustained attention in ADHD children is commonly

assessed using vigilance tasks such as the Continuous

Performance Test (CPT; Corkum & Siegel, 1993), which

measures sustained attention for infrequent events. During

the CPT, a series of numbers or letters are presented and

the child's goal is to identify the target number/letter or

number/letter sequence. Performance on the CPT can be

influenced by variables related to the task itself, such as

longer intervals between stimuli and the length of time that

the stimulus is displayed (Corkum & Siegel, 1993). When

task difficulty was increased, children with ADHD were

increasingly separated from normal children on performance

measures (Corkum & Siegel, 1993). Children with ADHD became








45

less careful in responding to a CPT task over the course of

the test, suggesting that impairment in sustained attention

is at least partially responsible for ADHD symptoms (Power,

1992). However, if the vigilance task used was designed for

assessment of seriously impaired patients, children with

ADHD may perform at the same level as normal children

(Zametkin et al, 1990). Use of stimulant medication can

alter the performance of an ADHD child on the CPT (Corkum &

Siegel, 1993), as can the presence or absence of an examiner

(Power, 1992). The negative effect of an examiner's absence

was frequently seen in children with ADHD who had strong

hyperactive or aggressive features, who are most prone to

act up when adult supervision is removed (Power, 1992).

It has been argued that deficits in physiological

arousal, rather than problems in sustained attention, are

primarily responsible for ADHD symptoms (Corkum & Siegel,

1993). Physiologically-based underarousal was found in

patients with other disorders of sustained alertness

(Weinberg & Harper, 1993). The concept of physiological

arousal deficits is controversial, however, as children with

attention deficits may become overaroused in some

situations, especially those involving a highly desired











reward (Douglas, 1983). Specific tasks, especially

experimental tests of attention, may not be interesting to

children with ADHD, leading to the appearance of low arousal

(Douglas, 1984). These same children may overreact when the

stimulus is interesting, suggesting that the true deficit is

in modulating their level of arousal. In order to more

fully define the underlying deficits of ADHD, the components

of vigilance need to be analyzed separately (Corkum &

Siegel, 1993).


Pharmacological Treatment of ADHD


Methylphenidate (Ritalin) is one of the most common

psychostimulants used for treatment of children with ADHD

(Barkley, 1990), and up to 77% of children who are placed on

Ritalin experience improvement in behavior (Murray, 1987).

Ritalin is a dopamine agonist, as are its companion

medications, Dexedrine (d-amphetamine) and Cylert (pemoline)

(Murray, 1987). Dopamine and other catecholamines are

believed to be involved in the control of attention (Hynd,

Voeller, Hern, & Marshall, 1991) and most children with ADHD

respond positively to these drugs (DuPaul, Barkley, &

McMurray, 1991). Ritalin is generally believed to increase











abnormally low metabolic rates in the striatal and

periventricular regions of these children (Lou et al, 1989).

The other stimulant medications apparently have similar

effects, although Cylert has been found to be slightly less

effective in moderating the behavior of ADHD children

(Conners & Taylor, 1980). Cylert is slower to act than

Ritalin, often requiring 3 to 4 weeks to have a therapeutic

effect (Dulcan, 1985) and it has a longer half-life,

averaging 12 hours, as opposed to 2 to 3 hours for Ritalin

(DuPaul & Barkley, 1990). The behavioral effects of Ritalin

and Dexedrine last around 4 hours (Dulcan, 1985), while

these effects are seen for up to 2 weeks after ending

administration of Cylert (Conners & Taylor, 1980). Ritalin

does not accumulate in the system (Dulcan, 1985), and no

traces of this drug are found in the urine after 12 hours

(DuPaul, Barkley, & McMurray, 1991). Slow-release forms of

Ritalin (methylphenidate SR) are commonly prescribed,

especially when administration of medication during the

school day (DuPaul, Barkley, & McMurray, 1991) or after-

school behavior (Simeon & Wiggins, 1993) are concerns.

Slow-release forms of Ritalin have plasma half-lives ranging

from 2 to 6 hours and behavioral effects that last up to 8











hours (DuPaul & Barkley, 1990). However, slow-release

preparations may take significantly longer to affect

behavioral change following dose administration (DuPaul,

Barkley, & McMurray, 1991) and behavioral effects may not

last as long as with a small afternoon dose of normal-acting

Ritalin (Simeon & Wiggins, 1993).

Side effects of stimulant medication can include

decreased appetite, insomnia, anxiety, and irritability

(DuPaul, Barkley, & McMurray, 1991). An afternoon increase

in ADHD behaviors is also common in children with ADHD who

take medication during the day. The lack of normal growth

is frequently seen in children with ADHD who are taking

stimulant medication and Dexedrine has been found to have a

more deleterious effect on growth than other stimulants

(Dulcan, 1985). Duration of treatment and amount of

appetite suppression appear to be important factors

affecting the child's growth, and this effect can be

modulated with drug holidays (Dulcan, 1985). Development of

motor tics is a relatively rare side effect and it can

difficult to predict, but a family history of motor

syndromes is a contraindication to stimulant treatment. As

with any pharmacologic treatment, a careful history should











be taken before stimulant medication is prescribed (DuPaul,

Barkley, & McMurray, 1991).

Antidepressants have also been found to be effective in

some ADHD children who are unresponsive to psychostimulants,

but their use should be closely monitored because of

potential side effects that may be more severe than those of

the stimulants (DuPaul, Barkley, & McMurray, 1991).

Research into the efficacy of fluoxetine (Prozac) indicated

that it may provide an alternative treatment for ADHD, with

less serious side effects than other antidepressants

(Barrickman et al., 1991).


Effects of Stimulant Medications
on Cognition and Behavior


Ritalin use has produced significant increases in

performance on arithmetic, paired-associate learning, and

complex word generation tasks, but not on a task measuring

spelling ability (Douglas, Barr, O'Neill, & Britton, 1986).

Children with ADHD were able to better focus on tasks and

use their time efficiently. Cylert produced similar

improvements in cognitive functioning and may actually be

somewhat more effective with tasks requiring visuomotor











planning and precision (Conners & Taylor, 1980). Improved

scores on word generation and paired-associate learning

indicated that stimulant medication does not effect only the

child's effort level, but also the ability to organize and

process material. Positive changes in the children's

behavior accompanied cognitive improvements, an indicator of

increased self-control. Stimulant medication appeared to

increase the ability of children with ADHD to maintain an

optimal level of cognitive effort (Douglas, Barr, O'Neill,

and Britton, 1986).

Dosage levels have been shown to affect both behavioral

and cognitive measures of ADHD (Douglas et al., 1988), and

there seems to be an optimal therapeutic dose, beyond which

there are diminishing returns (Rapport, Denney, DuPaul, &

Gardner, 1994). Improved performance of children with ADHD

on both simple reaction time and complex information-

processing tasks was correlated with increased stimulant

dosage (Douglas et al., 1988). Academic and behavioral

improvements have also been reported on clinician and

teacher ratings (Rapport, Denney, DuPaul, & Gardner, 1994),

confirming earlier findings of improvement on parent

behavior ratings (Conners & Taylor, 1980). These findings











to support the hypothesis that in addition to improved

behavior and greater effort, stimulant medication increases

self-regulation in ADHD children (Douglas et al., 1988).

However, there appeared to be a limit to medication

efficacy. On paired-associate learning, improvement in

performance did not continue to increase with stimulant

dosage (Douglas et al., 1988), and children's academic

performance does not increase significantly with increasing

dosages (Rapport, Denney, DuPaul, & Gardner, 1994). These

results were consistent with the self-regulation hypothesis,

as children with ADHD were believed to have improved their

performance to the limit of their ability at moderate doses

of Ritalin (Douglas et al., 1988). At higher dosage levels,

ADHD children may begin to over-regulate themselves and they

become overly cautious in responding, resulting in decreased

performance. Although not all children responded positively

to the medication in all situations, the authors indicated

that every child displayed positive effects on several

measures. This called into question the practice of

evaluating a child's response to medication based on a

single measure (Douglas et al., 1988).








52

Cognitive problems may precede behavioral problems when

a child is responding adversely to medication (Swanson et

al., 1991). Medication may be overprescribed as clinicians

ignore negative cognitive reactions in favor of positive

changes in behavior (Swanson et al., 1991). In addition,

there appeared to be a subset of children with ADHD who

receive minimal benefit from medication, especially in

classroom situations (Rapport, Denney, DuPaul, & Gardner,

1994; DuPaul, Barkley, & McMurray, 1994). Using a paired-

associate task, approximately 30% of children with ADHD were

classified as having a negative cognitive response to

Ritalin, as measured by a quadratic response curve, a curve

most often seen in difficult tasks (Swanson et al., 1991).

Absolute doses of medication may also be more beneficial to

children than dosage based on weight, as learning curves

indicated that absolute doses provided stable improvement in

learning for children of various weights. Learning curves

revealed that heavier children may actually need less

medication than indicated by a standard weight-based

prescription (Swanson et al., 1991).

Although stimulant medication appeared to improve

academic performance in children with ADHD, questions remain











as to its effectiveness on other aspects of their behavior

(DuPaul, Barkley, & McMurray, 1994). Although Ritalin

significantly reduced inattention and impulsivity in a group

of children with comorbid ADHD and internalizing symptoms,

it did not significantly improve the academic functioning of

these children (DuPaul, Barkley, & McMurray, 1994). In

fact, the academic functioning of children with ADHD and a

relatively greater number of internalizing symptoms may

actually decline, although further research is needed to

confirm this result (DuPaul, Barkley, & McMurray, 1994).


Medication Effects on Social Skills


Social behaviors in ADHD children are affected by

medication in several ways (Whalen et al., 1989; Buhrmeister

et al., 1992). Unmedicated children with ADHD were

significantly more socially engaged than controls,

suggesting that these children need social stimulation

(Buhrmeister et al., 1992). These children face

difficulties because their social interactions are generally

considered aversive by other children (Berry, Shaywitz, &

Shaywitz, 1985). Ritalin use resulted in improved peer

ratings of children with ADHD, but these ratings were still











not as positive as those of a normal control group (Whalen

et al., 1989).

Even in situations that demand prosocial behaviors,

children with ADHD have difficulties, despite a desire to

perform well (Buhrmeister et al., 1992). Although children

with ADHD engaged in prosocial behaviors as frequently as

controls, they simultaneously emitted higher rates of

aversive behaviors (Buhrmeister et al., 1992). Medication

reduced the rate of all social behaviors and there was less

responsiveness to social cues, without any increase in

prosocial behaviors. Medicated children with ADHD were

noted to be sad and withdrawn, (Buhrmeister et al., 1992),

but this was disputed by other research (Whalen et al.,

1989). Sadness and withdrawal appeared to negatively affect

peer ratings of these children and indicated that

controlling aversive behavior with medication alone does not

necessarily lead to more positive interactions for ADHD

children (Buhrmeister et al., 1992). Relatively normal

rates of prosocial behavior in unmedicated children with

ADHD suggested that effective interventions are those

focused on reducing aversive behavior, rather than on

increasing prosocial behavior (Buhrmeister et al., 1992).












Behavioral and Combined Treatment Strategies


Treatment of ADHD often involves combining

psychostimulant medication with a behavioral modification

program and parent training (Simeon & Wiggins, 1993;

Barkley, 1983). Training for parents of children with ADHD

generally consists of teaching behavioral principles such as

positive reinforcement and time-out, and having parents

recognize their own contributions to the child's behavior

(Barkley, 1983). Behavioral methods are often directly

related to parent training and involve the application of

contingency management strategies both at home and in

school. The goal of behavior modification programs is to

help the child control his own behavior, but they may be

difficult to implement without concomitant medication

intervention and may be more costly in terms of time and

money (Barkley, 1983; Murray, 1987). Despite these

constraints, behavioral approaches may be useful for

children with ADHD who are not responsive to medication

(Murray, 1987).

The combination of stimulant medication and behavior

therapy improved the behavior of children with ADHD (Murray,











1987), but academic performance was enhanced only by

medication (Carlson, Pelham, Milich, & Dixon, 1992).

Medication also positively influenced the self-ratings of

children with ADHD. The singular effect of medication

indicated deficient self-regulation (Douglas, 1984), and

medication appeared to augment the self-regulatory system.

Behavior therapy alone was found to be as effective as a low

dose of Ritalin in controlling disruptive behavior, but it

did not increase positive self-ratings (Carlson, Pelham,

Milich, & Dixon, 1992). Feedback on the children's

behavior, as applied in this condition, may have helped

control their behavior, but negatively impacted self-

ratings. A combination of behavior therapy and low-dose

medication was as effective in effecting behavior change as

high-dose medication alone, suggesting that combined

treatments can reduce medication use (Carlson, Pelham,

Milich, & Dixon, 1992). The authors noted that between-

subject differences played a significant role in the

effectiveness of either treatment and should be considered

when designing an intervention program.











Effects of Incoordination on Children with ADHD


Difficulty in motor skill learning may have a number of

effects on children with ADHD, both in school (learning to

write and draw) and among their peers (learning skills

required for games). Fewer children with ADHD participate

in organized athletics, possibly as a result of difficulties

in learning the necessary skills (Szatmari, Offord, & Boyle,

1989b). Children with ADHD have been found to experience

significant difficulties learning new motor skills and

adequately performing in sports or other activities

(Szatmari, Offord, & Boyle, 1989b). Despite findings of

developmental difficulties and poor coordination, motor

learning in children with ADHD is rarely researched. The

disruptive behavior of children with ADHD causes significant

stress for the parents and teachers of these children

(Anastapoulos, Guevremont, Shelton, & DuPaul, 1992). As a

result, most research concentrates on causes and treatment

of this behavior. Research into the motor skills learning

may open a new window on intervention with these children,

both academically and socially (Conners & Delamater, 1980).

It may also provide further evidence of the processes used








58

by children with ADHD when they learn any novel skill

(Leavell, Ackerson, & Fischer, 1995).















CHAPTER 2
CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD


The Impact of Right Hemisphere Dysfunction on ADHD


Research on the etiology of ADHD has focused on the

neurological basis for this disorder and on the possible

reasons for any brain dysfunction, as important differences

have been found in the neurology of children with ADHD

compared to control children (Barkley, 1990). Right

hemisphere abnormalities were found on CAT scans of nine of

fifteen children referred for behavioral and learning

problems, and all of these children met criteria for

attention deficit disorder (Voeller, 1986). These children

also had difficulties reading social cues and modulating the

cues they projected (Voeller, 1986). As a group, they were

withdrawn and isolated and did not respond well to

psychotherapy. Although the symptoms of these children are

similar in many ways to those of ADHD children, the

interpersonal problems of these children could not be

entirely attributed to attention deficits (Voeller, 1986).

59








60

Nevertheless, the finding that ADHD is closely correlated to

right hemisphere deficits is consistent with data concerning

symptoms of inattention and motor impersistence in adults

and children with right-sided brain injuries (Voeller &

Heilman, 1988a).

Consistent with other evidence of right hemisphere

dysfunction in children with ADHD, these children made

significantly more left-sided errors than normal controls on

a letter cancellation task (Voeller & Heilman, 1988a). The

authors carefully selected only subjects who met all DSM-III

criteria for attention deficit disorder and were not

children with a conduct disorder mislabeled as ADHD. The

children with ADHD also had subtle left-sided neurologic

signs and had problems sustaining voluntary movements, a

difficulty often seen in adults with right hemisphere injury

(Voeller & Heilman, 1988b).

Attentional functions such as focusing on a target and

then disengaging to refocus on the next target are believed

to reside in the right hemisphere (Voeller & Heilman,

1988a). Children with ADHD demonstrated deficits on tasks

requiring them to fixate on a stimulus, both with and

without distractions (Voeller & Heilman, 1988b). On a








61

covert visual orienting task, children with ADHD disengaged

significantly more quickly than normal control from invalid

cues in the left visual field, and more quickly than they

themselves disengaged from targets in the right visual field

(Carter et al., 1995). This suggested that children with

ADHD had difficulty in sustaining attention for any target

in the left visual field and provided supporting evidence

for an underlying right hemisphere deficit (Voeller &

Heilman, 1988a). Although factors other than neurologic

dysfunction influence the development of ADHD symptoms,

developmental abnormalities of, or injury to, the right

hemisphere and its attentional and motor control structures

seem to influence attentional deficits (Voeller & Heilman,

1988a; Carter et al., 1995).


Morphological Differences in Children with ADHD


Interhemispheric connections in ADHD children may

influence their ability to control of their behavior, but

the inconsistent results of morphology studies have

precluded any definite conclusions (Hynd et al., 1991;

Semrud-Clikeman et al., 1994). Morphometric analysis of the

genu, or most anterior portion of the corpus callosum,











indicated that it may be significantly smaller in children

with ADHD than in normal controls (Hynd et al., 1991), but

later studies using more sophisticated imaging equipment

contradicted this finding (Semrud-Clikeman et al., 1994).

The genu was smaller in children with ADHD who were

unresponsive to stimulant medication, but there were not

enough subjects for a statistical analysis (Semrud-Clikeman

et al., 1994). The genu contains fibers connecting the

prefrontal, orbitofrontal, and premotor cortices, and

although measures of callosal size may not accurately

reflect the number of interhemispheric fibers, a smaller

genu may be responsible for disruption in motor control and

behavioral inhibition systems (Hynd et al., 1991).

Posterior sections of the corpus callosum, the splenium and

the area just anterior to it, were also found to be smaller

in children with ADHD (Hynd et al., 1991; Semrud-Clikeman et

al., 1994). This may explain the difficulties ADHD children

have in attending to sensory information (Semrud-Clikeman et

al., 1994), although other research has suggested that the

sensory areas in these children may be overactive (Lou et

al, 1989), rather than the reverse.








63

The caudate nucleus has been called the "head ganglion

of the habit system, a designation that underlines its

importance in motor skill learning (Saint-Cyr, Taylor,

Trepanier, & Lang, 1992). This large subcortical nucleus

also influences behavioral responses to stimuli (Rolls &

Johnstone, 1992), suggesting that it is integrated into

attention systems (Lou, Henrikson, & Bruhn, 1990). Children

with ADHD have been found to have a smaller left than right

caudate nucleus, the reverse of what is found in normal

controls, but had no significant differences in overall

brain size (Hynd et al., 1993). The lack of differences in

overall brain size indicated regional differences in

development, rather than variations in the brain as a whole

(Hynd et al., 1990). Abnormal asymmetries may result in a

bias for right-sided control mechanisms and the disruption

of subcortical control of attention, as neurotransmitter

systems favor the non-dominant hemisphere. As dominant

hemisphere controls on the motor systems are disrupted,

overactivity may result. Behavioral disinhibition in

children with ADHD may also be influenced by subcortical

neurotransmitter systems and their relationship to the

frontal lobes, especially the prefrontal cortex. Abnormal








64

caudate asymmetries may negatively impact the activation of

frontal lobe functions that rely on subcortical modulation,

with lowered behavioral control similar to that seen in

adult cases of frontal dysfunction (Hynd et al., 1993).


Cerebral Blood Flow in Children with ADHD


Studies of regional cerebral blood flow, from which a

structure's functional involvement in behavior can be

inferred, provided further evidence of subcortical

involvement in ADHD (Chugani, Phelps, & Mazziotta, 1987).

Children with ADHD had significantly lower levels of blood

flow in both the caudate nucleus (Lou et al., 1989) and

posterior periventricular areas (Lou, Henrikson, & Bruhn,

1990). Lesions in these subcortical areas caused attention

problems and motor hyperactivity in animal studies (Lou et

al., 1989). Interconnections between these structures and

the frontal lobes (Hynd et al., 1993) provided evidence that

deficiencies in subcortical metabolism are responsible for

poorly modulated activity in the prefrontal cortex (Lou,

Henrikson, and Bruhn, 1990). As noted above, these areas of

cortex are responsible for behavioral inhibition and have










also been implicated in the control of attention (Luria,

1973).

Cerebral blood flow changes in the sensory and

sensorimotor regions of cortex have been demonstrated in

children with ADHD (Lou et al., 1989). Increases in blood

flow to the occipital lobe have been linked to an inability

to screen out irrelevant visual information (Lou,

Henrickson, & Bruhn, 1990). As other sensory cortices

demonstrated similar changes, it appears that there is a

lack of inhibitory control of sensory input, perhaps a

result of disrupted striatal connections to the thalamus

(Lou, Henrickson, & Bruhn, 1990). Consistent with the

hypothesis of deficient self-regulation (Douglas, 1983),

this may create difficulties for children with ADHD in

screening sensory input (Lou, Henrikson, & Bruhn, 1990).


Brain Metabolism in Children with ADHD


Glucose metabolism is the main source of energy for the

brain, so measurement of this process is another indicator

of the functional activity of brain structures (Chugani,

Phelps, & Mazziotta, 1987). During performance of a simple

attention task, the left prefrontal area was significantly











less active in adolescents with ADHD than in normal

controls, (Zametkin et al., 1993). Metabolism in this area

had a significant negative correlation with the severity of

ADHD symptoms (Zametkin et al., 1993). Adolescents with

ADHD had significantly higher metabolic rates in a portion

of the left parietal lobe, a finding that may be consistent

with their sensory processing deficits (Lou, Henrickson, &

Bruhn, 1990). Although these findings contradicted evidence

of right frontal lobe involvement in ADHD, they

differentiated between adolescents with ADHD and controls in

the absence of overall differences in brain metabolism

(Zametkin et al., 1993).

Adults with a childhood history of ADHD did have a

lower rate of total brain metabolism than normal controls,

perhaps as a result of the disorder's effects on maturation

(Zametkin et al., 1990). Adults with ADHD also had lower

metabolic rates in the somatosensory cortex (Zametkin et

al., 1990). Consistent with the findings in adolescents,

the greatest reduction in metabolic activity was found in

the left prefrontal regions of the adults with ADHD

(Zametkin et al., 1990).








67

The prefrontal regions of adults and children with ADHD

may deactivate when challenged with a simple attention task

(Amen, Paldi, & Thisted, 1993). Children with ADHD who

failed to demonstrate reduced prefrontal activity during an

intellectual task already had a lower resting metabolic rate

in that area. Prefrontal cortex controls attention,

concentration, problem-solving abilities and judgment (Amen,

Paldi, Thisted, 1993). Planning and execution of motor

activities are also functions of this part of the brain

(Zametkin et al., 1990). It is possible that the motor

incoordination seen in ADHD children is a result of abnormal

functioning in the prefrontal areas and in the subcortical

structures connected to it.


Issues of Subject Selection


The outcome of morphological and physiological studies

may be influenced by the inclusion of children with ADHD and

a comorbid diagnosis, especially a learning disability.

Although the right frontal cortices of both ADHD and

dyslexic children were significantly smaller than in normal

controls, dyslexic children differed from ADHD children in

the size of other brain regions (Hynd et al., 1990). The








68

length of the insular region was shorter bilaterally and the

posterior segment of Wernicke's area (planum temporale),

both areas involved in language, were smaller in dyslexics

than in normal children. Compared to children with ADHD and

normal controls, dyslexic children had a reversed pattern

(L
was due to the smaller left planum (Hynd et al, 1990).

Subject selection may also influence the results of

regional cerebral blood flow and metabolic studies.

Zametkin et al. (1990) and Zametkin et al. (1993) did not

analyze the data from ADHD-LD and ADHD-only subjects

separately. In addition to the low striatal blood flow

characteristic of ADHD, subjects with ADHD and comorbid

neurological diagnoses had more extensive reductions in the

central regions of the brain (Lou et al, 1989). While there

are similarities in the neurobiology of ADHD and

developmental learning disabilities, there are also

important differences that may influence research results if

not controlled (Lou et al., 1989; Lou, Henrikson, & Bruhn,

1990).











Neuropsychological Testing of Children with ADHD


Although frontal lobe dysfunction has long been

implicated in ADHD, formal testing of frontal lobe functions

produced inconsistent results (Barkley & Grodzinsky, 1994).

Some studies have found few differences between children

with ADHD and normal controls on tests of frontal lobe

functioning (Loge, Staton & Beatty, 1990), but this study

analyzed distractibility and vigilance tasks separately from

other tests of frontal lobe functioning. When those tests

were analyzed, it was concluded that ADHD children had

difficulty in directing and sustaining attention, a function

localized to the right parietal lobe (Posner, 1992).

However, subjects in this study may have had developmental

learning disabilities and parietal dysfunction unrelated to

their attention problems (Grodzinsky & Diamond, 1992).

Other authors indicated that symptoms of ADHD resemble

frontal lobe deficits, with subcortical involvement (Barkley

& Grodzinsky, 1994). Vigilance tests like the CPT are more

often used to measure frontal lobe function, rather than

parietal lobe function (Loge, Staton, & Beatty, 1990), in

children with ADHD, as inhibition and voluntary attention










are believed to be frontal lobe functions (Luria, 1973).

Impulsivity leads to errors of commission, while

inattentiveness leads to errors of omission (Grodzinsky &

Diamond, 1992). The deficient performances of children with

ADHD on vigilance tasks make these tests effective in

measuring the intensity of ADHD symptoms (Barkley &

Grodzinsky, 1994). Children with ADHD made errors of

commission significantly more often than children with

learning disabilities or normal controls and this measure

separated the performance of children with ADHD from normal

children (Barkley, & Grodzinsky, 1994; Seidman et al.,

1994). Adolescents with ADHD continued to have difficulty

with vigilance tasks, but were not more distractible than

normal controls, suggesting maturational effects (Fischer,

Barkley, Edelbrock, & Smallish, 1990).

Aside from the results of vigilance tasks, which were

fairly consistent across studies, tests of frontal lobe

functioning have produced mixed results in children with

ADHD. The Stroop Interference Task, which requires subjects

to name a stimulus while inhibiting a conflicting response,

differentiated children with ADHD from normal controls in

some studies (Grodzinsky & Diamond, 1992; Barkley,











Grodzinsky, & DuPaul, 1992), but in other studies the

performance difficulties of ADHD were not significant

(Barkley & Grodzinsky, 1994). The Wisconsin Card Sorting

Test (WCST), a measure of problem solving ability, also does

not always reliably discriminate ADHD children from normal

controls (Grodzinsky & Diamond, 1992; Barkley & Grodzinsky,

1994), although ADHD children have been found to make more

perseverative and nonperseverative errors than normal

controls (Shue & Douglas, 1992; Seidman, et al., 1994).

Normal children completed the first category faster than

children with ADHD (Grodzinsky & Diamond, 1992), and

children with ADHD completed fewer total categories (Shue &

Douglas, 1992). A review of studies with significant

results on the WCST indicated that they did not specifically

exclude children with learning disabilities (Grodzinsky &

Diamond, 1992), introducing a possible confound. Another

hypothesis is that these effects were age-related, with

younger children with ADHD performing significantly worse

than normal controls, while older children with ADHD

performed more normally (Fischer, Barkley, Edelbrock, &

Smallish, 1990). This hypothesis has not been confirmed and








72

the WCST has proved disappointing as a test of ADHD, even in

younger children (Barkley & Grodzinsky, 1994).

Children with ADHD had difficulty alternating responses

during sequencing tasks (Shue & Douglas, 1992), but even

when the difference was nonsignificant, normal children were

somewhat faster than children with ADHD (Grodzinsky &

Diamond, 1992). Tests of planning and organization also

produced mixed results (Grodzinsky & Diamond, 1992; Barkley

& Grodzinsky, 1994). Motor control difficulties in children

with ADHD are similar to deficits found in adults with

frontal lobe dysfunction (Shue & Douglas, 1992). Children

with ADHD had deficits inhibiting motor responses, made

impulsive errors in responding, and were echopraxic (Shue &

Douglas, 1992). Children with ADHD also had significantly

greater difficulty inhibiting memory-guided eye movements

compared to normal controls (Ross et al., 1994). These

results are consistent with what would be expected, given

abnormal asymmetry of the caudate nucleus and the subsequent

disruption of connections with the prefrontal lobes (Hynd et

al., 1993).

Verbal fluency tests, especially those which require

generation of words to a target letter, were a useful










measure of frontal lobe functioning in children with ADHD

(Koziol & Stout, 1992). Significantly fewer words were

generated by groups of ADHD children compared to normal

controls (Koziol & Stout, 1992; Barkley & Grodzinsky, 1994).

Adolescents with ADHD did not show deficits on these tasks

(Fischer, Barkley, Edelbrock, & Smallish, 1990). The

deficits in children were attributed to deficits in self-

regulation (Koziol & Stout, 1992; Douglas, 1983), and an

inability to focus and sustain attention. These deficits

may be attributable to frontal lobe dysfunction, although

research on this as a definitive test of ADHD is not yet

conclusive (Barkley & Grodzinsky, 1994).

It is difficult to draw any solid conclusions about

frontal lobe functions in ADHD children at this time, as

most of the tests used were designed for adults and may not

translate well to children (Barkley, Grodzinsky, & DuPaul,

1992). In addition, frontal lobe measures may miss subtle

defects in functioning resulting from developmental factors,

as they were designed to measure the results of more severe

brain insults. Vigilance tasks, which were designed

specifically to measure the ADHD symptoms of attention and

impulsivity, were most effective in distinguishing ADHD











children from normal controls (Barkley & Grodzinsky, 1994).

A family history of ADHD may negatively impact the

performance of a child with ADHD on neuropsychological

tests, but comorbid diagnoses did not appear to have a

significant effect (Seidman et al., 1994).


Neuroanatomy of Attention


The primary factors in defining attention are the

ability to focus on environmental stimuli, sustain

attention, encode information, respond to stimuli, and shift

attention to new targets (Mirsky et al., 1991). These

factors are similar to those proposed by other

neuropsychological models of attention (Cohen, 1993). Cohen

(1993) noted that a weakness of this model is that it is

based on responses to traditional neuropsychological

measures and may not measure the impact of differences in

motivation and behavior. An alternate model of attention

includes sensory attention, attentional capacity, selection

and control of responses to stimulation, and sustained

attention (Cohen, 1993). Children with ADHD were seen as

having impairments in most areas of attention, with

important exceptions. Their ability to focus on











environmental stimulation, filter those sensations, and

initiate a response appeared to be within normal limits.

This provided support for the importance of self-regulatory

deficits in these children (Douglas, 1983). Children with

ADHD also appeared to have a normal attentional capacity, as

measured by overall intellectual ability (Cohen, 1993).

Their ability to encode information, a function subserved by

the hippocampus and amygdala, was found to be normal (Ott &

Lyman, 1993).

The mesencephalic reticular formation is involved in

the arousal states necessary for attention (Watson,

Valenstein, & Heilman, 1981). Arousal can be defined as the

physiological readiness to attend to incoming stimulation

(Cohen, 1993). The reticular formation is believed to

modulate the function of the nucleus reticularis, which

influences the screening of sensory information by the

thalamus, and results in selective activation of cortical

areas (Watson, Valenstein, & Heilman, 1981). The ability to

sustain attention is mediated by the activation of these

structures, as they control the flow of sensory information

to higher cortical structures (Mirsky et al., 1991).

Cortical areas that play a role in the "higher" forms of











attention such as response selection and shifting attention

are activated by these subcortical structures.

Voeller (1991) discussed the relationship of

impairments in sensory attention, controlled by sensory

association areas and the subcortical structures that

project to these areas, to the symptoms of ADHD (Voeller,

1991). These systems may control the ability to focus

attention on external events (Mirsky, 1991). Automatic

shifts in sensory attention were impaired in children with

ADHD (Cohen, 1993), suggesting difficulty in controlling

responses to environmental stimuli (Douglas, 1983). As

noted earlier, children with ADHD have been described as

having left-sided neglect similar to adults with right

hemisphere dysfunction (Voeller & Heilman, 1988a). This

represented a deficit in directed sensory attention, which

may be a function of the posterior parietal attention system

(Posner, 1992). Processing of incoming sensory information

and automatic shifts of attention appear to be regulated by

the parietal lobe and associated thalamic nuclei (Posner,

1992).

Weinberg and Harper (1993) examined the literature

regarding the role of the right parietal lobe in sensory











attention and concluded that underarousal in this area

causes disinhibition of irrelevant input. However, this

conclusion was based on disorders, such as depression, that

cause secondary problems in vigilance and they did not

directly investigate vigilance in ADHD (Weinberg & Harper,

1993). Competing explanations for sustained attention

deficits in ADHD, such as the difficulties in self-

regulation proposed by Douglas (1983), suggest that it is

not only the posterior attention system that is involved in

ADHD. Other impairments, such as impaired active shifting

of attention, are controlled by different neural structures,

discussed below (Voeller & Heilman, 1988a).

The brain region most involved with attention and

cognitive regulation appears to be the prefrontal cortex

(Posner, 1992), thought to be responsible for active

shifting of attention (Mirsky et al., 1991). Planning and

organization of behavioral responses to environmental

stimulation is also an important component of frontal lobe

activity (Cohen, 1993). These skills have been found to be

deficient in children with ADHD (Shue & Douglas, 1992).

Unmedicated children with ADHD had normal recognition for

the spatial location of pictures presented to them in a











structured format (Ott & Lyman, 1993). Their free recall of

the pictures, which required self-generated organization of

information for output, was significantly worse than normal

controls (Ott & Lyman, 1993). Impulsivity and

distractibility are considered to be modulated by

frontal/executive functions (Voeller, 1991). ADHD children

have been found to have difficulties inhibiting responses to

one stimulus and then reengaging attention on second

stimulus, also considered to be a frontal/executive function

(Schachar, Tannock, & Logan, 1993).

Explanation for the inability of children with ADHD to

shift attention is probably not limited to frontal/executive

dysfunction (Yeates & Bornstein, 1994). Research has

suggested that a loop involving the caudate nucleus,

thalamus, and cortical areas is involved in ADHD (Yeates &

Bornstein, 1994). The frontal lobe-caudate nucleus

interconnection appeared to be important for regulation of

directed attention (Mirsky, et al., 1991) and modulation of

responses (Cohen, 1993). Dysfunction in frontal-caudate

systems may be involved in deficits of response inhibition

and motor overactivity (Voeller, 1991). When subjects are

asked to perform tasks with a substantial attentional











component, regional cerebral blood flow in the frontal and

subcortical regions involved in attention increases

significantly (Haxby, Grady, Ungerlieder, & Horwitz, 1991)

These authors also reported increased blood flow in the

areas of cortex responsible for sensory processing (e.g.,

the occipital lobes and-somatosensory cortex).

Overall, it appeared that children with ADHD have

cortical dysfunction in several areas, especially in the

right frontal and parietal cortices, and subcortical

dysfunction in areas responsible for modulating sensory

input, the caudate nucleus and thalamus. While the

dysfunction may be subtle and not influence the results of

formal neuropsychological testing (Barkley & Grodzinsky,

1994), it can and most likely does have an impact on daily

activities.














CHAPTER 3
THE PURSUIT ROTOR AND MOTOR SKILL ACQUISITION


The Pursuit Rotor


Description


The rotary pursuit task is a commonly used method of

investigating motor skill learning (Eysenck & Frith, 1977).

It is a simple device, consisting of a lighted target on a

rotating turntable. Subjects are expected to keep a light-

sensitive stylus in contact with the target and the total

time of contact is electronically recorded. Subjects

typically developed the motor coordination skills necessary

to increase time on target through repeated trials (Eysenck

& Frith, 1977). Distractors affected the performance of

normal subjects on the pursuit rotor, with greater amounts

of distraction causing greater difficulties in performance

(Eysenck & Thompson, 1966). Nonetheless, after a rest

period, normal subjects demonstrated normal learning for the

task. The hypothesis developed that most learning on the








81

pursuit task occurs during rest periods when the information

is consolidated (Eysenck & Thompson, 1966).

Type of practice (massed vs. distributed) significantly

influenced pursuit rotor performance (Eysenck & Frith,

1977). Massed practice refers to the measurement of

learning during continuous trials, while distributed

practice involves sets of trials with rest periods in

between trials. Distributed practice has been found to be

the most effective method of learning on this task, perhaps

as a result of consolidation processes (Eysenck & Thompson,

1966). In other words, subjects appeared to develop

programs for successfully completing the task while resting,

rather than through correction of errors during the task

(Eysenck & Frith, 1977).


Performance of Children on the Pursuit Rotor


Children demonstrated the ability to perform the rotary

pursuit task and to learn over repeated trials (Davol,

Hastings, & Klein, 1965; Dunham, Allan, & Winter, 1985).

The performance of children between kindergarten and third

grade was measured at two preset speeds (33 & 45 rpm). Age

had a significant effect on the performance and the slower










speed appeared necessary for younger children. Older

children showed greater improvement with practice, but never

achieved adult levels of performance (Davol, Hastings, &

Klein, 1965). Socioeconomic status may affect motor

learning at younger ages, but this difference disappears

among older children (Davoll & Breakell, 1968). Davoll,

Hastings, and Klein (1965) noted that young children may

find the rotary pursuit task fatiguing and repetitive. In

order to increase the motivation of these children,

reinforcement should be applied.

Children defined as "clumsy," who had significant motor

incoordination but were normal on neurological examination,

performed worse than normal controls on the rotary pursuit

task (Lord & Hulme, 1988). However, they did show a steady

increase in their ability to stay on target across trials,

suggesting a transfer from visual feedback control of motor

systems to the development of motor programs (Heindel,

Butters, & Salmon, 1988). Impairment in initial encoding,

through processing of visual feedback, may be a more

important factor in clumsiness than the inability of these

children to develop effective motor programs (Lord & Hulme,

1988). Nonetheless, these children did not approach normal









83

performance even after several trials, suggesting deficient

programming of motor sequences.

Children who are mildly mentally retarded have

significantly more difficulty in motor learning than normal

controls (Simenson, 1973). Use of an audible feedback

signal for errors did not facilitate performance, but extra

practice trials did, suggesting that these children may

actually experience feedback as noxious (Simenson, 1973).

Later research contradicted this conclusion, as visual,

tactile, and auditory feedback were found to enhance motor

learning in both retarded and control children (Horgan,

1982). In fact, auditory feedback given when a subject was

on target helped retarded children attain normal levels of

performance. These results suggested that task conditions

affect motor learning in retarded children and that optimal

conditions result in normal levels of motor learning

(Horgan, 1982).

Heitman and Gilley (1989) investigated the performance

of mentally retarded adolescents using either blocks of

same-speed trials or a random distribution of speeds. There

was no significant effect for the blocked condition,

suggesting that inattention to assigned tasks plays a role











in poor rotary pursuit performance by mentally retarded

children (Heitman & Gilley, 1989). The learning curves of

these children were correlated with on-task behaviors

(Heitman & Gilley, 1989), and feedback appeared to improve

attention to a task, consistent with earlier results

(Horgan, 1982). Retarded children appeared to gain from

consolidation, as second-day performance was improved over

the first day learning (Heitman & Gilley, 1989). This was

consistent with other evidence that skill retention in these

children is not significantly different from normal children

(Simenson, 1973).

No significant effect for either massed or distributed

practice was found in mildly mentally retarded children

(Rider & Abdulahad, 1991). Improved performance was again

found on the second day of testing, consistent with

consolidation and skill retention, but attention problems

had a negative impact on performance (Rider & Abdulahad,

1991). There seemed to be an optimal number of trials for

the acquisition of motor skills in autistic children, as the

use of more than 10 trials resulted in significant off-task

behavior (Wek & Husak, 1989). Within these limitations, it








85

appeared that autistic children are also capable of learning

a novel motor skill (Wek & Husak, 1989).

The impact of attention difficulties on rotary pursuit

performance may be relevant to children with ADHD.

Inattention and the inability to form motor programs may

both play a role in their motor learning. To determine the

effect of motor programming deficits, the motivation of

children with ADHD should be controlled to prevent the

additional effects of inattention and impulsivity on

results.


Sex Differences on the Pursuit Rotor


Research findings regarding sex differences in pursuit

rotor performance have been inconsistent. No sex

differences were found in the performance of children in

kindergarten through third grade (Davol, Hastings, & Klein,

1965), a finding replicated with a group that also contained

children in the fourth and fifth grades (Davol & Breakell,

1968). Another study indicated that the performance of boys

is significantly better than that of girls, but used a

subject pool that included children with mild mental

retardation (Simenson, 1973). Under massed practice











conditions, there were no significant differences between

first-grade boys and girls at lower speeds (15 & 30 rpm),

but boys demonstrated better learning than girls at the

highest speed (45 rpm; Horn, 1975). Consistent with this

finding, elementary school girls had lower ceiling speeds

than boys (Dunham, Allan, & Winter, 1985). Although

children were not compared in each grade, the major

differences appeared to exist in kindergarten, and sixth

grades, while girls in grades two through five appeared to

more closely match the performance of boys (Dunham, Allan, &

Winter, 1985). When speed of rotation was held constant,

the performances of boys and girls were not significantly

different (Ruffer, 1984). In addition, the performance of

college-age women was not significantly different from men

in distributed practice conditions with rest periods of 10

seconds or longer (McBride & Payne, 1980). No research to

date has compared the performance of boys and girls when

speeds were set individually, the method used in the current

study.











Motor Skill Acauisition in Children with ADHD


As noted above, little research has been done on motor

skill acquisition in children with ADHD. On a visual-motor

tracking task requiring the subject to use a control stick

to keep a lighted dot centered on a moving target, children

with ADHD performed significantly worse than normal controls

(Conners & Delamater, 1980). Although some practice effects

were recorded, the children were tested under several

different conditions and the task did not allow for

continuous practice of any one condition, making it

difficult to make any judgements about motor skill

acquisition (Conners & Delamater, 1980). Examination of the

effect of Ritalin on baseball skills indicated that it

improved the attention and on-task behaviors during games,

but had little effect on improving baseball skills (Pelham

et al., 1990). However, the children had relatively little

chance to practice their skills and baseball skills often

involve multiple coordinated movements and cognitions,

making it difficult to determine all variables involved in

their acquisition (Pelham et al., 1990).








88

On the rotary pursuit task, children with ADHD and with

ADD/WO demonstrated no differences from normal controls in

motor skill learning or retention (Leavell, Ackerson, &

Fischer, 1995). The times on target for children with ADHD

each of five 20-second trials and after a 30-minute delay

were significantly worse than normal controls (Leavell,

Ackerson, & Fischer, 1995), a finding consistent with

research on "clumsy" children (Lord & Hulme, 1988). First-

trial scores for children with ADHD were significantly

correlated with neuropsychological measures of visual-motor

integration, suggesting that deficits in these skills may be

responsible for incoordination in children with ADHD

(Leavell, Ackerson, & Fischer, 1995). However, it is

difficult to make conclusions about motor skill learning

from these results, as five trials may be insufficient for

even normal children to acquire the necessary motor

programs. In addition, the children were drawn from a wide

age range (6-16) and a relatively slow, uniform speed (15

rpm) was used. Use of this speed may have made the task too

easy for some of the children, especially the older ones.

Finally, the effect of motivation was not controlled.











Neuroanatomy of Motor Systems


Motor systems involve a number of neurological

substrates, both cortical and subcortical. Parietal lobe

lesions lead to difficulties in copying meaningless arm

movements (Kolb & Milner, 1981), while frontal lobe lesions

result in deficits in both facial and arm movement

imitation. The supplementary motor cortex is thought of as

the area responsible for programming complex movements

(Alexander, DeLong, & Strick, 1986), but the lesions in Kolb

and Milner (1981) varied widely, making precise localization

impossible. Nevertheless, it appeared that the frontal

lobes were responsible for the programming of movement

sequences. Movement programming may be represented

bilaterally in the frontal lobes (Kolb & Milner, 1981) and a

lack of coordination between hemispheres may lead to

increased severity of impairment (Milner & Kolb, 1985).

Patients with callosotomies (cutting of the corpus callosum)

performed significantly worse on a facial movement task than

did frontal lobe patients. While these effects may be

explained by memory difficulties, there were no significant

errors on single facial movements, suggesting that it is the











sequencing of movements that is affected (Milner & Kolb,

1985).

Frontal lobe lesions affected performance of sequential

tapping tasks (Leonard, Milner, & Jones, 1988). When the

coordination of both hands was required, subjects with

frontal lobe lesions had the greatest difficulty relative to

normal controls and subjects with temporal lobe lesions.

Subjects with left frontal lesions performed worse than

those with right frontal lesions. Subjects with temporal

lobe lesions demonstrated difficulties similar to frontal

lobe subjects on a sequenced tapping task using only one

hand. This result may have been influenced by task demands,

as speed rather than coordination was important in the one-

handed tapping task, and there is a general slowing of motor

speed in most cases of brain injury (Leonard, Milner, &

Jones, 1988).

The importance of right frontal lobe involvement in

movement has been demonstrated. Subjects with large right

frontal lesions have significant difficulty in recalling the

distance of arm movements (Leonard & Milner, 1991a). This

deficit was seen without regard to interference tasks, an

indicator that the right frontal lobe is involved in the











processing of this information. It is the maintenance,

rather than the encoding, of information about the distance

of arm movements that appeared to be a right frontal lobe

function, as immediate recall was not impaired in these

subjects (Leonard & Milner, 1991b). The right frontal lobe

subjects with large lesions were equally impaired with

either hand, and were more impaired than subjects with

either left frontal lesions or small right frontal lesions.

These findings indicated that localization and size are

important, with large right-sided frontal lesions disrupting

motor systems that maintain kinesthetic distance information

(Leonard & Milner, 1991a).

The basal ganglia caudatee nucleus, putamen, and

globus pallidus) play a role in motor skill learning (Saint-

Cyr, Taylor, Trepanier, & Lang, 1992). Subjects with

Huntington's disease, a movement disorder arising from basal

ganglia dysfunction, performed significantly worse than

groups of subjects with amnesia, Alzheimer's disease, and

normal controls on the pursuit rotor task (Heindel, Butters,

& Salmon, 1988). Neither global amnesia nor the early

stages of Alzheimer's disease impaired the performance of

these patients on a mirror-tracing task, suggesting that the








92

mechanisms for motor skills learning are separate from other

memory systems (Gabrieli, Corkin, Mickel, & Growdon, 1993).

Motor learning may also be separable from spatial location

ability. Spatial location was deficient in the amnesic

patient, H.M. (Smith, 1988), who demonstrated relatively

intact motor learning (Gabrieli, Corkin, Mickel, & Growden,

1993). The finding that subjects with Huntington's disease

were not as impaired as those with Alzheimer's on a verbal

recall task supported the dissociation between motor and

verbal learning (Heindel, Butters, & Salmon, 1988). The

basal ganglia are part of a loop involving the motor cortex

and thalamic nuclei that control motor behavior (Penny &

Young, 1986). Damage to the basal ganglia causes an

inability to direct and control movements. Other motor

control areas, such as the cerebellum, did not appear to

influence motor skill learning (Gabrieli, Corkin, Mickel, &

Growden, 1993).




Full Text
31
the risk of suspension, expulsion, dropping out of school,
and the development of adolescent delinquency (Barkley,
Fischer, Edelbrock, & Smallish, 1989; Hinshaw, 1992).
Academic remediation or behavior modification alone may
ameliorate disruptive behavior (McGee and Share, 1988), but
simultaneous treatment of academic and behavior problems has
been found to be more effective for children with ADHD/LD
(Hinshaw, 1992).
Social Relationships of Children with ADHD
Interpersonal relationships, whether with adults or
other children, have been found to be problematic for
children with ADHD (Szatmari, Offord, & Boyle, 1989b) and
rejection by peers is common (Barkley, 1990). In
interactions with adults, children with ADHD had significant
rates of noncompliance when asked to complete a task, and
they often did not finish assigned tasks (Alessandri, 1992).
In return, teachers disciplined children with ADHD more
frequently than they disciplined their non-ADHD counterparts
(Alessandri, 1992) .
Preschoolers with ADHD were shown to have patterns of
social interaction and play that differed significantly from


10
ADHD With and Without Hyperactivity
Comparison Studies of Children
with ADD/H and ADD/WO
Groups of children with ADD, with and without
hyperactivity, differed significantly in several respects
(Lahey et al., 1987) Children with ADD/H were more
impulsive, younger at the time of clinic referral, and had
significantly higher rates of overt conduct problems than
children with ADD/WO. Children with ADD/H were more likely
to be placed in a classroom for children with severe
behavior problems (Barkley, DuPaul, & McMurray, 1990) Both
groups of children experience social isolation, but children
with ADD/H have been found to experience rejection by peers,
while children with ADD/WO are withdrawn (Cantwell & Baker,
1992). ADD/H children also had less self-control and
significantly higher ratings of both internalizing and
externalizing behaviors on the CBCL than their ADD/WO
counterparts (Barkley, DuPaul, & McMurray, 1990).
The symptoms of children with ADD/H were often
considered more disruptive by teachers and parents,
resulting in earlier referral to clinics (Lahey et al.,


(7) has difficulty sustaining attention in tasks or
play activities
5
(8) often shifts from one uncompleted activity to
another
{9) has difficulty playing quietly
(10) often talks excessively
(11) often interrupts or intrudes on others, e.g.,
butts into other children's games
(12) often does not seem to listen to what is being
said to him or her
(13) often loses things necessary for tasks or
activities at school or at home (e.g., toys, pencils,
books, assignments)
(14) often engages in physically dangerous activities
without considering possible consequences (not for the
purpose of thrill-seeking), e.g., runs into street
without looking
B. Onset before the age of seven
C. Does not meet the criteria for a Pervasive
Developmental Disorder
Criteria for the severity of Attention-Deficit
Hyperactivity Disorder:
Mild: Few, if any symptoms in excess of those required
to make the diagnosis and only minimal or no impairment
in school and social functioning.
Moderate: Symptoms or functional impairment
intermediate between "mild" and "severe."
Severe: Many symptoms in excess of those required to
make the diagnosis and significant and pervasive


125
TABLE 3
NEUROPSYCHOLOGICAL MEASURES
ADHD CONTROL
GROUP GROUP
MEAN (SD)
MEAN (SD)
INTERPOLATED FSIQ 104.61 (13.42)
GROOVED PEGBOARD (seconds)
Dominant hand 32.45 (7.95)
Non-dominant hand 37.77 (11.03)
JUDGEMENT OF LINE ORIENTATION
(# correct) 17.35 (5.90)
110.45 (16.39)
30.00 (7.28)
32.58 (7.34)1
19.18 (5.03)
CONTINUOUS PERFORMANCE TEST: CANCELLATION
Hit percentage
Omission errors
Commission errors
Reaction time (ms)
90.97 (12.94)
1.77 (2.60)
10.90 (15.51)
590.16 (98.44)
91.06 (18.06)
1.79 (3.61)
3.82 (3.71)1
644.24 (115.41)1
CONTINUOUS PERFORMANCE TEST: CONDITIONAL CANCELLATION
Hit percentage
Omission errors
Commission errors
Reaction time (ms)
91.61 (13.25)
1.29 (1.88)
10.92 (19.43)
508.16 (103.66)
94.70 (5.72)
.88 (1.02)
3.61 (5.86)1
528.12 (110.77)
1
P < .05


40
Guevremont, Shelton, & DuPaul, 1992), while a positive
maternal style may avoid this outcome (Barkley, Fischer,
Edelbrock, & Smallish, 1991). As the interactions between
ADHD children and their parents are likely to remain stable
over time, early intervention is necessary to reduce or
avoid the development of oppositional symptoms (Barkley,
Fischer, Edelbrock, & Smallish, 1991).
Heritability of ADHD
Research has indicated that genetic factors make a
significant contribution to ADHD (Biederman et al., 1990).
Relatives of ADHD children were more likely to be diagnosed
with ADHD than are relatives of either normal or psychiatric
controls (Biederman et al., 1990). Antisocial personality
and mood disorders were also much more common among
relatives of ADHD children than in the control groups.
Consistent with the usual pattern of ADHD, male relatives
were given a diagnosis of ADHD more often than female
relatives, although the increased risk for ADHD compared to
controls occurred without regard to the sex of the relative.
Forty-four percent of the fathers and 19% of the mothers of
ADHD children met diagnostic criteria for ADHD,


89
Neuroanatomy of Motor Systems
Motor systems involve a number of neurological
substrates, both cortical and subcortical. Parietal lobe
lesions lead to difficulties in copying meaningless arm
movements {Kolb & Milner, 1981), while frontal lobe lesions
result in deficits in both facial and arm movement
imitation. The supplementary motor cortex is thought of as
the area responsible for programming complex movements
(Alexander, DeLong, &. Strick, 1986), but the lesions in Kolb
and Milner (1981) varied widely, making precise localization
impossible. Nevertheless, it appeared that the frontal
lobes were responsible for the programming of movement
sequences. Movement programming may be represented
bilaterally in the frontal lobes {Kolb & Milner, 1981) and a
lack of coordination between hemispheres may lead to
increased severity of impairment (Milner & Kolb, 1985).
Patients with callosotomies (cutting of the corpus callosum)
performed significantly worse on a facial movement task than
did frontal lobe patients. While these effects may be
explained by memory difficulties, there were no significant
errors on single facial movements, suggesting that it is the


ACKNOWLEDGEMENTS
The hard work and support of my committee was helpful
to me throughout this project. Eileen Fennell's advice and
encouragement was invaluable as I conceptualized this study.
Russell Bauer's knowledge of pursuit rotor methodology and
statistics aided me in formulating the protocol. Ernest
Bordini and the parents of the North Florida Chapter of the
Children and Adults with ADD were very supportive of this
research. Bernard Maria was very helpful in allowing access
to patients of the Children's Medical Services neurology
clinic. Wes Corbett of P.K. Yonge Developmental Research
School is thanked for allowing access to his students. Jack
Saarella of the University Lutheran Church is thanked for
allowing me to contact the families in his church. Tara
Saia's hard work and persistence during data collection were
outstanding, as she was extremely conscientious throughout
her work as a graduate assistant. Amy Perwien and Ryan
Bernstein were also extremely helpful during data
collection. My family was very supportive throughout this
11


8
Hyperactivity
(a) often fidgets with hands or feet or squirms in seat
(b) often leaves seat in classroom or in other
situations in which remaining seated is expected
(c) often runs about or climbs excessively in
situations in which it is appropriate (in adolescents
or adults, may be limited to subjective feelings of
restlessness)
(d) often has difficulty playing or engaging in leisure
activities quietly
(e) is often "on the go" or often acts if "driven by a
motor"
(f) often talks excessively
Impulsivity
(g) often blurts out answers before questions have been
completed
(h) often has difficulty awaiting turn
(i) often interrupts or intrudes on others (e.g., butts
into conversations or games)
B. Some hyperactive-impulsive or inattentive symptoms
that caused impairment were present before age 7 years.
C. Some impairment from the symptoms is present in two
or more settings (e.g., at school [or work] and at
home).
D. There must be clear evidence of clinically
significant impairment in social, academic, or
occupational functioning,
E. The symptoms do not occur exclusively during the
course of a Pervasive Developmental Disorder,
Schizophrenia, or other Psychotic Disorder and are not


136
{Barkley & Grodzinsky, 1994) and supported the hypothesis
that deficits in response inhibition underlie the symptoms
of ADHD (Douglas, 1984) .
There were no significant differences between the ADHD
and control groups in dominant (right) hand fine motor
coordination, but the ADHD group demonstrated deficits in
fine motor coordination with the non-dominant (left) hand.
This did not support the hypothesis of overall deficits in
fine motor coordination in the ADHD group, but was similar
to earlier findings on this task (Barkley & Grodzinsky,
1994). There was no strong support for the hypothesis of
right-hemisphere dysfunction in children with ADHD (Voeller,
1991). Although results of the fine motor task suggested
right-hemisphere dysfunction, the lack of significant
differences between the ADHD and control groups on
visuospatial judgement, another right-hemisphere task,
prevented the drawing of any firm conclusions.
Errors of commission on the CPT conditional
cancellation task was the only neuropsychological measure
found to be a significant predictor of pursuit rotor
performance for the entire sample. This was consistent with
the hypothesis that impulsivity increases motor learning


71
Grodzinsky, & DuPaul, 1992), but in other studies the
performance difficulties of ADHD were not significant
(Barkley & Grodzinsky, 1994). The Wisconsin Card Sorting
Test (WCST), a measure of problem solving ability, also does
not always reliably discriminate ADHD children from normal
controls (Grodzinsky & Diamond, 1992; Barkley & Grodzinsky,
1994), although ADHD children have been found to make more
perseverative and nonperseverative errors than normal
controls (Shue & Douglas, 1992; Seidman, et al., 1994).
Normal children completed the first category faster than
children with ADHD (Grodzinsky & Diamond, 1992), and
children with ADHD completed fewer total categories (Shue &
Douglas, 1992). A review of studies with significant
results on the WCST indicated that they did not specifically
exclude children with learning disabilities (Grodzinsky &
Diamond, 1992), introducing a possible confound. Another
hypothesis is that these effects were age-related, with
younger children with ADHD performing significantly worse
than normal controls, while older children with ADHD
performed more normally (Fischer, Barkley, Edelbrock, &
Smallish, 1990). This hypothesis has not been confirmed and


148
10. What state do you live in?
11. What county in that state?
12. Ethnicity:
l=White (not Hispanic) 4=Asian or Pacific Islander
2=Af rican-American 5=American Indian
3=Hispanic 6=Other
13. Is your child currently placed in a class for Specific
Learning Disabilities (SLD)? YES NO
14. Has your child been diagnosed with a behavior disorder
(Oppositional-Defiant Disorder, Conduct Disorder)?
YES NO IF YES, please specify


27
(1988) downplayed organic or environmental common causes of
the disorders. Instead, they defined ADHD as a conduct
problem resulting from the learning disabled child's
inability to understand academic material (McGee & Share,
1988). Children with comorbid ADHD and reading disabilities
have been found to exhibit processing difficulties similar
to non-ADHD children with reading disabilities (Pennington,
Groisser, & Welsh, 1993). This finding appeared to support
the idea that academic difficulties are a causal factor in
some children diagnosed with both ADHD and LD.
Although children with learning disabilities have been
rated by their teachers as showing evidence of attention
problems (Barkley & Grodzinsky, 1994), the conclusion that
academic frustration is the primary causative factor in ADHD
is problematic. A dissociation has been found between the
symptoms of primary ADHD and those of reading disabilities
(Pennington, Groisser, & Welsh, 1993), and the link between
learning problems and ADHD often begins well before the
child enters school (Hinshaw, 1992). Inconsistent
definitions of both ADHD and learning disabilities have been
used in the research (Semrud-Clikeman et al., 1992) and
while learning disabilities may contribute to disruptive


UNIVERSITY OF FLORIDA
3 1262 08554 6215


134
learning stemming from dysfunction in a motor control loop
(Penney & Young, 1986) were expected for the children in the
ADHD/Reward condition compared to both control children in
both conditions. Small rewards were selected for these
children because research has suggested that children with
ADHD may over-anticipate large rewards, attending to the
reward rather than the task (Douglas, 1984; Carlson, Pelham,
Milich, & Dixon, 1992) Children in the ADHD/No Reward
condition were expected to have additional deficits as a
result of inattention and impulsivity. This study used the
pursuit rotor task to measure motor learning, as success on
the pursuit rotor requires the formation, over repeated
trials, of a motor program for keeping the stylus in contact
with the rotating target (Eysenck & Frith, 1977).
Significant differences in pursuit rotor performance
between children with ADHD and controls supported the
hypothesis that children with ADHD have deficits in forming
new motor programs. In spite of the opportunity to practice
the task and individually adjusted rotation speeds, the ADHD
group began the task with a significantly lower time on
target than the control group and failed to demonstrate any
improvement. In contrast to the ADHD group, the control


88
On the rotary pursuit task, children with ADHD and with
ADD/WO demonstrated no differences from normal controls in
motor skill learning or retention (Leavell, Ackerson, &
Fischer, 1995). The times on target for children with ADHD
each of five 20-second trials and after a 30-minute delay
were significantly worse than normal controls (Leavell,
Ackerson, & Fischer, 1995), a finding consistent with
research on "clumsy" children (Lord & Hulme, 1988). First-
trial scores for children with ADHD were significantly
correlated with neuropsychological measures of visual-motor
integration, suggesting that deficits in these skills may be
responsible for incoordination in children with ADHD
(Leavell, Ackerson, & Fischer, 1995). However, it is
difficult to make conclusions about motor skill learning
from these results, as five trials may be insufficient for
even normal children to acquire the necessary motor
programs- In addition, the children were drawn from a wide
age range (6-16) and a relatively slow, uniform speed (15
rpm) was used. Use of this speed may have made the task too
easy for some of the children, especially the older ones.
Finally, the effect of motivation was not controlled.


APPENDIX B
BEHAVIOR CHECKLIST
Please indicate if your child displays any of the following
behaviors to a degree that (1) is greater than other
children the same age, and (2) causes problems for you, your
child, or for others (e.g., teachers, other children):
YES NO
1. Fails to give close attention to details or
makes careless mistakes in schoolwork, work,
or other activities
YES NO
2. Has difficulty sustaining attention in tasks
or play activities
YES NO
3. Does not seem to listen when spoken to
directly
YES NO
4. Does not follow through on instructions and
fails to finish schoolwork, or chores (but
not because of oppositional behavior or
failure to understand instructions)
YES NO
5. Has difficulty organizing tasks or activities
YES NO
6. Avoids, dislikes, or is reluctant to engage
in tasks that require sustained mental effort
(such as schoolwork or homework)
YES NO
7. Loses things necessary for tasks or
activities (assignments, toys, pencils,
books)
YES NO
8. Easily distracted
YES NO
9. Often forgetful in daily activities
149


CHAPTER 4
SUMMARY AND RATIONALE
Summary
Children with attention deficit hyperactivity disorder
(ADHD) are characterized by impulsivity, inattention, and
motor hyperactivity. A debate about possible subtypes
existed for some time, and research provided support for two
categories of attention deficit disorder (ADD), ADD with
hyperactivity (ADD/H) and ADD without hyperactivity
(ADD/WO). Behavioral ratings of children with ADD/WO
indicated that these children were lethargic, with more
internalizing behaviors, while ADD/H children displayed
motor hyperactivity and aggressiveness. Few differences
between these groups were found on neuropsychological
measures, and behavioral assessment is the method that best
distinguishes between them. The DSM-IV took this research
into consideration and recognized three subtypes of ADHD; a
Primarily Inattentive type, a Primarily Hyperactive type,
and a Combined type. The children with ADHD-combined type
93


project. Without the love, understanding and patience of my
wife, Cheryl Colvin, this dissertation would not have been
completed.
in


165
Saint-Cyr, J.A., Taylor, A.E., Trepanier, L.L., & Lang, A.E.
(1992). The caudate nucleus: Head ganglion of the habit
system. In Vallar, G., Cappa, S.F., & Wallesch, C-W.
{Eds.) Neuropsychological Disorders Associated with
Subcortical Lesions, pp. 61-97. New York: Oxford
University Press.
Sattler, J.M. (1992). Assessment of Children: Third Edition-
Expande.&-.and Revised... San Diego: Jerome M. Sattler.
Schachar, R.J., Tannock, R., & Logan, G. (1993). Inhibitory
control, impulsiveness, and attention deficit
hyperactivity disorder. Clinical Psychology Review. H,
721-739.
Seidman, L.J., Biederman, J., Faraone, S.V., Milberger, S.,
Norman, D., Seiverd, K., Benedict, K., Guite, J., Mick,
E., Kiely, K. (1995). Effects of family history and
comorbidity on the neuropsychological performance of
children with ADHD: Preliminary findings. Journal of
the American Academy of child and Adolescent
14, 1015-1924.
Semrud-Clikeman, M., Biederman, J., Sprich-Buckminster S.,
Krichfer-Lehman, B., Faraone, S.V., & Norman, D.
(1992). Comorbidity between ADDH and learning
disability: A review and report in a clinically
referred sample. Journal of the American Academy of
Child and Adolescent Psychiatry. 11, 439-448.
Semrud-Clikeman, M., Filipek, P.A., Biederman, J.,
Steingard, R., Kennedy, D., Renshaw, P, Bekken, K.
(1994). Attention-deficit hyperactivity disorder:
Magnetic resonance imaging morphometric analysis of the
corpus callosum. Journal of the American Academy of
Child and Adolescent Psychiatry. H, 875-881.
Shaw, G.A. & Giambra, L. (1993). Task-unrelated thoughts of
college students diagnosed as hyperactive in childhood.
Deyfilopmantal Neurcpsycholcgy, 1, 17-30.


BIOGRAPHICAL SKETCH
I graduated high school in 1983 and received a National
Merit Scholarship from the Ohio State University. While at
Ohio State, I majored in Psychology and graduated in 1987
with a Bachelor of Arts degree. I was employed for two
years in Columbus, Ohio, as a Licensed Social Worker,
working with adolescents and their families. In order to
receive further training, I applied to graduate school and
was accepted into the clinical psychology program at the
University of Florida. Under the supervision of Dr. Sheila
Eyberg, I completed a restandardization of the Eyberg Child
Behavior Inventory and received my Master's degree in 1994.
I developed an interest in pediatric neuropsychology while
in graduate school and Dr. Fennell's supervision has helped
me gain more knowledge of this area. I completed an
internship in clinical neuropsychology at Columbia-
Presbyterian Medical Center in June, 1996, and will begin
post-doctoral training at the Columbus, Ohio, Children's
Hospital in September, 1996.
169


168
Yeates, K.O. & Bornstein, R.A. (1994). Attention deficit
disorder and neuropsychological functioning in children
with Tourettes syndrome. Neuropsychology, j£, 65-74.
Zametkin, A.J., Liebenauer, L.L.# Fitzgerald, G.A., King,
A.C., Minkunas, D.V., Herscovitch, P., Yamada, E.M., &
Cohen, R.M. (1993). Brain metabolism in teenagers with
attention deficit hyperactivity disorder. Archives of
General Psychiatry, 11, 333-340.
Zametkin, A.J., Nordahl, T.E., Gross, M., King, A.C.,
Semple,W.E., Rumsey, J., Hamburger, S., & Cohen, R.M.
(1990). Cerebral glucose metabolism in adults with
hyperactivity of childhood onset. The New England
Journal o Medicine, 123, 1361-1366.


105
while hit percentage and omission errors were used to
estimate inattention.
The Grooved Peaboard provided an estimate of fine motor
coordination. Each child was timed while placing grooved
pegs into 10 slotted holes, with the slots varied by angle
of rotation (Lezak, 1983). Time to completion was used as
the measure of performance. This test has been found to be
a valid measure of motor performance and normative data for
children has been established (Klonoff & Low, 1974).
Spatial abilities were assessed by the Judgement of
Line Orientation task (Benton, Hansher, Varney, & Spreen,
1983). Subjects were required to match the orientation of
line segments with those target lines, a task that requires
the cognitive ability to extend the segments and recognize
their angular placement. Number of correct matches was used
as the measure of performance. The results of this measure
were used to determine what effect, if any, that spatial
deficits had on motor skill acquisition.
Primary Dependent Measure
The primary dependent measure was the Photoelectric
Pursuit Rotor. The pursuit rotor apparatus consisted of a


42
heritability of learning disabilities, but the authors noted
that the finding of ADHD heritability appeared robust.
Concordance results did not appear to be a result of the
parents confusing the behavior of identical twins (Gillis,
Gilger, Pennington, & DeFries, 1992). However, despite
evidence of a genetic component to ADHD, no research to date
has found a direct link with a particular gene {Alessi,
Hottois, Sc Coates, 1993) The discovery of a rare thyroid
condition was correlated with ADHD and directly linked with
a particular gene suggested that this gene may be identified
in the future (Alessi, Hottois, & Coates, 1993).
Nonetheless, no evidence has supported the linkage of all
forms of ADHD to a thyroid condition.
Assessment and Treatment
A variety of techniques are used to evaluate attention
deficits in children. Parent and teacher reports are often
used in the assessment of the behavioral aspects of ADHD.
Two of the most commonly used behavior checklists are the
Conners rating scales (Goyette, Conners, & Ulrich, 1978) and
the Child Behavior Checklist (CBCL Achenbach, 1991).
These rating scales have both parent and teacher forms in


81
pursuit task occurs during rest periods when the information
is consolidated (Eysenck & Thompson, 1966) .
Type of practice (massed vs. distributed) significantly
influenced pursuit rotor performance (Eysenck & Frith,
1977). Massed practice refers to the measurement of
learning during continuous trials, while distributed
practice involves sets of trials with rest periods in
between trials. Distributed practice has been found to be
the most effective method of learning on this task, perhaps
as a result of consolidation processes (Eysenck & Thompson,
1966). In other words, subjects appeared to develop
programs for successfully completing the task while resting,
rather than through correction of errors during the task
(Eysenck & Frith, 1977).
Performance q£ Children on the.Pursuit Rotor
Children demonstrated the ability to perform the rotary
pursuit task and to learn over repeated trials (Davol,
Hastings, & Klein, 1965; Dunham, Allan, & Winter, 1985) .
The performance of children between kindergarten and third
grade was measured at two preset speeds (33 & 45 rpm). Age
had a significant effect on the performance and the slower


135
group demonstrated significant learning on the pursuit
rotor, but reached a plateau after the first three blocks.
This finding indicated that the use of fewer blocks in
future research would not significantly impact results and
may make the task less fatiguing for children. Controlling
attention and motivation- through the use of small rewards
had no significant effect on motor learning in either the
ADHD or control groups.
Secondary Analyses
Hypotheses concerning performance on neuropsychological
measures received mixed support. The ADHD group
demonstrated significant impulsivity, or errors of
commission, on both CPT tasks compared to children in the
control group. The ADHD group was not significantly
different from the control group on the percentage of
correctly identified targets or errors of omission, scores
that are believed to measure task-related attention (Corkum
& Siegel, 1993). These results were consistent with earlier
findings indicating that the errors of commission score is
the most effective neuropsychological measure in
discriminating between ADHD children and normal controls


162
Lezak, M.D. {1983). Neuropsychological assessment Third
Edition. New York: Oxford University Press.
Loge, D.V., Staton, D., & Beatty, W.W. (1990). Performance
of children with ADHD on test sensitive to frontal lobe
dysfunction. Journal of the American Academy of_Chlld
and Adolescent Psychiatry, 22, 540-545.
Lord, R. & Hulme, C. (1988). Patterns of rotary pursuit
performance in clumsy and normal children. Journal of
Child Psychology and Psychiatry, 21, 691-701.
Lou, H.C., Henrikson, L., & Bruhn, P. (1990). Focal cerebral
dysfunction in developmental learning disabilities.
Lancet, 221, 8-n.
Lou, H.C., Henrikson, L., Bruhn, P., Borner, H., & Bieber-
Nielson, J. (1989). Striatal dysfunction in attention
deficit and hyperkinetic disorder. Archives of
Neurology, 41, 48-52.
Luria, A.R. (1973). The Working Brain. New York: Basic
Books.
Mannuzza, S., Klein, R.G., Bessler, A., Malloy, P., &
LaPadula, M. (1993). Adult outcome of hyperactive boys.
Archives of General Psychiatry. 21, 565-576.
McBride, D.K. & Payne, R.B. (1980). The sex difference in
rotary pursuit performance: Aptitude or inhibition?
Journal Qf Motor.-Behavior, 12, 270-280.
McGee, R. & Share, D.L. (1988). Attention deficit
hyperactivity disorder and academic failure: Which
comes first and what should be treated? Journal of the
American Academy of Child and Adolescent Psychiatry.
22, 318-325.
Milberger, S., Biederman, J., Faraone, S.V., Murphy, J., &
Tsuang, M.T. (1995). Attention deficit hyperactivity
disorder and comorbid disorders: Issues of overlapping
symptoms. American Journal of Psychiatry. 152. 1793-
1799.


137
deficits in children with ADHD. However, this finding was
not significant for either the ADHD or control groups
separately, making interpretation of this finding difficult.
Larger sample sizes in later studies may allow for
confirmation and interpretation of this finding.
There were significant individual differences in the
ability to acquire motor skills. Correlations between the
learning index and time on target for each block indicated
that motor ability and motor learning were separable, as it
was difficult to predict good and bad learners from their
initial performance.
Implications
The current results contradict the suggestion that the
motor difficulties of children with ADHD lie in their
initial processing of task demands, rather than their
ability to form motor programs through practice (Leavell,
Ackerson, & Fischer, 1995). Methodological differences
between the current study and the study conducted by
Leavell, Ackerson, and Fischer (1995) may help explain the
contradictory findings. In the earlier study, children only
completed five total trials, followed by a single delay


I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
-P-P-! ^~
Griffin
:iate Professor of
Special Education
This dissertation was submitted to the Graduate Faculty
of the College of Health Professions and to the Graduate
School and was accepted as partial fulfillment of the
requirements for the degree of Doctor of Philosophy.
December, 1996
Dean, College of Health
Professions
Dean, Graduate School


25
disorder {Szatmari, Offord, & Boyle, 1989a). Attention
difficulties and psychomotor disturbances are overlapping
symptoms that may cause difficulty in making a differential
diagnosis between ADHD and a mood disorder (Milberger et
al., 1995). However, research has indicated that between 90
and 100 percent of children retain the diagnosis of ADHD
after controlling for this overlap (Milberger, et al.,
1995). This suggested that ADHD can be distinguished from
comorbid mood disorders and that treatment plans should
consider all comorbid diagnoses (Milberger et al., 1995).
Learning Problems in Children with. ADHD
Children with ADHD are difficult for both parents and
teachers to control because of their inability to stay on
task, failure to follow instructions, and distractibility.
In addition, children with ADHD were rated by teachers as
displaying significantly more aggressive behaviors than
normal controls (Barkley, DuPaul & McMurray, 1990) Mild
ADHD symptoms in the home can become extremely problematic
in the structured environment of the classroom, and teachers
are likely to be the first to recognize ADHD in a child
(Szatmari, Offord, & Boyle, 1989a). Teachers often have


85
appeared that autistic children are also capable of learning
a novel motor skill (Wek & Husak, 1989).
The impact of attention difficulties on rotary pursuit
performance may be relevant to children with ADHD.
Inattention and the inability to form motor programs may
both play a role in their motor learning. To determine the
effect of motor programming deficits, the motivation of
children with ADHD should be controlled to prevent the
additional effects of inattention and impulsivity on
results.
Sex Differences on the Pursuit Rotor
Research findings regarding sex differences in pursuit
rotor performance have been inconsistent. No sex
differences were found in the performance of children in
kindergarten through third grade (Davol, Hastings, & Klein,
1965), a finding replicated with a group that also contained
children in the fourth and fifth grades (Davol & Breakell,
1968). Another study indicated that the performance of boys
is significantly better than that of girls, but used a
subject pool that included children with mild mental
retardation (Simenson, 1973). Under massed practice


9
better accounted for by another mental disorder (e.g.,
Mood Disorder, Anxiety Disorder, Dissociative Disorder,
or a Personality Disorder).
Code based on type:
314.01 Attention-Deficit/Hyperactivity Disorder,
Combined Type: if both Criteria A1 and A2 are met for
the past 6 months
314.00 Attention-Deficit/Hyperactivity Disorder,
Predominantly Inattentive Type: if Criterion A1 is met
but Criterion A2 is not met for the past 6 months
314.01 Attention-Deficit/Hyperactivity Disorder,
Predominantly Hyperactive-Impulsive Type: if Criterion
A2 is met but Criterion A1 is not met for the past 6
months
(BSM-IV, 78-85)
This nomenclature represents a return to consideration of
each of the three behavioral elements equally, unlike DSM-
III-R criteria (American Psychiatric Association, 1987),
which included only the ill-defined category of
undifferentiated attention deficit disorder to classify
predominantly inattentive children. As noted above,
significant differences have been found between the ADHD-
combined group and children who primarily displayed
inattentive symptoms (Goodyear & Hynd, 1992).


109
paper with equal numbers of either a "1" or a "211, into four
paper bags, two for the ADHD group and two for the control
group. Children were not told the meaning of the numbers
and only children in the reward conditions were asked to
choose a reward prior to the rotary pursuit task. These
children were allowed to choose from a selection of small
rewards (baseball cards, stickers, etc.), and told that they
would receive a reward each time that their performance
improved or stayed the same. This was to avoid a loss of
motivation that may have occurred when the children reached
performance ceilings and could no longer be rewarded for
improvements. Children in the no-reward groups were
encouraged to do their best on the rotary pursuit, but did
not receive any rewards based on performance. These
children received a small reward after completing the
protocol, but were unaware of this during the task.
Following assignment to a condition, the pursuit rotor
task was demonstrated to each child and they were told that
the goal was to keep the stylus in contact with the
rotating target. Performance on the pursuit rotor was
measured by the number of seconds the child spent on target.
Subjects were given between one and four practice trials on


116
Neuropsychological Measures
Continuous Performance Test
On the CPT cancellation task, no significant
differences were found between the group of children with
ADHD and the control group on hit percentage (L (62) = -.02,
ns) or omission errors (£ (62) = -.02, ns; Table 3).
Children with ADHD made significantly more commission errors
{£. (62) = 2.55, p <.05) and the reaction time of children
with ADHD on the cancellation task was significantly faster
than the control group {£. (62) = -2.01, p < .05). On the
CPT conditional cancellation task, no significant
differences were found between the ADHD and control groups
on hit percentage (t (62) = -1.22, ns), omission errors (£
(62) = 1.10, ns) or reaction time (£ (62) = -.74, ns; Table
3). The ADHD group made significantly more commission
errors than the control group {£ = 2.07, p < .05).
10 Screening. Grooved Pegboard and
Spatial Orientation
There was no significant difference between the
interpolated IQ scores of the ADHD and control groups (t


CHAPTER 8
DISCUSSION
Although children with ADHD are frequently reported to
have poor motor coordination (Barkley, 1990), little
research to date has investigated the mechanisms of this
incoordination. Motor incoordination in children with ADHD
has been attributed to inattention and impulsivity (Pelham
et al. 1990) However, children with ADHD have been found
to have abnormalities in both the metabolism (Lou et al.,
1989) and structure (Hynd et al., 1993; Castellanos et al.,
1996) of brain areas associated with both orientation to
stimuli (Rolls & Johnstone, 1992) and the formation of motor
programs (Saint-Cyr, Taylor, Trepanier, & Lang, 1992).
These findings suggested that the incoordination of children
with ADHD is primarily related to deficits in the formation
of motor programs and not only inattention and impulsivity.
131


41
significantly higher percentages than in control groups.
Siblings, and especially brothers, of children with ADHD
often had a diagnosis of ADHD (Biederman et al., 1990).
After controlling for socioeconomic status and
intactness of the family, relatives of children with ADHD
children were still significantly more likely than controls
to have a diagnosis of attention deficit disorder (Biederman
et al. 1990). However, these factors also increased the
risk for ADHD in the families of control groups, suggesting
that environmental factors do impact the development of ADHD
symptoms (Biederman et al., 1990). The high rates of
attention problems and increased risk for antisocial
behaviors in fathers of children with ADHD may explain the
high rates of separation and divorce in the homes of these
children (Barkley, Fischer, Edelbrock, & Smallish, 1991).
The heritability of ADHD was supported by twin studies.
Concordance rates for ADHD dizygotic twins are significantly
higher than those for monozygotic twins (Gillis, Gilger,
Pennington, & DeFries, 1992). This finding was stable for
both sexes, strengthening the hypothesis of ADHD
heritability. This study used reading-disabled twins, so it
was possible the findings were influenced by the


17
Characteristics-pf ADHD
£ex Piff.ergnceg in Children with ADHD
Sex differences in the behavior of ADHD children have
generally not been supported by research (Breen, 1989),
although some behavioral and cognitive differences have been
found (Berry, Shaywitz, & Shaywitz, 1985). Boys with ADHD
were more aggressive and harder to control at school,
perhaps resulting in a higher rate of referral to clinics
than girls with ADHD (Berry, Shaywitz, & Shaywitz, 1985).
Girls with ADHD demonstrated significantly fewer aggressive
and disruptive behaviors, but significantly more cognitive
deficits and a higher likelihood of rejection by peers than
boys with ADHD (Berry, Shaywitz, & Shaywitz, 1985). Verbal
IQ was significantly lower in girls with ADHD and they were
rated as having more language difficulties than boys. No
significant sex differences were found in attention,
hyperactivity, or impulsivity, and the overall behavioral
profile for both ADHD boys and girls was similar. These
results suggested that, because of their less disruptive
behavior, girls with ADHD who do not have other academic or


abnormal in children with ADHD. The major hypothesis of
this study was that children with ADHD would have difficulty
forming motor programs through practice. The photoelectric
pursuit rotor was used to compare the motor learning of
children with ADHD to that of normal controls. Small
rewards have been found to increase the performance of
children with ADHD without the use of medication; therefore,
a reward condition was used to control for motivation and
attention. There were 64 subjects in the current study (31
ADHD, 33 control). Neuropsychological measures of
attention, impulsivity, fine motor coordination, and spatial
judgement were administered and significant differences in
impulsivity and fine motor coordination with the non
dominant hand were found between the ADHD and control
groups. Children were randomly assigned either to a reward
or no reward condition, for a total of four groups
(ADHD/Reward, ADHD/No Reward, Control/Reward, Control/No
Reward). Six blocks of five, 30-second pursuit rotor trials
were administered, in a manner consistent with distributed
practice. Repeated measures ANOVAs indicated that the ADHD
group had deficits in motor learning compared with the
control group. Multiple regression analysis performed for
vii


45
less careful in responding to a CPT task over the course of
the test, suggesting that impairment in sustained attention
is at least partially responsible for ADHD symptoms (Power,
1992). However, if the vigilance task used was designed for
assessment of seriously impaired patients, children with
ADHD may perform at the same level as normal children
(Zametkin et al, 1990). Use of stimulant medication can
alter the performance of an ADHD child on the CPT (Corkum &
Siegel, 1993), as can the presence or absence of an examiner
(Power, 1992). The negative effect of an examiner's absence
was frequently seen in children with ADHD who had strong
hyperactive or aggressive features, who are most prone to
act up when adult supervision is removed (Power, 1992).
It has been argued that deficits in physiological
arousal, rather than problems in sustained attention, are
primarily responsible for ADHD symptoms (Corkum & Siegel,
1993). Physiologically-based underarousal was found in
patients with other disorders of sustained alertness
(Weinberg & Harper, 1993). The concept of physiological
arousal deficits is controversial, however, as children with
attention deficits may become overaroused in some
situations, especially those involving a highly desired


132
Sample Characteristics
This study examined the development of motor programs
in 7-11 year old children with ADHD compared to normal
controls from the same age group. Prepubertal children were
chosen to avoid maturation effects that may effect motor
learning. The groups were not significantly different by
ethnicity or interpolated Full Scale IQ. There was no
relationship found between motor learning and academic
tutoring received by children; however, children with
learning disorders were excluded from the study. The
control group had a significantly higher socioeconomic
status (Hollingshead, 1975) than the ADHD group.
Socioeconomic status has been reported to have a significant
effect on motor learning, with lower-status children having
more difficulty (Davol & Breakell, 1968), but no effect was
found in this study. Unlike the current study, the previous
research (Davol & Breakell, 1968) did not control for the
effects of disruptive behavior or learning disabilities.
However, it is difficult to draw firm conclusions because
this study contained few subjects in the two lower
socioeconomic classes. The significant difference in gender


30
children who scored in the borderline range on achievement
tests {Hinshaw, 1992). Shifting criteria may lead either to
overly inclusive and expensive academic interventions for
all children with academic deficits, or to a failure to
provide children with ADHD academic remediation because
their disruptive behavior prompts teachers to ignore
learning problems (Semrud-Clikeman et al., 1992). A
comparison of three increasingly exclusive definitions of
learning disability indicated that the moderate definition
of learning disability, provided for under Public Law 94-
142, was effective in correctly classifying children with
comorbid diagnoses (Semrud-Clikeman et al., 1992). Under
criteria for Public Law 94-142, children with ADHD were
shown to have significantly higher rates of both reading and
arithmetic learning disabilities compared to normal
controls, suggesting that careful academic screening of
these children is necessary (Semrud-Clikeman et al., 1992).
The impact of oppositional and conduct problem
behaviors on early academic difficulties is often
exacerbated by the presence of ADHD and attention deficits
increase the difficulty of remediation (Hinshaw, 1992). The
combination of ADHD with conduct disorder greatly increases


127
TABLE 5
PERFORMANCE OF CONTROL GROUP OVER BLOCKS
COMPARISON df Significance
BLOCK
1
vs.
BLOCK
2
-7.13
32
£ <
.001
BLOCK
2
vs.
BLOCK
3
-4.19
32
£ <
. 001
BLOCK
3
vs.
BLOCK
4
-.04
32
ns
BLOCK
4
vs.
BLOCK
5
-1.32
32
ns
BLOCK
5
vs.
BLOCK
6
-1.71
32
ns


68
length of the insular region was shorter bilaterally and the
posterior segment of Wernicke's area {planum temporale),
both areas involved in language, were smaller in dyslexics
than in normal children. Compared to children with ADHD and
normal controls, dyslexic children had a reversed pattern
(L was due to the smaller left planum (Hynd et al, 1990).
Subject selection may also influence the results of
regional cerebral blood flow and metabolic studies.
Zametkin et al. (1990) and Zametkin et al. (1993) did not
analyze the data from ADHD-LD and ADHD-only subjects
separately. In addition to the low striatal blood flow
characteristic of ADHD, subjects with ADHD and comorbid
neurological diagnoses had more extensive reductions in the
central regions of the brain (Lou et al, 1989). While there
are similarities in the neurobiology of ADHD and
developmental learning disabilities, there are also
important differences that may influence research results if
not controlled (Lou et al., 1989; Lou, Henrikson, & Bruhn,
1990) .


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
ROTARY PURSUIT PERFORMANCE IN CHILDREN WITH
ATTENTION DEFICIT HYPERACTIVITY DISORDER
By
Andrew Colvin
December, 1996
Chairperson: Eileen B. Fennell
Major Department: Clinical and Health Psychology
Attention deficit hyperactivity disorder (ADHD) is a
disruptive behavior disorder characterized by inattention,
impulsivity, and motor overactivity. Motor delays and
incoordination are also commonly associated with ADHD, and
these problems may impact children's social and academic
functioning. However, the incoordination seen in these
children is often attributed to impulsivity and inattention,
and little research has investigated the causes of these
motor problems. Neural structures involved in the
development of motor programs have been identified as being
vi


18
psychiatric problems remain unreferred, and their needs
often remain unmet (Berry, Shaywitz, & Shaywitz, 1985) .
Similar attention and behavioral profiles in boys and
girls with ADHD have been supported in the research (Breen,
1989). Boys and girls with ADHD were rated as more
disruptive than controls in a controlled academic setting,
but there were no significant differences in behavior
between boys and girls with ADHD (Breen, 1989). Consistent
with Berry, Shaywitz, and Shaywitz (1985), the severity of
disruptive behaviors exhibited by girls with ADHD in a
controlled parent-child interaction was not significantly
worse than normal controls nor significantly better than
boys with ADHD. Both boys and girls with ADHD were rated by
teachers as having more externalizing behaviors than
controls and had similar difficulties on a vigilance task.
This indicated that both boys and girls with ADHD have
significant difficulties in sustained attention (Breen,
1989). No contrasts were found on measures of overall
cognitive ability. Breen (1989) interpreted these results
as supporting the similarity of ADHD symptoms in boys and
girls.


APPENDIX A
BACKGROUND INFORMATION
Please circle the appropriate answer or fill in the blank.
1. What is your relationship to this child?
1= Mother / 2 = Father / 3 = Other (specify)
2. How old is your child?
3. Is your child a BOY (1) or a GIRL (2)
4. Who does the child live with now?
1 = mother and father 4 = mother and stepfather
2 = mother only 5 = father and stepmother
3 = father only 6 = foster parents
7=other
5. How many brothers and sisters does this child have?
6. What is the highest grade you finished?
7. What is the highest grade your spouse finished?
8. Do you have a job? YES NO
If yes, what is your job?
9. Does your spouse have a job? YES NO
If yes, what is your spouses job?
10. Please estimate your family's current yearly income:
1=0- 4,999 4 = 15,000 19,999 7 = 30,000 34,999
2 = 5,000 9,999 5 = 20,000 24,999 8 = 35,000 39,999
3 = 10,000 14,999 6 = 25,000 29,999 9 = over 40,000
147


133
distribution between the ADHD and control groups had no
significant effect on motor skill acquisition. This was
consistent with research indicating a lack of sex
differences in the motor learning performance of children
(Davol, Hastings, & Klein, 1965; Davol & Breakell, 1968).
Overall, it appeared that differences on demographic
variables did not have an impact on the results of the
primary task.
Children in the ADHD group were diagnosed by clinicians
outside of this study. However, parent reports were used to
provide behavioral profiles of the two groups and reflected
significantly more inattention, impulsivity, hyperactivity,
and disruptive behavior in the ADHD group compared to the
control group. The differences in behavioral profiles
between groups were expected (Barkley, 1990) and suggested
that children in the ADHD group had been accurately
diagnosed.
Rotary Pursuit Performance
The major hypothesis of this study was that children
with ADHD would have significant difficulty in motor
learning compared to normal controls. Deficits in motor


57
Effects of Incoordination on Children._with ADHD
Difficulty in motor skill learning may have a number of
effects on children with ADHD, both in school (learning to
write and draw) and among their peers (learning skills
required for games). Fewer children with ADHD participate
in organized athletics, possibly as a result of difficulties
in learning the necessary skills (Szatmari, Offord, & Boyle,
1989b). Children with ADHD have been found to experience
significant difficulties learning new motor skills and
adequately performing in sports or other activities
(Szatmari, Offord, & Boyle, 1989b). Despite findings of
developmental difficulties and poor coordination, motor
learning in children with ADHD is rarely researched. The
disruptive behavior of children with ADHD causes significant
stress for the parents and teachers of these children
(Anastapoulos, Guevremont, Shelton, & DuPaul, 1992). As a
result, most research concentrates on causes and treatment
of this behavior. Research into the motor skills learning
may open a new window on intervention with these children,
both academically and socially (Conners & Delamater, 1980).
It may also provide further evidence of the processes used


97
attention (Corkum & Siegel, 1993). No significant group
difference was expected on a test of visuospatial ability
(Douglas, 1984).


102
withhold medication for at least 12 hours prior to their
child's participation in the study.
Measures
Behavior Rating Scales
Parents completed two rating scales designed to
estimate symptoms of ADHD in children, the 48-item revised
version of the Conners Parent Rating Scale (CPRS-R; Goyette,
Conners, & Ulrich, 1978) and an 18-item checklist of ADHD
symptoms drawn from the DSM-IV (American Psychiatric
Association, 1994; Appendix A). The CPRS-R has been found
to be reliable in assessing symptoms of ADHD (Barkley,
1990). These measures were used to compare the behavioral
profiles of the ADHD and control groups, but not to diagnose
ADHD. As noted above, the children in the ADHD group were
diagnosed by clinicians outside of this study.
Demographics
Parents completed a short demographic questionnaire
(Appendix B). This provided information on age, ethnicity,


36
conform to regular schedules and rules set by others
(Mannuzza et al., 1993). Compared to normal controls, a
greater percentage of adults with ADHD were diagnosed with a
comorbid psychiatric disorder, most commonly antisocial
personality disorder (Biederman et al., 1993). Similar to
the findings for educational and occupational status, adults
with uncomplicated ADHD were at greater risk for substance
abuse than controls {Mannuzza et al., 1993; Biederman et
al., 1995). Comorbid antisocial personality disorder added
greatly to this risk {Biederman et al., 1995).
Family Characteristics
Family and household variables, including urban
residence, family receiving public assistance, single parent
as head of household, and inadequate family functioning are
all significantly correlated with ADHD (Szatmari, Offord, &
Boyle, 1989b). In addition to these variables, children
with ADHD experience frequent changes in residence compared
to control children {Barkley, Fischer, Edelbrock, &
Smallish, 1990). Parents of children with ADHD have a
significantly greater incidence of psychiatric diagnoses


2
History
Still (1902) described "morbid defects of moral
control" in 20 children with no intellectual impairments or
brain injury. These children demonstrated symptoms that are
now associated with ADHD such as inattention, impulsivity,
lack of inhibition, aggression, and defiance of authority
figures. These symptoms were compared with those of
children who had suffered epilepsy, traumatic brain injury,
or encephalitis. The similar symptom picture led to the
belief that although there was no history of brain injury or
disease, children with a defect of moral control had an
underlying neurological deficit {Still, 1902). Family
psychopathology and minor physical anomalies noted in these
children were also cited as evidence for the existence of
minimal brain damage, which was the first primary diagnosis
given to children who displayed the symptoms of ADHD
{Cantwell 5c Baker, 1991). This diagnosis lost its clinical
utility as evidence accumulated that minor brain damage
actually resulted in multiple, nonspecific symptom pictures
(Spreen et al. 1984; Barkley, 1990).


79
component, regional cerebral blood flow in the frontal and
subcortical regions involved in attention increases
significantly (Haxby, Grady, Ungerlieder, & Horwitz, 1991).
These authors also reported increased blood flow in the
areas of cortex responsible for sensory processing (e.g.,
the occipital lobes and- somatosensory cortex) .
Overall, it appeared that children with ADHD have
cortical dysfunction in several areas, especially in the
right frontal and parietal cortices, and subcortical
dysfunction in areas responsible for modulating sensory
input, the caudate nucleus and thalamus. While the
dysfunction may be subtle and not influence the results of
formal neuropsychological testing {Barkley & Grodzinsky,
1994), it can and most likely does have an impact on daily
activities.


20
his review noted that research results conflict, Barkley
(1990) stated that up to 52% of children with ADHD may have
poor motor coordination, especially with fine motor skills.
In addition, children with ADHD have been shown to have
difficulties reproducing sequential hand movements (Breen,
1989). Compared with both normal controls and children with
learning disabilities, children with ADHD are significantly
more likely to be described as having poor coordination
(Barkley, DuPaul, & McMurray, 1990).
Accidents and Injury Risk in
Children with ADHD
The impulsivity and aggressiveness of ADHD children may
lead them to engage in physically dangerous activities
(Barkley, 1990). Children with ADHD recognized dangerous
situations as well as controls. Nonetheless, they rated
themselves as more likely to engage in hazardous activities
than did normal controls and underestimated the potential
severity of injuries (Farmer & Peterson, 1995). They also
generated fewer avoidance behaviors, suggesting a lack of
knowledge about safety rules (Farmer & Peterson, 1995).
Fractures and accidental poisonings are common among


141
in the ADHD/Reward group failed to demonstrate acquisition
of motor skills. Therefore, it appears that children with
ADHD have problems in generating appropriate behavioral
responses, even when adequately stimulated.
Although the magnitude of the statistically significant
differences between groups in time on target, ranging from
approximately 3 to approximately 7 seconds, did not appear
large, these differences occurred on a relatively simple
gross motor task. The lack of motor learning demonstrated
by children with ADHD on the pursuit rotor would most likely
be magnified by the more complex motor tasks in school or at
play. Lacking the ability to successfully learn motor
tasks, these children may become frustrated and act out,
leading to punishment from parents and teachers. They may
also be excluded from games because of their incoordination,
resulting in lowered self-esteem.
Knowledge of how children with ADHD acquire motor
skills may lead to effective methods of academic remediation
and increase their participation in sports and other games,
thereby improving peer relationships (Szatmari, Offord, &
Boyle, 1989b). Educating parents and teachers about the
motor learning difficulties of children with ADHD may lead


106
lighted target embedded in a turntable, a stylus held by the
subject, and an attached electronic counter to measure time
on target. The lighted target rotated in a circular motion
around the turntable, and the stylus was used to track the
motion of the target. The counter recorded the amount of
time that a subject successfully kept the stylus in contact
with the target. Performance scores on the pursuit rotor
vary between individuals, but learning curves tend to be
similar. The test has been found to have reliabilities of
around x = .90, indicating that differences in individual
performance are constant (Eysenck & Frith, 1977) When
given to cadet pilots as part of a motor test battery, the
pursuit rotor had good correlations with tests of motor
ability such as complex coordination (x = .65), rudder
control (x = -43) and finger dexterity (x = .45; Eysenck &
Frith, 1977). Factor analysis on the motor battery found
that the pursuit rotor loaded highly on a "coordination" or
"psychomotor" factor that included other tests of dexterity
and gross motor coordination (Eysenck & Frith, 1977). These
findings suggested that the pursuit rotor would provide a
satisfactory measure of motor learning ability.


155
Carlson, C.L., Pelham, W.E., Milich, R., & Dixon, J. (1992).
Single and combined effects of methylphenidate and
behavior therapy on the classroom performance of
children with attention deficit hyperactivity disorder.
Journal of Abnormal Child Psychology. 2£, 213-232.
Carter, C.S., Krener, P., Chaderjian, M., Northcutt, C., &
Wolfe, V. (1995) Asymmetrical visual-spatial
attentional performance in ADHD: Evidence for a right
hemispheric deficit. Biological Psychiatry. XL, 789-
797.
Castellanos, F.X., Giedd, J.N., Marsh, W.L., Hamburger,
S.D., Vaituzis, A.C., Dickstei, D.P., Sarfatti, S.E.,
Vauss, Y.C., Snell, J.W., Lange, N., Kaysen, D., Krain,
A., Ritchie, G.F., Rajapske, J.C., Rapoport, J.L.
(1996). Quantitative Brain Magnetic Resonance Imaging
in Attention-Deficit Hyperactivity Disorder. Archives
of-General Psychiatry, 1, 607-616.
Chugani, H.T., Phelps, M.E., & Mazziotta, J.C. (1987).
Positron emission tomography study of human brain
functional development. Annals of NeurolQgy, 22, 487-
497.
Cohen, R.A. (1993). The Neuropsychology of Attention. New
York: Plenum Press.
Conners, C.K. & Delamater, A. (1980). Visual-motor tracking
by hyperkinetic children. Perceptual and Motor Skills.
51. 487-497.
Conners, C.K. & Taylor, E. (1980). Pemoline,
Methylphenidate, and placebo in children with minimal
brain dysfunction. Archives of General Psychiatry. XL,
922-930.
Corkum, P.V. & Siegel, L.S. (1993). Is the continuous
performance test a valuable research tool for use with
children with attention deficit hyperactivity disorder?
Journal of Child Psychology and Psychiatry. XL, 1217-
1239.


95
results. It is possible that dysfunction in cortical-
subcortical systems of attention and motor control lead to
the characteristic features of ADHD. The hypothesis that
these children are physiologically underaroused continues to
be debated. Some evidence has been found to support this
theory, while other research has indicated that difficulties
in self-regulation explain apparent deficits in arousal.
Incoordination in these children may result from
difficulties in forming motor programs. An inability to
learn motor tasks may have an impact on both social and
academic functioning and may be related to the neural
substrate of ADHD. This study compared the performance of
children with ADHD on the rotary pursuit task to that of
normal children in an attempt to answer some of these
questions.
Specific Aims 3nd Hypotheses
Although motor skills deficits have been noted, little
research to date has investigated motor learning in children
with ADHD. Motor learning deficits were often explained by
inattention during skill learning (Pelham et al, 1990). The
present study provided information about motor skill


144
Time on target was the only measure of motor learning
used in this study. The use of error scores may have
provided additional information about the nature of between-
group differences in motor skill acquisition.
The children with ADHD who participated in this study
were diagnosed by several outside clinicians, perhaps
introducing significant variability into the ADHD group.
Individual clinicians may differ somewhat in rating the
symptoms of ADHD and in their criteria for diagnosing the
disorder. Diagnosis by a single clinician would help
control this source of variability in future research.
Summary and Directions for Future Research
This study investigated motor learning in children with
ADHD and the results suggested that as a group, children
with ADHD have significant deficits in acquiring new motor
skills. These deficits appeared to be a result of
dysfunction in forming motor programs, dysfunction that is
likely related to developmental abnormalities in the brains
of children with ADHD. An expansion of the current study
would be to investigate the effect of stimulant medications
on the motor skill acquisition of children with ADHD. If


TABLE 8
CORRELATIONS BETWEEN TIME ON TARGET AND LEARNING INDEX
130
TOTAL SAMPLE £ p
Block 1
.14
ns
Block 2
.46
. 001
Block 3
.57
. 001
Block 4
.64
.001
Block 5
.71
.001
Block 6
.80
. 001
ADHD GROUP
Block 1
- .13
ns
Block 2
.24
ns
Block 3
.41
ns
Block 4
.48
.01
Block 5
.60
.001
Block 6
.71
.001
CONTROL GROUP
Block 1
.15
ns
Block 2
.33
ns
Block 3
.43
.01
Block 4
.54
.01
Block 5
.63
.001
Block 6
.75
.001


83
performance even after several trials, suggesting deficient
programming of motor sequences.
Children who are mildly mentally retarded have
significantly more difficulty in motor learning than normal
controls (Simenson, 1973) Use of an audible feedback
signal for errors did not facilitate performance, but extra
practice trials did, suggesting that these children may
actually experience feedback as noxious (Simenson, 1973).
Later research contradicted this conclusion, as visual,
tactile, and auditory feedback were found to enhance motor
learning in both retarded and control children (Horgan,
1982). In fact, auditory feedback given when a subject was
on target helped retarded children attain normal levels of
performance. These results suggested that task conditions
affect motor learning in retarded children and that optimal
conditions result in normal levels of motor learning
(Horgan, 1982).
Heitman and Gilley (1989) investigated the performance
of mentally retarded adolescents using either blocks of
same-speed trials or a random distribution of speeds. There
was no significant effect for the blocked condition,
suggesting that inattention to assigned tasks plays a role


ROTARY PURSUIT PERFORMANCE IN CHILDREN
WITH ATTENTION DEFICIT HYPERACTIVITY DISORDER
By
ANDREW COLVIN
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1996


86
conditions, there were no significant differences between
first-grade boys and girls at lower speeds (15 & 30 rpm),
but boys demonstrated better learning than girls at the
highest speed (45 rpm; Horn, 1975). Consistent with this
finding, elementary school girls had lower ceiling speeds
than boys (Dunham, Allan, & Winter, 1985). Although
children were not compared in each grade, the major
differences appeared to exist in kindergarten, and sixth
grades, while girls in grades two through five appeared to
more closely match the performance of boys (Dunham, Allan, &
Winter, 1985). When speed of rotation was held constant,
the performances of boys and girls were not significantly
different (Ruffer, 1984). In addition, the performance of
college-age women was not significantly different from men
in distributed practice conditions with rest periods of 10
seconds or longer (McBride & Payne, 1980) No research to
date has compared the performance of boys and girls when
speeds were set individually, the method used in the current
study.


35
regulatory mechanisms in students with ADHD fail to screen
spontaneous, unrelated thoughts (Douglas, 1983). These
thoughts then disrupt concentration and make completion of
experimental tasks or academic work more difficult (Shaw &
Giambra, 1993) .
Although the continuation of ADHD symptoms into
adulthood has been a controversial subject, several studies
have provided evidence supporting adult ADHD (Mannuzza et
al., 1993; Biederman et al., 1993). Symptoms of ADHD have
been found to persist in at least 11% of subjects with a
childhood diagnosis of the disorder, a figure that the
authors believed to be an underestimate (Mannuzza et al.,
1993). The educational attainment and socioeconomic status
of adults with ADHD was significantly lower than achieved by
controls (Mannuzza et al., 1993; Biederman et al., 1993).
Although comorbid psychiatric diagnoses played some role in
adult educational and occupational status, history of ADHD
appeared to have a unique impact (Mannuzza et al., 1993).
Most adults who had been diagnosed as ADHD in childhood were
employed, but few held professional positions and compared
to controls, a greater proportion owned their own
businesses, perhaps to compensate for an inability to


121
Multiple Regression Analyses
An index of learning was created by subtracting Block 1
performance from Block 6 performance. A multiple regression
analysis was conducted for the entire sample to examine the
relationship between this index and attention, impulsivity,
fine motor coordination, and spatial judgement. The number
of subjects made it necessary to limit the number of
independent variables entered into the equation to six.
Omission scores for both CPT tasks were chosen as the best
measures of attention, and both commission scores were used
as the best measures of impulsivity. Grooved Pegboard
performance for the non-dominant hand was used to measure
fine motor coordination, because group differences made it
more likely that this measure would be related to problems
in motor learning. The number correct on the Judgement of
Line Orientation was used as a measure of spatial judgment.
A stepwise multiple regression procedure was used to find
the predictive values of these variables. The only variable
found to be a significant predictor of learning was
commission errors on the CPT conditional cancellation task.
Results of the multiple regression are listed in Table 7.


ROTARY PURSUIT PERFORMANCE IN CHILDREN
WITH ATTENTION DEFICIT HYPERACTIVITY DISORDER
By
ANDREW COLVIN
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1996

ACKNOWLEDGEMENTS
The hard work and support of my committee was helpful
to me throughout this project. Eileen Fennell's advice and
encouragement was invaluable as I conceptualized this study.
Russell Bauer's knowledge of pursuit rotor methodology and
statistics aided me in formulating the protocol. Ernest
Bordini and the parents of the North Florida Chapter of the
Children and Adults with ADD were very supportive of this
research. Bernard Maria was very helpful in allowing access
to patients of the Children's Medical Services neurology
clinic. Wes Corbett of P.K. Yonge Developmental Research
School is thanked for allowing access to his students. Jack
Saarella of the University Lutheran Church is thanked for
allowing me to contact the families in his church. Tara
Saia's hard work and persistence during data collection were
outstanding, as she was extremely conscientious throughout
her work as a graduate assistant. Amy Perwien and Ryan
Bernstein were also extremely helpful during data
collection. My family was very supportive throughout this
ii

project. Without the love, understanding and patience of ray
wife, Cheryl Colvin, this dissertation would not have been
completed.

TABLE OF CONTENTS
ACKNOWLEDGMENTS Ü
ABSTRACT vi
CHAPTERS
1. CHILDREN WITH ADHD 1
Prevalence 1
History 2
Current Diagnostic Criteria 6
ADHD With and Without Hyperactivity 10
Characteristics of ADHD 17
Assessment and Treatment 42
2. CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD . . 59
Impact of Right Hemisphere Dysfunction on
ADHD 59
Morphological Differences in Children with
ADHD 60
Cerebral Blood Flow in Children with ADHD . . 64
Brain Metabolism in Children with ADHD ... 65
Issues of Subject Selection 67
Neuropsychological Testing of Children with
ADHD 69
Neuroanatomy of Attention 74
3. THE PURSUIT ROTOR AND MOTOR SKILL
ACQUISITION 80
The Pursuit Rotor 80
Motor Skill Acquisition in Children with
ADHD 87
iv

Neuroanatomy of Motor Systems 8 9
4. SUMMARY AND RATIONALE 93
Summary 93
Specific Aims and Hypotheses 95
5. DESIGN 98
6. PROCEDURE AND METHODS 100
Subjects 100
Measures 102
Procedure 107
7. RESULTS 114
Initial Analyses 114
Neuropsychological Measures 116
Analyses of Pursuit Rotor Performance .... 117
8 . DISCUSSION 131
Sample Characteristics 132
Rotary Pursuit Performance 133
Secondary Analyses 135
Implications 137
Limitations 142
Summary and Directions for Future Research . 144
APPENDICES
A BACKGROUND INFORMATION 147
B BEHAVIOR CHECKLIST 149
REFERENCES 151
BIOGRAPHICAL SKETCH 169
v

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
ROTARY PURSUIT PERFORMANCE IN CHILDREN WITH
ATTENTION DEFICIT HYPERACTIVITY DISORDER
By
Andrew Colvin
December, 1996
Chairperson: Eileen B. Fennell
Major Department: Clinical and Health Psychology
Attention deficit hyperactivity disorder (ADHD) is a
disruptive behavior disorder characterized by inattention,
impulsivity, and motor overactivity. Motor delays and
incoordination are also commonly associated with ADHD, and
these problems may impact children's social and academic
functioning. However, the incoordination seen in these
children is often attributed to impulsivity and inattention,
and little research has investigated the causes of these
motor problems. Neural structures involved in the
development of motor programs have been identified as being
vi

abnormal in children with ADHD. The major hypothesis of
this study was that children with ADHD would have difficulty
forming motor programs through practice. The photoelectric
pursuit rotor was used to compare the motor learning of
children with ADHD to that of normal controls. Small
rewards have been found to increase the performance of
children with ADHD without the use of medication; therefore,
a reward condition was used to control for motivation and
attention. There were 64 subjects in the current study (31
ADHD, 33 control). Neuropsychological measures of
attention, impulsivity, fine motor coordination, and spatial
judgement were administered and significant differences in
impulsivity and fine motor coordination with the non¬
dominant hand were found between the ADHD and control
groups. Children were randomly assigned either to a reward
or no reward condition, for a total of four groups
(ADHD/Reward, ADHD/No Reward, Control/Reward, Control/No
Reward). Six blocks of five, 30-second pursuit rotor trials
were administered, in a manner consistent with distributed
practice. Repeated measures ANOVAs indicated that the ADHD
group had deficits in motor learning compared with the
control group. Multiple regression analysis performed for
Vll

the entire sample suggested that impulsivity may be a
significant predictor of pursuit rotor performance, but this
was not found for either group separately. The motor
programming deficits found in the children with ADHD were
discussed in terms of their relationship to neural
structures.
viii

CHAPTER 1
CHILDREN WITH ADHD
Prevalence
Attention deficit hyperactivity disorder (ADHD) is one
of the most common childhood psychiatric disorders. It is
estimated that 3%-5% of school-age children meet criteria
for ADHD (American Psychiatric Association, 1994), but the
prevalence may be as high as 12% (Trites, Dugas, Lynch, &
Ferguson, 1979). Depending on the population studied, four
to nine times as many boys as girls are diagnosed with ADHD
(American Psychiatric Association, 1994). A child's age has
not been shown to have a significant effect on the diagnosis
of ADHD, although there may a trend towards fewer symptoms
as the child ages (Szatmari, Offord, & Boyle, 1989a).
Children with ADHD are estimated to be 30% to 40% of
referrals to clinicians (Barkley, 1990) and so research into
ADHD is critical as a basis for clinical work.
1

2
Histnry
Still (1902) described "morbid defects of moral
control" in 20 children with no intellectual impairments or
brain injury. These children demonstrated symptoms that are
now associated with ADHD such as inattention, impulsivity,
lack of inhibition, aggression, and defiance of authority
figures. These symptoms were compared with those of
children who had suffered epilepsy, traumatic brain injury,
or encephalitis. The similar symptom picture led to the
belief that although there was no history of brain injury or
disease, children with a defect of moral control had an
underlying neurological deficit (Still, 1902). Family
psychopathology and minor physical anomalies noted in these
children were also cited as evidence for the existence of
minimal brain damage, which was the first primary diagnosis
given to children who displayed the symptoms of ADHD
(Cantwell & Baker, 1991). This diagnosis lost its clinical
utility as evidence accumulated that minor brain damage
actually resulted in multiple, nonspecific symptom pictures
(Spreen et al. 1984; Barkley, 1990).

3
Although inattention continued to be recognized as a
symptom of the disorder, motor overactivity was the basis
for the next diagnostic schema, hyperkinetic reaction of
childhood (American Psychiatric Association, 1968; Cantwell
& Baker, 1992) . However, inattention and impulsivity were
often essential characteristics of these childrens' symptoms
and the diagnostic nomenclature was changed to reflect this
(Goodyear & Hynd, 1992) . Attention deficit disorder (ADD),
a diagnosis that included the three essential features of
inattention, impulsivity, and hyperactivity, was recognized
in the third edition of the Diagnostic and Statistical
Manual of Mental Disorders (DSM-III; American Psychiatric
Association, 1980). Two subtypes of ADD were described in
the DSM-III; the first included all three behavioral
characteristics, with emphasis on motor hyperactivity
(ADD/H), and the second group was characterized by attention
deficits, with little or no overactivity (ADD/WO). The
existence of ADD/WO was the subject of considerable debate
following publication of the DSM-III and during development
of the next diagnostic system, the DSM-III-R (American
Psychiatric Association, 1987) . Attention deficit disorder
without hyperactivity is a rare symptom cluster (Szatmari,

4
Offord, & Boyle, 1989a), making research with this group of
children difficult. The scarcity of data on children with
ADD/WO led the developers of the DSM-III-R (American
Psychiatric Association, 1987) to recognize only Attention
Deficit Disorder with hyperactivity as a diagnostic category
(Goodyear & Hynd, 1992) . The diagnostic criteria for ADHD
in the DSM-III-R were as follows:
Attention Deficit Hyperactivity Disorder
Note: Consider a criterion met only if the behavior is
considerably more frequent than that of most people of
the same mental age.
A. A disturbance of at least six months during which
at least eight of the following are present:
(1) often fidgets with hands or feet or squirms in seat
(in adolescents may be limited to subjective feelings
of restlessness)
(2) has difficulty remaining seated when required to do
so
(3) is easily distracted by extraneous stimuli
(4) has difficulty awaiting turn in games or group
situations
(5) often blurts out answers to questions before they
have been completed
(6) has difficulty following through on instructions
from others (not due to oppositional behavior or
failure of comprehension), e.g., fails to finish chores

5
(7) has difficulty sustaining attention in tasks or
play activities
(8) often shifts from one uncompleted activity to
another
(9) has difficulty playing quietly
(10) often talks excessively
(11) often interrupts or intrudes on others, e.g.,
butts into other children's games
(12) often does not seem to listen to what is being
said to him or her
(13) often loses things necessary for tasks or
activities at school or at home (e.g., toys, pencils,
books, assignments)
(14) often engages in physically dangerous activities
without considering possible consequences (not for the
purpose of thrill-seeking), e.g., runs into street
without looking
B. Onset before the age of seven
C. Does not meet the criteria for a Pervasive
Developmental Disorder
Criteria for the severity of Attention-Deficit
Hyperactivity Disorder:
Mild: Few, if any symptoms in excess of those required
to make the diagnosis and only minimal or no impairment
in school and social functioning.
Moderate: Symptoms or functional impairment
intermediate between "mild'1 and "severe."
Severe: Many symptoms in excess of those required to
make the diagnosis and significant and pervasive

6
impairment in functioning at home and school and with
peers.
(DSM-III-R. 50-53)
Considerable research, to be discussed below, provided
strong data in support of multiple subtypes and Attention
deficit disorder was again divided into subtypes with the
appearance of the DSM-IV American Psychiatric Association,
1994) .
Current Diagnostic Criteria
The Fourth Edition of the Diagnostic and Statistical
Manual for Mental Disorder (DSM-IV; American Psychiatric
Association, 1994) recognizes three subtypes of ADHD; ADHD-
combined type, ADHD-predominantly inattentive type, and
ADHD-predominantly hyperactive/impulsive type. Children who
meet criteria for the predominantly inattentive type do not
meet hyperactive/impulsive criteria, while children who fall
into the hyperactive/impulsive category are overactive, but
not distractible. The complete DSM-IV diagnostic criteria
are as follows:
DSM-IV Criteria for Attention Deficit/Hyperactivity
Disorder

7
A. Either (1) or (2) :
(1) six (or more) of the following symptoms of
inattention have persisted for at least 6 months to a
degree that is maladaptive and inconsistent with
developmental level:
Inattention
(a) often fails to give close attention to details or
makes careless mistakes in schoolwork, work, or other
activities
(b) often has difficulty sustaining attention in tasks
or play activities
(c) often does not seem to listen when spoken to
directly
(d) often does not follow through on instructions and
fails to finish schoolwork, chores, or duties in the
workplace (not due to oppositional behavior or failure
to understand instructions)
(e) often has difficulty organizing tasks and
activities
(f) often avoids, dislikes, or is reluctant to engage
in tasks that require sustained mental effort (such as
schoolwork or homework)
(g) often loses things necessary for tasks or
activities (e.g., toys, school assignments, pencils,
books, or tools)
(h) is often easily distracted by extraneous stimuli
(i) is often forgetful in daily activities
(2) six (or more) of the following symptoms of
hyperactivity-impulsivity have persisted for at least 6
months to a degree that is maladaptive and inconsistent
with developmental level:

8
Hyperactivity
(a) often fidgets with hands or feet or squirms in seat
(b) often leaves seat in classroom or in other
situations in which remaining seated is expected
(c) often runs about or climbs excessively in
situations in which it is appropriate (in adolescents
or adults, may be limited to subjective feelings of
restlessness)
(d) often has difficulty playing or engaging in leisure
activities quietly
(e) is often "on the go" or often acts if "driven by a
motor"
(f) often talks excessively
Impulsivity
(g) often blurts out answers before questions have been
completed
(h) often has difficulty awaiting turn
(i) often interrupts or intrudes on others (e.g., butts
into conversations or games)
B. Some hyperactive-impulsive or inattentive symptoms
that caused impairment were present before age 7 years.
C. Some impairment from the symptoms is present in two
or more settings (e.g., at school [or work] and at
home).
D. There must be clear evidence of clinically
significant impairment in social, academic, or
occupational functioning.
E. The symptoms do not occur exclusively during the
course of a Pervasive Developmental Disorder,
Schizophrenia, or other Psychotic Disorder and are not

9
better accounted for by another mental disorder (e.g.,
Mood Disorder, Anxiety Disorder, Dissociative Disorder,
or a Personality Disorder).
Code based on type:
314.01 Attention-Deficit/Hyperactivity Disorder,
Combined Type: if both Criteria A1 and A2 are met for
the past 6 months
314.00 Attention-Deficit/Hyperactivity Disorder,
Predominantly Inattentive Type: if Criterion A1 is met
but Criterion A2 is not met for the past 6 months
314.01 Attention-Deficit/Hyperactivity Disorder,
Predominantly Hyperactive-Impulsive Type: if Criterion
A2 is met but Criterion A1 is not met for the past 6
months
(DSM-IV. 78-85)
This nomenclature represents a return to consideration of
each of the three behavioral elements equally, unlike DSM-
III-R criteria (American Psychiatric Association, 1987),
which included only the ill-defined category of
undifferentiated attention deficit disorder to classify
predominantly inattentive children. As noted above,
significant differences have been found between the ADHD-
combined group and children who primarily displayed
inattentive symptoms (Goodyear & Hynd, 1992).

10
ADHD With and Without Hyperactivity
Comparison Studies of Children
with ADD/H and ADD/WO
Groups of children with ADD, with and without
hyperactivity, differed significantly in several respects
(Lahey et al., 1987) . Children with ADD/H were more
impulsive, younger at the time of clinic referral, and had
significantly higher rates of overt conduct problems than
children with ADD/WO. Children with ADD/H were more likely
to be placed in a classroom for children with severe
behavior problems (Barkley, DuPaul, & McMurray, 1990). Both
groups of children experience social isolation, but children
with ADD/H have been found to experience rejection by peers,
while children with ADD/WO are withdrawn (Cantwell & Baker,
1992). ADD/H children also had less self-control and
significantly higher ratings of both internalizing and
externalizing behaviors on the CBCL than their ADD/WO
counterparts (Barkley, DuPaul, & McMurray, 1990).
The symptoms of children with ADD/H were often
considered more disruptive by teachers and parents,
resulting in earlier referral to clinics (Lahey et al.,

11
1987). In fact, research has indicated that children with
ADD/H were referred to clinics one year earlier than
children with ADD/WO (Goodyear & Hynd, 1992) , and clinic
referrals of ADD/H children resulted from their disruptive
behaviors (Cantwell & Baker, 1992). ADD/WO children were
more likely to be referred for academic difficulties and
depression, symptoms that could be secondary to attention
deficits (Cantwell & Baker, 1992) .
Children with ADD/WO have been rated by their teachers
as having a slower cognitive tempo, or speed of problem
solving (Lahey et al. 1987; Lahey, Schaughency, Frame, &
Strauss, 1985). Other researchers have described these
children as daydreamy, confused, and lost in thought
(Barkley, DuPaul, & McMurray, 1990). Symptoms of
internalizing behavior problems, such as anxiety,
depression, and obsessive-compulsive behaviors, were found
in children with ADD/WO by (Lahey et al., 1987), a result
confirmed in later studies (Barkley, DuPaul, & McMurray,
1990). Children with ADD/H had significantly more overt
conduct problems, but the two groups did not have
significant differences in the number of covert problems
such as lying and truancy.

12
Sluggish cognitive tempo in children with ADD/WO has
been a consistent finding in the research (Lahey et al.,
1988; Barkley, DuPaul, and McMurray, 1990). A factor-
analytic investigation of both the teacher-completed SNAP
checklist (Pelham, Atkins, & Murphy, 1981) and a set of
clinician-rated symptoms provided evidence for slowed
cognitive tempo, inattention, and disorganization in
children with ADD/WO (Lahey et al., 1988). The SNAP yielded
two factors, inattention-disorganization and motor
hyperactivity-impulsivity, suggesting that inattention can
be separated from hyperactivity, resulting in at least two
distinct behavioral syndromes involving attention. In
addition to inattention-disorganization and hyperactivity-
impulsivity, a factor identified as sluggish cognitive tempo
emerged from the clinician ratings of clinic-referred
children. Slowed cognitive tempo may not have been
identified on the SNAP because no items on the checklist are
related to this symptom cluster (Lahey et al., 1988).
Sluggish cognitive tempo was related to the drowsiness and
forgetfulness that had been previously identified (Lahey,
Schaughency, Frame, & Strauss, 1985) in teacher ratings of
children with ADD/WO. In addition, slowed tempo is

13
consistent with teacher ratings that identified ADD/WO
children as daydreamy, apathetic, and lethargic (Barkley,
DuPaul, & McMurray, 1990).
The slowed tempo, daydreaminess, and lethargy displayed
by children with ADD/WO may result from a greater
preoccupation with internal stimuli, rather than the
disinhibition that characterizes children with ADD/H
(Barkley, DuPaul, & McMurray, 1990). Although children of
both subtypes were rated as inattentive in school, children
with ADD/H exhibited more disruptive behaviors, while
children with ADD/WO were more often seen as unmotivated
(Barkley, DuPaul, & McMurray, 1990). There were also
differences between the family psychiatric histories of the
two groups. Relatives of children with ADD/WO were more
likely to have a history of anxiety disorder, while
relatives of children with ADD/H had a higher incidence of
aggressive behavior and substance abuse (Barkley, DuPaul, &
McMurray, 1990). This was consistent with the conclusions
of a review that suggested an
"attentional/cognitive/anxiety" constellation of symptoms in
ADD/WO, rather than the "attentional/behavioral/impulsive"
characteristics of ADD/H (Goodyear & Hynd, 1992).

14
Neuropsychological Studies of ADD/H
and ADD/WO Children
Differences between ADD/H and ADD/WO children have been
found to exist on neuropsychological measures, but the exact
nature of these differences was not always clear.
Methodological difficulties, especially the relative rarity
of children with ADD/WO made it difficult to carry out these
studies (Goodyear & Hynd, 1992). Some authors suggested
that behavioral, rather than neuropsychological, criteria
should be used to differentiate between the subtypes (Hynd,
et al., 1989). These researchers found that children with
attention deficits and clinic-referred controls had similar
performances on simple reaction time tasks. A task
requiring speeded matching of letter strings, the most
difficult task in the study, did discriminate between
children with attention deficits and clinic-referred
controls, with the ADD children performing worse than the
control children. However, there was no significant
difference in the performance of ADD/H and ADD/WO children
on these tasks, suggesting little difference in the
neuropsychology of the subtypes (Hynd et al., 1989).

15
Recent changes in methodology have resulted in more
consistent findings of cognitive differences between the
attention deficit subtypes, differences that are consistent
with the behavior pattern of each group (Goodyear & Hynd,
1992). A review of the literature indicated that there were
differences in information processing styles between the
subtypes (Goodyear & Hynd, 1992). Children with ADD/H were
hypothesized to have input difficulties related to their
attention deficits, while ADD/WO children were believed to
have output problems related to their slower rate of
cognition, and deficits in automatized information
processing similar to those of children with learning
disabilities. Support for this view came from findings that
children with ADD/H were impaired on tests of sustained
attention and behavioral inhibition, while children with
ADD/WO had deficits in focused attention and slowed
cognition (Barkley, DuPaul, & McMurray, 1990). These
authors reported differences between the two subtypes in the
performance of several tasks. ADD/WO children were found to
have significantly more difficulty than ADD/H children on
the WISC-R Coding subtest and on tests of long-term verbal
memory. Children with ADD/WO demonstrated lower levels of

16
off-task behaviors and less impulsivity during a vigilance
task, but their overall performance was similar to that of
children with ADD/H (Barkley, DuPaul, & McMurray, 1990).
Neuropsychological tests of fine motor speed, planning,
sequencing, and problem solving did not distinguish ADHD
subgroups in a study by Barkley, Grodzinsky, and DuPaul
(1992) or more recently in research by Barkley and
Grodzinsky (1994).
Overall, research has indicated that of the DSM-IV
subtypes, ADHD-Combined and ADHD-Primarily Inattentive have
sufficient empirical support. The evidence for the third
subtype, ADHD-Primarily Hyperactive/Impulsive, was not as
strong and the basis for this diagnosis was not clear. It
is the combination of motor hyperactivity and attentional
components that makes the children with ADHD-Combined type
of interest to the current study. Further references to
children with ADHD will include only this group of children.
The different cognitive style of children with ADD/WO may
introduce confounds into a study of motor learning and they
will be excluded from the current study.

17
Characteristics of ADHD
Sex Differences in Children with ADHD
Sex differences in the behavior of ADHD children have
generally not been supported by research (Breen, 1989),
although some behavioral and cognitive differences have been
found (Berry, Shaywitz, & Shaywitz, 1985). Boys with ADHD
were more aggressive and harder to control at school,
perhaps resulting in a higher rate of referral to clinics
than girls with ADHD (Berry, Shaywitz, & Shaywitz, 1985).
Girls with ADHD demonstrated significantly fewer aggressive
and disruptive behaviors, but significantly more cognitive
deficits and a higher likelihood of rejection by peers than
boys with ADHD (Berry, Shaywitz, & Shaywitz, 1985) . Verbal
IQ was significantly lower in girls with ADHD and they were
rated as having more language difficulties than boys. No
significant sex differences were found in attention,
hyperactivity, or impulsivity, and the overall behavioral
profile for both ADHD boys and girls was similar. These
results suggested that, because of their less disruptive
behavior, girls with ADHD who do not have other academic or

18
psychiatric problems remain unreferred, and their needs
often remain unmet (Berry, Shaywitz, & Shaywitz, 1985).
Similar attention and behavioral profiles in boys and
girls with ADHD have been supported in the research (Breen,
1989). Boys and girls with ADHD were rated as more
disruptive than controls in a controlled academic setting,
but there were no significant differences in behavior
between boys and girls with ADHD (Breen, 1989). Consistent
with Berry, Shaywitz, and Shaywitz (1985), the severity of
disruptive behaviors exhibited by girls with ADHD in a
controlled parent-child interaction was not significantly
worse than normal controls nor significantly better than
boys with ADHD. Both boys and girls with ADHD were rated by
teachers as having more externalizing behaviors than
controls and had similar difficulties on a vigilance task.
This indicated that both boys and girls with ADHD have
significant difficulties in sustained attention (Breen,
1989). No contrasts were found on measures of overall
cognitive ability. Breen (1989) interpreted these results
as supporting the similarity of ADHD symptoms in boys and
girls.

Developmental Problems Reported
in Children with ADHD
19
Children with ADHD have presented with a number of
developmental problems such as delays in learning to talk,
and speech and language dysfunction (Szatmari, Offord, &
Boyle, 1989b; Barkley, DuPaul & McMurray, 1990). The speech
and language problems manifested by children with ADHD can
become serious enough to require later referral for speech
and language therapy (Cantwell & Baker, 1992) . As infants,
children with ADHD may have difficulty in establishing
regular sleeping and eating schedules (Hartsough & Lambert,
1985). They have been found to be significantly more
restless and overactive as infants and may be more
persistent in their demands (Barkley, DuPaul, & McMurray,
1990).
Early motor difficulties and later coordination
problems are common in children with ADHD. They crawl at a
significantly later age compared with normal controls
(Hartsough & Lambert, 1985). Children with ADHD have been
found to be delayed in learning to walk and are reported by
parents to be clumsy as children (Szatmari, Offord, & Boyle,
1989b; Mitchell, Aman, Turbott, & Manku, 1987). Although

20
his review noted that research results conflict, Barkley
(1990) stated that up to 52% of children with ADHD may have
poor motor coordination, especially with fine motor skills.
In addition, children with ADHD have been shown to have
difficulties reproducing sequential hand movements (Breen,
1989). Compared with both normal controls and children with
learning disabilities, children with ADHD are significantly
more likely to be described as having poor coordination
(Barkley, DuPaul, & McMurray, 1990).
Accidents and Injury Risk in
Children with ADHD
The impulsivity and aggressiveness of ADHD children may
lead them to engage in physically dangerous activities
(Barkley, 1990). Children with ADHD recognized dangerous
situations as well as controls. Nonetheless, they rated
themselves as more likely to engage in hazardous activities
than did normal controls and underestimated the potential
severity of injuries (Farmer & Peterson, 1995). They also
generated fewer avoidance behaviors, suggesting a lack of
knowledge about safety rules (Farmer & Peterson, 1995).
Fractures and accidental poisonings are common among

21
children with ADHD (Szatmari, Offord, & Boyle, 1989b).
Children with ADHD frequently suffer four or more serious
accidents during childhood, and these may include head, eye,
and tooth injuries (Hartsough & Lambert, 1985) . Although
this characteristic of ADHD can be quite problematic for
caregivers, many of these accidents may be preventable if
parents are aware of the need for extra precautions
(Szatmari, Offord, & Boyle, 1989b).
Health Problems in Children with ADHD
and Their Mothers
Chronic health problems in infancy and childhood have
also been associated with ADHD (Hartsough & Lambert, 1985) .
Controlling for medication prescribed to treat ADHD
symptoms, children with ADHD are prescribed medication
significantly more often than normal controls (Szatmari,
Offord, & Boyle, 1989b). Asthma, allergies, and ear
infections have all been found in ADHD children at a higher
rate than in normal controls (Hartsough & Lambert, 1985).
Barkley (1990) noted that minor physical anomalies, such as
increased head circumference, eyes placed farther apart than

22
normal, and fine hair are all significantly more common in
children with ADHD than in normal controls.
Mixed evidence exists concerning the influence of
maternal health and pre- and perinatal factors on the
incidence of ADHD. Poor maternal health, toxemia or
eclampsia during pregnancy, and a maternal age younger than
twenty were found to differentiate mothers of ADHD children
from mothers of normal controls (Hartsough & Lambert, 1985).
Significantly longer labor and later gestational age were
also correlated with ADHD in the child. Another study
(Barkley, DuPaul, & McMurray, 1990) found evidence for none
of these factors. Low birth weight was found to be
correlated with ADHD by Szatmari, Offord, and Boyle (1989b)
and Mitchell, Aman, Turbott, and Manku (1987), but was not
found to be significant by Hartsough and Lambert (1985) or
Barkley, DuPaul, and McMurray (1990) . Research on the
effect of fetal distress at birth has also produced
contradictory findings, with some research indicating a
significant correlation with ADHD (Hartsough & Lambert,
1985), while others do not (Barkley, DuPaul, & McMurray,
1990). The existence of difficulties in toilet training has
also been disputed by investigators. Nevertheless, it

23
seemed that these problems are present in some ADHD children
and may be significantly more common than in children
without ADHD (Hartsough & Lambert, 1985) .
Comorbid Psychiatric Diagnoses
in Children with ADHD
Hyperactivity is closely related to other disruptive
behavior disorders, as research has found that 40% to 60% of
children with ADHD have been found to have a comorbid
conduct disorder (Szatmari, Offord, & Boyle, 1989a; Barkley,
Fischer, Edelbrock, & Smallish, 1990). The Conduct Disorder
and Attention Problem subscales of the Revised Behavior
Problem Checklist (RBPC) had a shared variance of between 20
and 31 percent (Quay & Peterson, 1983) . In addition there
were high correlations between attention-deficit and
antisocial behavior factors on both the Conners Teacher
Rating Scale (TRS) and the original Behavior Problem
Checklist (BPC; Arnold, Barneby, & Smeltzer, 1981). These
correlations emerged when these authors factor-analyzed
items from these scales, treating all 93 items as if they
constituted a single measure. The hyperkinetic factor on
the two scales correlated at r = .86, supporting the

24
criteria used for measuring hyperactivity (Arnold, Barneby,
& Smeltzer, 1981). The hyperkinetic factor on the TRS and
RBPC had correlations of between .69 and .77 with the
rebellious unsocialized and antisocial immature factors on
the TRS, indicating significant overlap between disruptive
behavior disorders (Arnold, Barneby, and Smeltzer, 1981).
Despite the high correlations between ADHD and other
disruptive behavior disorders, evidence supported ADHD as a
distinct diagnosis (Blouin, Conners, Seidel, & Blouin,
1989). Comparisons between groups of clinically referred
children have shown that inattention and impulsivity
separate ADHD children from conduct disordered or anxious
children (Halperin et al, 1993). The codiagnosis of
oppositional or conduct disorder is often given to children
with ADHD when they respond to conflicts in structured
situations with violations of major rules and laws (Barkley,
1990; Wells & Forehand, 1985). Comorbid conduct disorder
was associated with increased cigarette, alcohol, and
marijuana use in children with ADHD compared to controls
(Barkley, Fischer, Edelbrock, & Smallish, 1990) .
Children with ADHD are also frequently diagnosed with a
comorbid mood disorder, such as depression or bipolar

25
disorder (Szatmari, Offord, & Boyle, 1989a). Attention
difficulties and psychomotor disturbances are overlapping
symptoms that may cause difficulty in making a differential
diagnosis between ADHD and a mood disorder (Milberger et
al., 1995). However, research has indicated that between 90
and 100 percent of children retain the diagnosis of ADHD
after controlling for this overlap (Milberger, et al.,
1995). This suggested that ADHD can be distinguished from
comorbid mood disorders and that treatment plans should
consider all comorbid diagnoses (Milberger et al., 1995).
Learning Problems in children with adhd
Children with ADHD are difficult for both parents and
teachers to control because of their inability to stay on
task, failure to follow instructions, and distractibility.
In addition, children with ADHD were rated by teachers as
displaying significantly more aggressive behaviors than
normal controls (Barkley, DuPaul & McMurray, 1990) . Mild
ADHD symptoms in the home can become extremely problematic
in the structured environment of the classroom, and teachers
are likely to be the first to recognize ADHD in a child
(Szatmari, Offord, & Boyle, 1989a). Teachers often have

26
more experience in evaluating behaviors and deciding whether
or not they are age-appropriate, and they observe the impact
of a child's disruptive behavior (Simeon & Wiggins, 1993).
Disruptive classroom behaviors were coupled with
academic difficulties in children with ADHD, as they were
more likely than normal controls to have been held back in
school, placed in special education, or received tutoring
(Barkley, DuPaul & McMurray, 1990; Faraone et al., 1993).
Compared to the proportion of variance accounted for by
symptoms of ADHD alone, comorbid conduct disorders had
little additive effect on problems in school, although they
increased the risk of dropping out of school in adolescence
(Barkley, Fischer, Edelbrock, & Smallish, 1990). The
independent effect of ADHD symptoms was related to their
adverse impact on academic performance and the correlation
of these symptoms with cognitive deficits (Barkley, Fischer,
Edelbrock, & Smallish, 1990; Faraone et al., 1993).
There is a highly significant association between ADHD
and developmental learning disabilities (Cantwell & Baker,
1991), but the meaning of this association has been disputed
(McGee & Share, 1988) . In a review of the literature
related to ADHD and academic difficulties, McGee and Share

27
(1988) downplayed organic or environmental common causes of
the disorders. Instead, they defined ADHD as a conduct
problem resulting from the learning disabled child's
inability to understand academic material (McGee & Share,
1988). Children with comorbid ADHD and reading disabilities
have been found to exhibit processing difficulties similar
to non-ADHD children with reading disabilities (Pennington,
Groisser, & Welsh, 1993). This finding appeared to support
the idea that academic difficulties are a causal factor in
some children diagnosed with both ADHD and LD.
Although children with learning disabilities have been
rated by their teachers as showing evidence of attention
problems (Barkley & Grodzinsky, 1994), the conclusion that
academic frustration is the primary causative factor in ADHD
is problematic. A dissociation has been found between the
symptoms of primary ADHD and those of reading disabilities
(Pennington, Groisser, & Welsh, 1993), and the link between
learning problems and ADHD often begins well before the
child enters school (Hinshaw, 1992). Inconsistent
definitions of both ADHD and learning disabilities have been
used in the research (Semrud-Clikeman et al., 1992) and
while learning disabilities may contribute to disruptive

28
behaviors, they are not necessarily causative of ADHD. For
example, the ADHD/LD children in the Pennington, Groisser,
and Welsh (1993) study displayed significant conduct
problems in addition to attention deficits. The children
with ADHD/LD also had significantly higher rates of family
instability and this combined with academic failure, rather
than a primary ADHD, may have led to disruptive behavior in
some of these children (Pennington, Groisser, & Welsh,
1993) .
Further evidence against the causative link between
learning disabilities and ADHD was provided by findings that
preschoolers with ADHD have difficulties with independent
work and following rules in a structured setting
(Alessandri, 1992). Developmental problems related to ADHD
may cause cognitive impairments that lead to academic
difficulties, even when there is no co-occurring learning
disability diagnosis (Szatmari, Offord, & Boyle, 1989b).
Symptoms of ADHD are often present before 4 years of age
(Barkley, Fischer, Edelbrock, & Smallish, 1990) and academic
problems were linked to pre-existing impulsivity and
inattention in children with ADHD (Barkley,1990). Prior to
enrollment in school, or even if enrolled in preschool, a

29
child would be unlikely to experience the levels of academic
frustration described by McGee and Share (1988). Each child
should be evaluated independently and interventions should
be directed at the primary deficit (McGee & Share, 1988), as
comorbidity between learning disabilities and ADHD resulted
in greater learning problems than ADHD alone (Kataria, Hall,
Wong, & Keys, 1992).
As noted above, past comorbidity studies used
inconsistent criteria for defining learning disabilities,
resulting in considerably different conclusions (Semrud-
Clikeman et al., 1992). Children with ADHD are at
significant risk for school failure, and remediation of
academic deficits may be as important as treatment of
disruptive behaviors (Hinshaw, 1992). Research suggested
that, regardless of learning disability, children with ADHD
are more likely to be placed in a classroom for children
with disruptive behaviors, perhaps making them less likely
to receive academic remediation (Barkley, DuPaul, &
McMurray, 1990). Inconsistent criteria for defining
learning disabilities in the literature ranged from labeling
any academic deficit as a learning disability to extremely
stringent criteria limiting learning disabilities to those

30
children who scored in the borderline range on achievement
tests (Hinshaw, 1992). Shifting criteria may lead either to
overly inclusive and expensive academic interventions for
all children with academic deficits, or to a failure to
provide children with ADHD academic remediation because
their disruptive behavior prompts teachers to ignore
learning problems (Semrud-Clikeman et al., 1992). A
comparison of three increasingly exclusive definitions of
learning disability indicated that the moderate definition
of learning disability, provided for under Public Law 94-
142, was effective in correctly classifying children with
comorbid diagnoses (Semrud-Clikeman et al., 1992). Under
criteria for Public Law 94-142, children with ADHD were
shown to have significantly higher rates of both reading and
arithmetic learning disabilities compared to normal
controls, suggesting that careful academic screening of
these children is necessary (Semrud-Clikeman et al., 1992).
The impact of oppositional and conduct problem
behaviors on early academic difficulties is often
exacerbated by the presence of ADHD and attention deficits
increase the difficulty of remediation (Hinshaw, 1992). The
combination of ADHD with conduct disorder greatly increases

31
the risk of suspension, expulsion, dropping out of school,
and the development of adolescent delinquency (Barkley,
Fischer, Edelbrock, & Smallish, 1989; Hinshaw, 1992) .
Academic remediation or behavior modification alone may
ameliorate disruptive behavior (McGee and Share, 1988), but
simultaneous treatment of academic and behavior problems has
been found to be more effective for children with ADHD/LD
(Hinshaw, 1992) .
Social Relationships of Children with ADHD
Interpersonal relationships, whether with adults or
other children, have been found to be problematic for
children with ADHD (Szatmari, Offord, & Boyle, 1989b) and
rejection by peers is common (Barkley, 1990) . In
interactions with adults, children with ADHD had significant
rates of noncompliance when asked to complete a task, and
they often did not finish assigned tasks (Alessandri, 1992) .
In return, teachers disciplined children with ADHD more
frequently than they disciplined their non-ADHD counterparts
(Alessandri, 1992) .
Preschoolers with ADHD were shown to have patterns of
social interaction and play that differed significantly from

32
normal controls (Alessandri, 1992). Preschoolers with ADHD
were less creative and developmentally advanced in their
play. They played alone more often than control children
and had significantly fewer conversations with peers. In
group situations, ADHD children failed to understand social
rules, became overstimulated, and lost control of their
behavior (Berry, Shaywitz, & Shaywitz, 1985). Peer
rejection likely has an increasingly negatively impact on a
child's self-esteem, leading to a higher frequency of
disruptive behaviors in older children with ADHD
(Alessandri, 1992).
The combination of ADHD and LD significantly increases
the risk for social rejection (Flicek, 1992). Peer
nomination identified ADHD children as disruptive, while LD
children were seen as having low peer popularity and few
leadership skills. The group of combined ADHD/LD children
was rejected by, and fought with, peers significantly more
often than normal controls, a finding that was not repeated
in the ADHD-only or LD-only groups (Flicek, 1992) . Although
ADHD alone did not result in significant social rejection,
these children were rated as more disruptive. Children with
ADHD/LD may combine aggressive, disruptive ADHD symptoms

33
with deficient cognitive processing and incorrectly view
their peers as hostile and rejecting in all situations
(Flicek, 1992). This perception may lead to increased
conflict with, and rejection by, peers. Evaluations of
social problems may lead to more effective interventions if
they include both cognitive and behavioral factors (Flicek,
1992) .
Long-Term Outcome of Children with ADHD
Studies have indicated that up to 80% of children
diagnosed with ADHD continue to show salient characteristics
of the disorder well into adolescence (Barkley, Fischer,
Edelbrock, and Smallish, 1990) . Adolescents with ADHD were
significantly more likely than normal controls to have a
comorbid conduct disorder (Barkley, Fischer, Edelbrock, &
Smallish, 1990) . Consistent with this, adolescents with
ADHD were more likely to have been involved in antisocial
activities, including theft, assault, and destruction of
others' property (Barkley, Fischer, Edelbrock, & Smallish,
1990) . Adolescents with ADHD were somewhat more likely to
have been in auto accidents than control subjects, but the
risk was not significantly higher. Adolescents with

34
comorbid ADHD and conduct disorder were at significantly
greater risk for substance abuse (Barkley, Fischer,
Edelbrock, & Smallish, 1990) .
Symptoms of ADHD may manifest themselves in college
students as poor study skills and learning difficulties, and
students with previously undiagnosed ADHD may feel that they
are not working up to their potential (Heiligenstein &
Keeling, 1995). Although college students with ADHD may
have developed compensatory strategies, they still have
noticeable problems in sustained attention (Heiligenstein &
Keeling, 1995) . College students with a childhood diagnosis
of ADHD demonstrated poor concentration on a 20-minute
letter cancellation task (Shaw & Giambra, 1993) . When
compared to control groups that included both normals and
students who reported some childhood ADHD symptoms, students
with ADHD reported more spontaneous thoughts unrelated to
the task, and were impulsive in their responses to the task.
The results suggested that symptoms of ADHD do not always
disappear with age, and adults with ADHD continue to have
poor modulation of internal processes, especially when bored
(Shaw Sc Giambra, 1993; Douglas, 1984). In an attempt to
relieve boredom and achieve an optimal level of stimulation,

35
regulatory mechanisms in students with ADHD fail to screen
spontaneous, unrelated thoughts (Douglas, 1983) . These
thoughts then disrupt concentration and make completion of
experimental tasks or academic work more difficult (Shaw &
Giambra, 1993) .
Although the continuation of ADHD symptoms into
adulthood has been a controversial subject, several studies
have provided evidence supporting adult ADHD (Mannuzza et
al. , 1993; Biederman et al., 1993) . Symptoms of ADHD have
been found to persist in at least 11% of subjects with a
childhood diagnosis of the disorder, a figure that the
authors believed to be an underestimate (Mannuzza et al.,
1993). The educational attainment and socioeconomic status
of adults with ADHD was significantly lower than achieved by
controls (Mannuzza et al., 1993; Biederman et al., 1993).
Although comorbid psychiatric diagnoses played some role in
adult educational and occupational status, history of ADHD
appeared to have a unique impact (Mannuzza et al., 1993).
Most adults who had been diagnosed as ADHD in childhood were
employed, but few held professional positions and compared
to controls, a greater proportion owned their own
businesses, perhaps to compensate for an inability to

36
conform to regular schedules and rules set by others
(Mannuzza et al., 1993). Compared to normal controls, a
greater percentage of adults with ADHD were diagnosed with a
comorbid psychiatric disorder, most commonly antisocial
personality disorder (Biederman et al., 1993) . Similar to
the findings for educational and occupational status, adults
with uncomplicated ADHD were at greater risk for substance
abuse than controls (Mannuzza et al., 1993; Biederman et
al., 1995). Comorbid antisocial personality disorder added
greatly to this risk (Biederman et al., 1995) .
Family Characteristics
Family and household variables, including urban
residence, family receiving public assistance, single parent
as head of household, and inadequate family functioning are
all significantly correlated with ADHD (Szatmari, Offord, &
Boyle, 1989b). In addition to these variables, children
with ADHD experience frequent changes in residence compared
to control children (Barkley, Fischer, Edelbrock, &
Smallish, 1990). Parents of children with ADHD have a
significantly greater incidence of psychiatric diagnoses

37
than parents of children with developmental delays (Roizen
et al., 1996).
Fathers of children with ADHD were reported to have
high rates of antisocial behavior and frequent changes in
employment (Barkley, Fischer, Edelbrock, & Smallish, 1990).
For example, fathers of children with ADHD engaged in
significantly more childhood antisocial behaviors and 11.2%
of these fathers were diagnosed as having antisocial
personality disorder, while only 1.6% of the fathers of
normal controls received this diagnosis. Fathers of
children with comorbid ADHD and conduct disorder had
somewhat higher rates of antisocial behaviors than fathers
of children with uncomplicated ADHD. However, this
difference did not reach significance, which indicated that
antisocial behavior in the father is an important correlate
of uncomplicated ADHD. Psychopathology in fathers of
children with ADHD may render the father ineffective as a
parent and produce an unstable environment for the child,
negatively impacting the child's behavior (Barkley, Fischer,
Edelbrock, & Smallish, 1990). Mothers of children with ADHD
have been found to be younger, less educated, and had a
higher rate of separation and divorce than mothers of

38
control children (Barkley, Fischer, Edelbrock, & Smallish,
1990) . Married mothers of children with ADHD rated their
marriages as less satisfying than mothers of control
children (Barkley, Fischer, Edelbrock, & Smallish, 1991).
Family conflict was significantly more frequent in the
lives of children with ADHD than in children without
attention problems (Barkley, Fischer, Edelbrock, & Smallish,
1991). Mothers of ADHD children rated their family
environment as extremely stressful, with the impulsivity and
hyperactivity of the child playing an important role in
exacerbating this stress (Anastopoulos, Guevremont, Shelton,
& DuPaul, 1992). Aggressiveness in a child with ADHD added
to this stress, and comorbid oppositional-defiant disorder
led to higher levels of parenting stress than ADHD alone.
Health problems in childhood, often a characteristic of ADHD
(Hartsough & Lambert, 1985), was the final child-related
stressor identified in parents of children with ADHD
(Anastopoulos, Guevremont, Shelton, & DuPaul, 1992). These
findings were similar to parent ratings of the behavior of
adolescents with ADHD, who continue to have conflicts with
family members (Barkley, Fischer, Edelbrock, & Smallish,
1991). Although ADHD symptoms appeared to have an

39
independent contribution, comorbid oppositional-defiant or
conduct disorders made a significant contribution to family
conflicts (Anastopoulos, Guevremont, Shelton, & DuPaul,
1992).
Observed interactions between children with ADHD and
their mothers provided evidence that, in a neutral
situation, children with ADHD used a more negative
conversational style than controls (Barkley, Fischer,
Edelbrock, & Smallish, 1991). Mothers of children with
comorbid Oppositional-Defiant Disorder (ODD) and ADHD used
more commands and put-downs than mothers of normal controls
or of children with uncomplicated ADHD (Barkley, Fischer,
Edelbrock, & Smallish, 1991). Mothers of children with
comorbid ADHD/ODD also reported significantly more
subjective stress than mothers of children with
uncomplicated ADHD (Anastopoulos, Guevremont, Shelton, &
DuPaul, 1992). Symptoms of depression, anxiety,
somatization, and hostility were all found in the mothers of
aggressive ADHD children (Barkley, Fischer, Edelbrock, &
Smallish, 1991). Maternal psychopathology and increased
subjective stress may interact with the negative behavior of
the child to produce parent-child conflict (Anastopoulos,

40
Guevremont, Shelton, & DuPaul, 1992), while a positive
maternal style may avoid this outcome (Barkley, Fischer,
Edelbrock, & Smallish, 1991). As the interactions between
ADHD children and their parents are likely to remain stable
over time, early intervention is necessary to reduce or
avoid the development of oppositional symptoms (Barkley,
Fischer, Edelbrock, & Smallish, 1991) .
Heritabilitv of ADHD
Research has indicated that genetic factors make a
significant contribution to ADHD (Biederman et al., 1990).
Relatives of ADHD children were more likely to be diagnosed
with ADHD than are relatives of either normal or psychiatric
controls (Biederman et al., 1990). Antisocial personality
and mood disorders were also much more common among
relatives of ADHD children than in the control groups.
Consistent with the usual pattern of ADHD, male relatives
were given a diagnosis of ADHD more often than female
relatives, although the increased risk for ADHD compared to
controls occurred without regard to the sex of the relative.
Forty-four percent of the fathers and 19% of the mothers of
ADHD children met diagnostic criteria for ADHD,

41
significantly higher percentages than in control groups.
Siblings, and especially brothers, of children with ADHD
often had a diagnosis of ADHD (Biederman et al., 1990).
After controlling for socioeconomic status and
intactness of the family, relatives of children with ADHD
children were still significantly more likely than controls
to have a diagnosis of attention deficit disorder (Biederman
et al., 1990). However, these factors also increased the
risk for ADHD in the families of control groups, suggesting
that environmental factors do impact the development of ADHD
symptoms (Biederman et al., 1990). The high rates of
attention problems and increased risk for antisocial
behaviors in fathers of children with ADHD may explain the
high rates of separation and divorce in the homes of these
children (Barkley, Fischer, Edelbrock, & Smallish, 1991).
The heritability of ADHD was supported by twin studies.
Concordance rates for ADHD dizygotic twins are significantly
higher than those for monozygotic twins (Gillis, Gilger,
Pennington, & DeFries, 1992). This finding was stable for
both sexes, strengthening the hypothesis of ADHD
heritability. This study used reading-disabled twins, so it
was possible the findings were influenced by the

42
heritability of learning disabilities, but the authors noted
that the finding of ADHD heritability appeared robust.
Concordance results did not appear to be a result of the
parents confusing the behavior of identical twins (Gillis,
Gilger, Pennington, & DeFries, 1992) . However, despite
evidence of a genetic component to ADHD, no research to date
has found a direct link with a particular gene (Alessi,
Hottois, & Coates, 1993). The discovery of a rare thyroid
condition was correlated with ADHD and directly linked with
a particular gene suggested that this gene may be identified
in the future (Alessi, Hottois, & Coates, 1993).
Nonetheless, no evidence has supported the linkage of all
forms of ADHD to a thyroid condition.
Assessment and Treatment
A variety of techniques are used to evaluate attention
deficits in children. Parent and teacher reports are often
used in the assessment of the behavioral aspects of ADHD.
Two of the most commonly used behavior checklists are the
Conners rating scales (Goyette, Conners, & Ulrich, 1978) and
the Child Behavior Checklist (CBCL - Achenbach, 1991).
These rating scales have both parent and teacher forms in

43
order to fully evaluate a child's behavior. Checklists
require raters to report frequencies of various problem
behaviors in children and these ratings are then combined to
produce a profile of the child's behavior. The Conners
rating scales have been shown to be a valid measure of
hyperactive and inattentive behaviors (Trites, Blouin, &
Laprade, 1982). Children with ADHD tended to score highly
on the Externalizing Behaviors scale of the CBCL (Barkley,
1990) because of their overactivity and disruptive
behaviors.
It has been hypothesized that deficits in self¬
regulation underlie the symptoms of ADHD (Douglas, 1983).
Poor self-regulation can be defined by four behavioral
components characteristic of children with ADHD (Douglas,
1984). An unusual need for immediate gratification, an
unwillingness to invest effort in demanding tasks, an
inability to inhibit impulsive responses, and a lack of
arousal modulation have all been found in children with
ADHD. The lack of self-regulation in ADHD children has a
number of effects on behavior. These children fail to
utilize knowledge and skills they are known to possess, an
inconsistency in performance often noted by teachers

44
(Barkley, 1990). Compared to normal children, they are
inefficient in their management of resources, and so they
have difficulty completing tasks even if well motivated
(Douglas, 1984). Self-regulation deficits may cause
deficiencies in sustained attention unrelated to increased
responsiveness to extraneous stimuli (Douglas, 1983). In
addition to impulsive responses to environmental changes,
children with ADHD have problems maintaining attention for
any task (Douglas, 1983) .
Sustained attention in ADHD children is commonly
assessed using vigilance tasks such as the Continuous
Performance Test (CPT; Corkum & Siegel, 1993), which
measures sustained attention for infrequent events. During
the CPT, a series of numbers or letters are presented and
the child's goal is to identify the target number/letter or
number/letter sequence. Performance on the CPT can be
influenced by variables related to the task itself, such as
longer intervals between stimuli and the length of time that
the stimulus is displayed (Corkum & Siegel, 1993). When
task difficulty was increased, children with ADHD were
increasingly separated from normal children on performance
measures (Corkum & Siegel, 1993). Children with ADHD became

45
less careful in responding to a CPT task over the course of
the test, suggesting that impairment in sustained attention
is at least partially responsible for ADHD symptoms (Power,
1992). However, if the vigilance task used was designed for
assessment of seriously impaired patients, children with
ADHD may perform at the same level as normal children
(Zametkin et al, 1990). Use of stimulant medication can
alter the performance of an ADHD child on the CPT (Corkum &
Siegel, 1993), as can the presence or absence of an examiner
(Power, 1992). The negative effect of an examiner's absence
was frequently seen in children with ADHD who had strong
hyperactive or aggressive features, who are most prone to
act up when adult supervision is removed (Power, 1992).
It has been argued that deficits in physiological
arousal, rather than problems in sustained attention, are
primarily responsible for ADHD symptoms (Corkum & Siegel,
1993). Physiologically-based underarousal was found in
patients with other disorders of sustained alertness
(Weinberg & Harper, 1993). The concept of physiological
arousal deficits is controversial, however, as children with
attention deficits may become overaroused in some
situations, especially those involving a highly desired

46
reward (Douglas, 1983). Specific tasks, especially
experimental tests of attention, may not be interesting to
children with ADHD, leading to the appearance of low arousal
(Douglas, 1984). These same children may overreact when the
stimulus is interesting, suggesting that the true deficit is
in modulating their level of arousal. In order to more
fully define the underlying deficits of ADHD, the components
of vigilance need to be analyzed separately (Corkum &
Siegel, 1993) .
Pharmacological Treatment of ADHD
Methylphenidate (Ritalin) is one of the most common
psychostimulants used for treatment of children with ADHD
(Barkley, 1990), and up to 77% of children who are placed on
Ritalin experience improvement in behavior (Murray, 1987).
Ritalin is a dopamine agonist, as are its companion
medications, Dexedrine (d-amphetamine) and Cylert (pemoline)
(Murray, 1987). Dopamine and other catecholamines are
believed to be involved in the control of attention (Hynd,
Voeller, Hern, & Marshall, 1991) and most children with ADHD
respond positively to these drugs (DuPaul, Barkley, &
McMurray, 1991). Ritalin is generally believed to increase

47
abnormally low metabolic rates in the striatal and
periventricular regions of these children (Lou et al, 1989).
The other stimulant medications apparently have similar
effects, although Cylert has been found to be slightly less
effective in moderating the behavior of ADHD children
(Conners & Taylor, 1980). Cylert is slower to act than
Ritalin, often requiring 3 to 4 weeks to have a therapeutic
effect (Dulcan, 1985) and it has a longer half-life,
averaging 12 hours, as opposed to 2 to 3 hours for Ritalin
(DuPaul & Barkley, 1990). The behavioral effects of Ritalin
and Dexedrine last around 4 hours (Dulcan, 1985), while
these effects are seen for up to 2 weeks after ending
administration of Cylert (Conners & Taylor, 1980) . Ritalin
does not accumulate in the system (Dulcan, 1985), and no
traces of this drug are found in the urine after 12 hours
(DuPaul, Barkley, & McMurray, 1991). Slow-release forms of
Ritalin (methylphenidate SR) are commonly prescribed,
especially when administration of medication during the
school day (DuPaul, Barkley, & McMurray, 1991) or after¬
school behavior (Simeon & Wiggins, 1993) are concerns.
Slow-release forms of Ritalin have plasma half-lives ranging
from 2 to 6 hours and behavioral effects that last up to 8

48
hours (DuPaul & Barkley, 1990). However, slow-release
preparations may take significantly longer to affect
behavioral change following dose administration (DuPaul,
Barkley, & McMurray, 1991) and behavioral effects may not
last as long as with a small afternoon dose of normal-acting
Ritalin (Simeon & Wiggins, 1993).
Side effects of stimulant medication can include
decreased appetite, insomnia, anxiety, and irritability
(DuPaul, Barkley, & McMurray, 1991). An afternoon increase
in ADHD behaviors is also common in children with ADHD who
take medication during the day. The lack of normal growth
is frequently seen in children with ADHD who are taking
stimulant medication and Dexedrine has been found to have a
more deleterious effect on growth than other stimulants
(Dulcan, 1985) . Duration of treatment and amount of
appetite suppression appear to be important factors
affecting the child's growth, and this effect can be
modulated with drug holidays (Dulcan, 1985) . Development of
motor tics is a relatively rare side effect and it can
difficult to predict, but a family history of motor
syndromes is a contraindication to stimulant treatment. As
with any pharmacologic treatment, a careful history should

49
be taken before stimulant medication is prescribed (DuPaul,
Barkley, & McMurray, 1991) .
Antidepressants have also been found to be effective in
some ADHD children who are unresponsive to psychostimulants,
but their use should be closely monitored because of
potential side effects that may be more severe than those of
the stimulants (DuPaul, Barkley, & McMurray, 1991).
Research into the efficacy of fluoxetine (Prozac) indicated
that it may provide an alternative treatment for ADHD, with
less serious side effects than other antidepressants
(Barrickman et al., 1991).
Effects of Stimulant Medications
on Cognition and Behavior
Ritalin use has produced significant increases in
performance on arithmetic, paired-associate learning, and
complex word generation tasks, but not on a task measuring
spelling ability (Douglas, Barr, O'Neill, & Britton, 1986).
Children with ADHD were able to better focus on tasks and
use their time efficiently. Cylert produced similar
improvements in cognitive functioning and may actually be
somewhat more effective with tasks requiring visuomotor

50
planning and precision (Conners & Taylor, 1980). Improved
scores on word generation and paired-associate learning
indicated that stimulant medication does not effect only the
child's effort level, but also the ability to organize and
process material. Positive changes in the children's
behavior accompanied cognitive improvements, an indicator of
increased self-control. Stimulant medication appeared to
increase the ability of children with ADHD to maintain an
optimal level of cognitive effort (Douglas, Barr, O'Neill,
and Britton, 1986).
Dosage levels have been shown to affect both behavioral
and cognitive measures of ADHD (Douglas et al., 1988), and
there seems to be an optimal therapeutic dose, beyond which
there are diminishing returns (Rapport, Denney, DuPaul, &
Gardner, 1994). Improved performance of children with ADHD
on both simple reaction time and complex information¬
processing tasks was correlated with increased stimulant
dosage (Douglas et al., 1988). Academic and behavioral
improvements have also been reported on clinician and
teacher ratings (Rapport, Denney, DuPaul, & Gardner, 1994),
confirming earlier findings of improvement on parent
behavior ratings (Conners & Taylor, 1980). These findings

51
to support the hypothesis that in addition to improved
behavior and greater effort, stimulant medication increases
self-regulation in ADHD children (Douglas et al., 1988).
However, there appeared to be a limit to medication
efficacy. On paired-associate learning, improvement in
performance did not continue to increase with stimulant
dosage (Douglas et al., 1988), and children's academic
performance does not increase significantly with increasing
dosages (Rapport, Denney, DuPaul, & Gardner, 1994). These
results were consistent with the self-regulation hypothesis,
as children with ADHD were believed to have improved their
performance to the limit of their ability at moderate doses
of Ritalin (Douglas et al., 1988). At higher dosage levels,
ADHD children may begin to over-regulate themselves and they
become overly cautious in responding, resulting in decreased
performance. Although not all children responded positively
to the medication in all situations, the authors indicated
that every child displayed positive effects on several
measures. This called into question the practice of
evaluating a child's response to medication based on a
single measure (Douglas et al., 1988).

52
Cognitive problems may precede behavioral problems when
a child is responding adversely to medication (Swanson et
al., 1991). Medication may be overprescribed as clinicians
ignore negative cognitive reactions in favor of positive
changes in behavior (Swanson et al., 1991). In addition,
there appeared to be a subset of children with ADHD who
receive minimal benefit from medication, especially in
classroom situations (Rapport, Denney, DuPaul, & Gardner,
1994; DuPaul, Barkley, & McMurray, 1994). Using a paired-
associate task, approximately 30% of children with ADHD were
classified as having a negative cognitive response to
Ritalin, as measured by a quadratic response curve, a curve
most often seen in difficult tasks (Swanson et al., 1991).
Absolute doses of medication may also be more beneficial to
children than dosage based on weight, as learning curves
indicated that absolute doses provided stable improvement in
learning for children of various weights. Learning curves
revealed that heavier children may actually need less
medication than indicated by a standard weight-based
prescription (Swanson et al., 1991).
Although stimulant medication appeared to improve
academic performance in children with ADHD, questions remain

53
as to its effectiveness on other aspects of their behavior
(DuPaul, Barkley, & McMurray, 1994). Although Ritalin
significantly reduced inattention and impulsivity in a group
of children with comorbid ADHD and internalizing symptoms,
it did not significantly improve the academic functioning of
these children (DuPaul, Barkley, & McMurray, 1994). In
fact, the academic functioning of children with ADHD and a
relatively greater number of internalizing symptoms may
actually decline, although further research is needed to
confirm this result (DuPaul, Barkley, & McMurray, 1994).
Medication Effects on Social Skills
Social behaviors in ADHD children are affected by
medication in several ways (Whalen et al., 1989; Buhrmeister
et al., 1992). Unmedicated children with ADHD were
significantly more socially engaged than controls,
suggesting that these children need social stimulation
(Buhrmeister et al., 1992). These children face
difficulties because their social interactions are generally
considered aversive by other children (Berry, Shaywitz, &
Shaywitz, 1985). Ritalin use resulted in improved peer
ratings of children with ADHD, but these ratings were still

54
not as positive as those of a normal control group (Whalen
et al., 1989).
Even in situations that demand prosocial behaviors,
children with ADHD have difficulties, despite a desire to
perform well (Buhrmeister et al., 1992). Although children
with ADHD engaged in prosocial behaviors as frequently as
controls, they simultaneously emitted higher rates of
aversive behaviors (Buhrmeister et al., 1992). Medication
reduced the rate of all social behaviors and there was less
responsiveness to social cues, without any increase in
prosocial behaviors. Medicated children with ADHD were
noted to be sad and withdrawn, (Buhrmeister et al., 1992),
but this was disputed by other research (Whalen et al.,
1989). Sadness and withdrawal appeared to negatively affect
peer ratings of these children and indicated that
controlling aversive behavior with medication alone does not
necessarily lead to more positive interactions for ADHD
children (Buhrmeister et al., 1992). Relatively normal
rates of prosocial behavior in unmedicated children with
ADHD suggested that effective interventions are those
focused on reducing aversive behavior, rather than on
increasing prosocial behavior (Buhrmeister et al., 1992).

55
Behavioral and Combined Treatment Strategies
Treatment of ADHD often involves combining
psychostimulant medication with a behavioral modification
program and parent training (Simeon & Wiggins, 1993;
Barkley, 1983). Training for parents of children with ADHD
generally consists of teaching behavioral principles such as
positive reinforcement and time-out, and having parents
recognize their own contributions to the child's behavior
(Barkley, 1983). Behavioral methods are often directly
related to parent training and involve the application of
contingency management strategies both at home and in
school. The goal of behavior modification programs is to
help the child control his own behavior, but they may be
difficult to implement without concomitant medication
intervention and may be more costly in terms of time and
money (Barkley, 1983; Murray, 1987). Despite these
constraints, behavioral approaches may be useful for
children with ADHD who are not responsive to medication
(Murray, 1987).
The combination of stimulant medication and behavior
therapy improved the behavior of children with ADHD (Murray,

56
1987), but academic performance was enhanced only by
medication (Carlson, Pelham, Milich, & Dixon, 1992).
Medication also positively influenced the self-ratings of
children with ADHD. The singular effect of medication
indicated deficient self-regulation (Douglas, 1984), and
medication appeared to augment the self-regulatory system.
Behavior therapy alone was found to be as effective as a low
dose of Ritalin in controlling disruptive behavior, but it
did not increase positive self-ratings (Carlson, Pelham,
Milich, & Dixon, 1992). Feedback on the children's
behavior, as applied in this condition, may have helped
control their behavior, but negatively impacted self-
ratings. A combination of behavior therapy and low-dose
medication was as effective in effecting behavior change as
high-dose medication alone, suggesting that combined
treatments can reduce medication use (Carlson, Pelham,
Milich, & Dixon, 1992). The authors noted that between-
subject differences played a significant role in the
effectiveness of either treatment and should be considered
when designing an intervention program.

57
Effects of Incoordination on Children.with ADHD
Difficulty in motor skill learning may have a number of
effects on children with ADHD, both in school (learning to
write and draw) and among their peers (learning skills
required for games). Fewer children with ADHD participate
in organized athletics, possibly as a result of difficulties
in learning the necessary skills (Szatmari, Offord, & Boyle,
1989b). Children with ADHD have been found to experience
significant difficulties learning new motor skills and
adequately performing in sports or other activities
(Szatmari, Offord, & Boyle, 1989b). Despite findings of
developmental difficulties and poor coordination, motor
learning in children with ADHD is rarely researched. The
disruptive behavior of children with ADHD causes significant
stress for the parents and teachers of these children
(Anastapoulos, Guevremont, Shelton, & DuPaul, 1992). As a
result, most research concentrates on causes and treatment
of this behavior. Research into the motor skills learning
may open a new window on intervention with these children,
both academically and socially (Conners & Delamater, 1980) .
It may also provide further evidence of the processes used

58
by children with ADHD when they learn any novel skill
(Leavell, Ackerson, & Fischer, 1995) .

CHAPTER 2
CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD
The Impact of Right Hemisphere Dysfunction on ADHD
Research on the etiology of ADHD has focused on the
neurological basis for this disorder and on the possible
reasons for any brain dysfunction, as important differences
have been found in the neurology of children with ADHD
compared to control children (Barkley, 1990). Right
hemisphere abnormalities were found on CAT scans of nine of
fifteen children referred for behavioral and learning
problems, and all of these children met criteria for
attention deficit disorder (Voeller, 1986). These children
also had difficulties reading social cues and modulating the
cues they projected (Voeller, 1986). As a group, they were
withdrawn and isolated and did not respond well to
psychotherapy. Although the symptoms of these children are
similar in many ways to those of ADHD children, the
interpersonal problems of these children could not be
entirely attributed to attention deficits (Voeller, 1986).
59

60
Nevertheless, the finding that ADHD is closely correlated to
right hemisphere deficits is consistent with data concerning
symptoms of inattention and motor impersistence in adults
and children with right-sided brain injuries (Voeller &
Heilman, 1988a).
Consistent with other evidence of right hemisphere
dysfunction in children with ADHD, these children made
significantly more left-sided errors than normal controls on
a letter cancellation task (Voeller & Heilman, 1988a). The
authors carefully selected only subjects who met all DSM-III
criteria for attention deficit disorder and were not
children with a conduct disorder mislabeled as ADHD. The
children with ADHD also had subtle left-sided neurologic
signs and had problems sustaining voluntary movements, a
difficulty often seen in adults with right hemisphere injury
(Voeller & Heilman, 1988b).
Attentional functions such as focusing on a target and
then disengaging to refocus on the next target are believed
to reside in the right hemisphere (Voeller & Heilman,
1988a). Children with ADHD demonstrated deficits on tasks
requiring them to fixate on a stimulus, both with and
without distractions (Voeller & Heilman, 1988b). On a

61
covert visual orienting task, children with ADHD disengaged
significantly more quickly than normal control from invalid
cues in the left visual field, and more quickly than they
themselves disengaged from targets in the right visual field
(Carter et al., 1995). This suggested that children with
ADHD had difficulty in sustaining attention for any target
in the left visual field and provided supporting evidence
for an underlying right hemisphere deficit (Voeller &
Heilman, 1988a). Although factors other than neurologic
dysfunction influence the development of ADHD symptoms,
developmental abnormalities of, or injury to, the right
hemisphere and its attentional and motor control structures
seem to influence attentional deficits (Voeller & Heilman,
1988a; Carter et al., 1995).
Morphological Differences in Children with ADHD
Interhemispheric connections in ADHD children may
influence their ability to control of their behavior, but
the inconsistent results of morphology studies have
precluded any definite conclusions (Hynd et al., 1991;
Semrud-Clikeman et al., 1994). Morphometric analysis of the
genu, or most anterior portion of the corpus callosum,

62
indicated that it may be significantly smaller in children
with ADHD than in normal controls (Hynd et al., 1991), but
later studies using more sophisticated imaging equipment
contradicted this finding (Semrud-Clikeman et al., 1994).
The genu was smaller in children with ADHD who were
unresponsive to stimulant medication, but there were not
enough subjects for a statistical analysis (Semrud-Clikeman
et al. , 1994). The genu contains fibers connecting the
prefrontal, orbitofrontal, and premotor cortices, and
although measures of callosal size may not accurately
reflect the number of interhemispheric fibers, a smaller
genu may be responsible for disruption in motor control and
behavioral inhibition systems (Hynd et al., 1991).
Posterior sections of the corpus callosum, the splenium and
the area just anterior to it, were also found to be smaller
in children with ADHD (Hynd et al., 1991; Semrud-Clikeman et
al., 1994). This may explain the difficulties ADHD children
have in attending to sensory information (Semrud-Clikeman et
al., 1994), although other research has suggested that the
sensory areas in these children may be overactive (Lou et
al, 1989), rather than the reverse.

63
The caudate nucleus has been called the "head ganglion
of the habit system, " a designation that underlines its
importance in motor skill learning (Saint-Cyr, Taylor,
Trepanier, & Lang, 1992). This large subcortical nucleus
also influences behavioral responses to stimuli (Rolls Sc
Johnstone, 1992), suggesting that it is integrated into
attention systems (Lou, Henrikson, Sc Bruhn, 1990) . Children
with ADHD have been found to have a smaller left than right
caudate nucleus, the reverse of what is found in normal
controls, but had no significant differences in overall
brain size (Hynd et al., 1993). The lack of differences in
overall brain size indicated regional differences in
development, rather than variations in the brain as a whole
(Hynd et al., 1990). Abnormal asymmetries may result in a
bias for right-sided control mechanisms and the disruption
of subcortical control of attention, as neurotransmitter
systems favor the non-dominant hemisphere. As dominant
hemisphere controls on the motor systems are disrupted,
overactivity may result. Behavioral disinhibition in
children with ADHD may also be influenced by subcortical
neurotransmitter systems and their relationship to the
frontal lobes, especially the prefrontal cortex. Abnormal

64
caudate asymmetries may negatively impact the activation of
frontal lobe functions that rely on subcortical modulation,
with lowered behavioral control similar to that seen in
adult cases of frontal dysfunction (Hynd et al., 1993).
Cerebral Blood Flow in Children with ADHD
Studies of regional cerebral blood flow, from which a
structure's functional involvement in behavior can be
inferred, provided further evidence of subcortical
involvement in ADHD (Chugani, Phelps, & Mazziotta, 1987).
Children with ADHD had significantly lower levels of blood
flow in both the caudate nucleus (Lou et al., 1989) and
posterior periventricular areas (Lou, Henrikson, & Bruhn,
1990). Lesions in these subcortical areas caused attention
problems and motor hyperactivity in animal studies (Lou et
al., 1989). Interconnections between these structures and
the frontal lobes (Hynd et al., 1993) provided evidence that
deficiencies in subcortical metabolism are responsible for
poorly modulated activity in the prefrontal cortex (Lou,
Henrikson, and Bruhn, 1990). As noted above, these areas of
cortex are responsible for behavioral inhibition and have

65
also been implicated in the control of attention (Luria,
1973).
Cerebral blood flow changes in the sensory and
sensorimotor regions of cortex have been demonstrated in
children with ADHD (Lou et al., 1989) . Increases in blood
flow to the occipital lobe have been linked to an inability
to screen out irrelevant visual information (Lou,
Henrickson, & Bruhn, 1990). As other sensory cortices
demonstrated similar changes, it appears that there is a
lack of inhibitory control of sensory input, perhaps a
result of disrupted striatal connections to the thalamus
(Lou, Henrickson, & Bruhn, 1990). Consistent with the
hypothesis of deficient self-regulation (Douglas, 1983),
this may create difficulties for children with ADHD in
screening sensory input (Lou, Henrikson, & Bruhn, 1990).
Brain Metabolism in Children with ADHD
Glucose metabolism is the main source of energy for the
brain, so measurement of this process is another indicator
of the functional activity of brain structures (Chugani,
Phelps, & Mazziotta, 1987) . During performance of a simple
attention task, the left prefrontal area was significantly

66
less active in adolescents with ADHD than in normal
controls, (Zametkin et al., 1993). Metabolism in this area
had a significant negative correlation with the severity of
ADHD symptoms (Zametkin et al., 1993). Adolescents with
ADHD had significantly higher metabolic rates in a portion
of the left parietal lobe, a finding that may be consistent
with their sensory processing deficits (Lou, Henrickson, &
Bruhn, 1990). Although these findings contradicted evidence
of right frontal lobe involvement in ADHD, they
differentiated between adolescents with ADHD and controls in
the absence of overall differences in brain metabolism
(Zametkin et al., 1993).
Adults with a childhood history of ADHD did have a
lower rate of total brain metabolism than normal controls,
perhaps as a result of the disorder's effects on maturation
(Zametkin et al., 1990) . Adults with ADHD also had lower
metabolic rates in the somatosensory cortex (Zametkin et
al., 1990). Consistent with the findings in adolescents,
the greatest reduction in metabolic activity was found in
the left prefrontal regions of the adults with ADHD
(Zametkin et al., 1990).

67
The prefrontal regions of adults and children with ADHD
may deactivate when challenged with a simple attention task
(Amen, Paldi, & Thisted, 1993) . Children with ADHD who
failed to demonstrate reduced prefrontal activity during an
intellectual task already had a lower resting metabolic rate
in that area. Prefrontal cortex controls attention,
concentration, problem-solving abilities and judgment (Amen,
Paldi, Thisted, 1993). Planning and execution of motor
activities are also functions of this part of the brain
(Zametkin et al., 1990). It is possible that the motor
incoordination seen in ADHD children is a result of abnormal
functioning in the prefrontal areas and in the subcortical
structures connected to it.
Issues of Subject Selection
The outcome of morphological and physiological studies
may be influenced by the inclusion of children with ADHD and
a comorbid diagnosis, especially a learning disability.
Although the right frontal cortices of both ADHD and
dyslexic children were significantly smaller than in normal
controls, dyslexic children differed from ADHD children in
the size of other brain regions (Hynd et al., 1990) . The

68
length of the insular region was shorter bilaterally and the
posterior segment of Wernicke's area (planum temporale),
both areas involved in language, were smaller in dyslexics
than in normal children. Compared to children with ADHD and
normal controls, dyslexic children had a reversed pattern
(L was due to the smaller left planum (Hynd et al, 1990).
Subject selection may also influence the results of
regional cerebral blood flow and metabolic studies.
Zametkin et al. (1990) and Zametkin et al. (1993) did not
analyze the data from ADHD-LD and ADHD-only subjects
separately. In addition to the low striatal blood flow
characteristic of ADHD, subjects with ADHD and comorbid
neurological diagnoses had more extensive reductions in the
central regions of the brain (Lou et al, 1989). While there
are similarities in the neurobiology of ADHD and
developmental learning disabilities, there are also
important differences that may influence research results if
not controlled (Lou et al., 1989; Lou, Henrikson, & Bruhn,
1990) .

69
Neuropsychological Testing of Children with ADHD
Although frontal lobe dysfunction has long been
implicated in ADHD, formal testing of frontal lobe functions
produced inconsistent results (Barkley & Grodzinsky, 1994).
Some studies have found few differences between children
with ADHD and normal controls on tests of frontal lobe
functioning (Loge, Staton & Beatty, 1990), but this study
analyzed distractibility and vigilance tasks separately from
other tests of frontal lobe functioning. When those tests
were analyzed, it was concluded that ADHD children had
difficulty in directing and sustaining attention, a function
localized to the right parietal lobe (Posner, 1992).
However, subjects in this study may have had developmental
learning disabilities and parietal dysfunction unrelated to
their attention problems (Grodzinsky & Diamond, 1992).
Other authors indicated that symptoms of ADHD resemble
frontal lobe deficits, with subcortical involvement (Barkley
& Grodzinsky, 1994). Vigilance tests like the CPT are more
often used to measure frontal lobe function, rather than
parietal lobe function (Loge, Staton, & Beatty, 1990), in
children with ADHD, as inhibition and voluntary attention

70
are believed to be frontal lobe functions (Luria, 1973).
Impulsivity leads to errors of commission, while
inattentiveness leads to errors of omission (Grodzinsky &
Diamond, 1992). The deficient performances of children with
ADHD on vigilance tasks make these tests effective in
measuring the intensity of ADHD symptoms (Barkley &
Grodzinsky, 1994). Children with ADHD made errors of
commission significantly more often than children with
learning disabilities or normal controls and this measure
separated the performance of children with ADHD from normal
children (Barkley, & Grodzinsky, 1994; Seidman et al.,
1994). Adolescents with ADHD continued to have difficulty
with vigilance tasks, but were not more distractible than
normal controls, suggesting maturational effects (Fischer,
Barkley, Edelbrock, & Smallish, 1990).
Aside from the results of vigilance tasks, which were
fairly consistent across studies, tests of frontal lobe
functioning have produced mixed results in children with
ADHD. The Stroop Interference Task, which requires subjects
to name a stimulus while inhibiting a conflicting response,
differentiated children with ADHD from normal controls in
some studies (Grodzinsky & Diamond, 1992; Barkley,

71
Grodzinsky, & DuPaul, 1992), but in other studies the
performance difficulties of ADHD were not significant
(Barkley & Grodzinsky, 1994) . The Wisconsin Card Sorting
Test (WCST), a measure of problem solving ability, also does
not always reliably discriminate ADHD children from normal
controls (Grodzinsky & Diamond, 1992; Barkley & Grodzinsky,
1994), although ADHD children have been found to make more
perseverative and nonperseverative errors than normal
controls (Shue & Douglas, 1992; Seidman, et al., 1994) .
Normal children completed the first category faster than
children with ADHD (Grodzinsky & Diamond, 1992), and
children with ADHD completed fewer total categories (Shue &
Douglas, 1992). A review of studies with significant
results on the WCST indicated that they did not specifically
exclude children with learning disabilities (Grodzinsky &
Diamond, 1992), introducing a possible confound. Another
hypothesis is that these effects were age-related, with
younger children with ADHD performing significantly worse
than normal controls, while older children with ADHD
performed more normally (Fischer, Barkley, Edelbrock, &
Smallish, 1990). This hypothesis has not been confirmed and

72
the WCST has proved disappointing as a test of ADHD, even in
younger children (Barkley & Grodzinsky, 1994).
Children with ADHD had difficulty alternating responses
during sequencing tasks (Shue & Douglas, 1992), but even
when the difference was nonsignificant, normal children were
somewhat faster than children with ADHD (Grodzinsky &
Diamond, 1992). Tests of planning and organization also
produced mixed results (Grodzinsky & Diamond, 1992; Barkley
& Grodzinsky, 1994). Motor control difficulties in children
with ADHD are similar to deficits found in adults with
frontal lobe dysfunction (Shue & Douglas, 1992). Children
with ADHD had deficits inhibiting motor responses, made
impulsive errors in responding, and were echopraxic (Shue &
Douglas, 1992). Children with ADHD also had significantly
greater difficulty inhibiting memory-guided eye movements
compared to normal controls (Ross et al., 1994). These
results are consistent with what would be expected, given
abnormal asymmetry of the caudate nucleus and the subsequent
disruption of connections with the prefrontal lobes (Hynd et
al., 1993) .
Verbal fluency tests, especially those which require
generation of words to a target letter, were a useful

73
measure of frontal lobe functioning in children with ADHD
(Koziol & Stout, 1992). Significantly fewer words were
generated by groups of ADHD children compared to normal
controls (Koziol & Stout, 1992; Barkley & Grodzinsky, 1994).
Adolescents with ADHD did not show deficits on these tasks
(Fischer, Barkley, Edelbrock, & Smallish, 1990) . The
deficits in children were attributed to deficits in self¬
regulation (Koziol & Stout, 1992; Douglas, 1983), and an
inability to focus and sustain attention. These deficits
may be attributable to frontal lobe dysfunction, although
research on this as a definitive test of ADHD is not yet
conclusive (Barkley & Grodzinsky, 1994).
It is difficult to draw any solid conclusions about
frontal lobe functions in ADHD children at this time, as
most of the tests used were designed for adults and may not
translate well to children (Barkley, Grodzinsky, & DuPaul,
1992). In addition, frontal lobe measures may miss subtle
defects in functioning resulting from developmental factors,
as they were designed to measure the results of more severe
brain insults. Vigilance tasks, which were designed
specifically to measure the ADHD symptoms of attention and
impulsivity, were most effective in distinguishing ADHD

74
children from normal controls (Barkley & Grodzinsky, 1994).
A family history of ADHD may negatively impact the
performance of a child with ADHD on neuropsychological
tests, but comorbid diagnoses did not appear to have a
significant effect (Seidman et al., 1994).
Neuroanatomy of Attention
The primary factors in defining attention are the
ability to focus on environmental stimuli, sustain
attention, encode information, respond to stimuli, and shift
attention to new targets (Mirsky et al., 1991). These
factors are similar to those proposed by other
neuropsychological models of attention (Cohen, 1993). Cohen
(1993) noted that a weakness of this model is that it is
based on responses to traditional neuropsychological
measures and may not measure the impact of differences in
motivation and behavior. An alternate model of attention
includes sensory attention, attentional capacity, selection
and control of responses to stimulation, and sustained
attention (Cohen, 1993) . Children with ADHD were seen as
having impairments in most areas of attention, with
important exceptions. Their ability to focus on

75
environmental stimulation, filter those sensations, and
initiate a response appeared to be within normal limits.
This provided support for the importance of self-regulatory
deficits in these children (Douglas, 1983). Children with
ADHD also appeared to have a normal attentional capacity, as
measured by overall intellectual ability (Cohen, 1993).
Their ability to encode information, a function subserved by
the hippocampus and amygdala, was found to be normal (Ott &
Lyman, 19 93) .
The mesencephalic reticular formation is involved in
the arousal states necessary for attention (Watson,
Valenstein, & Heilman, 1981). Arousal can be defined as the
physiological readiness to attend to incoming stimulation
(Cohen, 1993). The reticular formation is believed to
modulate the function of the nucleus reticularis, which
influences the screening of sensory information by the
thalamus, and results in selective activation of cortical
areas (Watson, Valenstein, & Heilman, 1981). The ability to
sustain attention is mediated by the activation of these
structures, as they control the flow of sensory information
to higher cortical structures (Mirsky et al., 1991).
Cortical areas that play a role in the "higher" forms of

76
attention such as response selection and shifting attention
are activated by these subcortical structures.
Voeller (1991) discussed the relationship of
impairments in sensory attention, controlled by sensory
association areas and the subcortical structures that
project to these areas, to the symptoms of ADHD (Voeller,
1991). These systems may control the ability to focus
attention on external events (Mirsky, 1991). Automatic
shifts in sensory attention were impaired in children with
ADHD (Cohen, 1993), suggesting difficulty in controlling
responses to environmental stimuli (Douglas, 1983). As
noted earlier, children with ADHD have been described as
having left-sided neglect similar to adults with right
hemisphere dysfunction (Voeller & Heilman, 1988a). This
represented a deficit in directed sensory attention, which
may be a function of the posterior parietal attention system
(Posner, 1992). Processing of incoming sensory information
and automatic shifts of attention appear to be regulated by
the parietal lobe and associated thalamic nuclei (Posner,
1992) .
Weinberg and Harper (1993) examined the literature
regarding the role of the right parietal lobe in sensory

77
attention and concluded that underarousal in this area
causes disinhibition of irrelevant input. However, this
conclusion was based on disorders, such as depression, that
cause secondary problems in vigilance and they did not
directly investigate vigilance in ADHD (Weinberg & Harper,
1993). Competing explanations for sustained attention
deficits in ADHD, such as the difficulties in self¬
regulation proposed by Douglas (1983), suggest that it is
not only the posterior attention system that is involved in
ADHD. Other impairments, such as impaired active shifting
of attention, are controlled by different neural structures,
discussed below (Voeller & Heilman, 1988a).
The brain region most involved with attention and
cognitive regulation appears to be the prefrontal cortex
(Posner, 1992), thought to be responsible for active
shifting of attention (Mirsky et al., 1991). Planning and
organization of behavioral responses to environmental
stimulation is also an important component of frontal lobe
activity (Cohen, 1993). These skills have been found to be
deficient in children with ADHD (Shue & Douglas, 1992).
Unmedicated children with ADHD had normal recognition for
the spatial location of pictures presented to them in a

78
structured format (Ott & Lyman, 1993). Their free recall of
the pictures, which required self-generated organization of
information for output, was significantly worse than normal
controls (Ott & Lyman, 1993). Impulsivity and
distractibility are considered to be modulated by
frontal/executive functions (Voeller, 1991). ADHD children
have been found to have difficulties inhibiting responses to
one stimulus and then reengaging attention on second
stimulus, also considered to be a frontal/executive function
(Schachar, Tannock, & Logan, 1993).
Explanation for the inability of children with ADHD to
shift attention is probably not limited to frontal/executive
dysfunction (Yeates & Bornstein, 1994). Research has
suggested that a loop involving the caudate nucleus,
thalamus, and cortical areas is involved in ADHD (Yeates &
Bornstein, 1994). The frontal lobe-caudate nucleus
interconnection appeared to be important for regulation of
directed attention (Mirsky, et al., 1991) and modulation of
responses (Cohen, 1993). Dysfunction in frontal-caudate
systems may be involved in deficits of response inhibition
and motor overactivity (Voeller, 1991). When subjects are
asked to perform tasks with a substantial attentional

79
component, regional cerebral blood flow in the frontal and
subcortical regions involved in attention increases
significantly (Haxby, Grady, Ungerlieder, & Horwitz, 1991).
These authors also reported increased blood flow in the
areas of cortex responsible for sensory processing (e.g.,
the occipital lobes and- somatosensory cortex) .
Overall, it appeared that children with ADHD have
cortical dysfunction in several areas, especially in the
right frontal and parietal cortices, and subcortical
dysfunction in areas responsible for modulating sensory
input, the caudate nucleus and thalamus. While the
dysfunction may be subtle and not influence the results of
formal neuropsychological testing (Barkley & Grodzinsky,
1994), it can and most likely does have an impact on daily
activities.

CHAPTER 3
THE PURSUIT ROTOR AND MOTOR SKILL ACQUISITION
The Pursuit Rotor
Description
The rotary pursuit task is a commonly used method of
investigating motor skill learning (Eysenck & Frith, 1977).
It is a simple device, consisting of a lighted target on a
rotating turntable. Subjects are expected to keep a light-
sensitive stylus in contact with the target and the total
time of contact is electronically recorded. Subjects
typically developed the motor coordination skills necessary
to increase time on target through repeated trials (Eysenck
& Frith, 1977) . Distractors affected the performance of
normal subjects on the pursuit rotor, with greater amounts
of distraction causing greater difficulties in performance
(Eysenck & Thompson, 1966). Nonetheless, after a rest
period, normal subjects demonstrated normal learning for the
task. The hypothesis developed that most learning on the
80

81
pursuit task occurs during rest periods when the information
is consolidated (Eysenck & Thompson, 1966).
Type of practice (massed vs. distributed) significantly
influenced pursuit rotor performance (Eysenck & Frith,
1977). Massed practice refers to the measurement of
learning during continuous trials, while distributed
practice involves sets of trials with rest periods in
between trials. Distributed practice has been found to be
the most effective method of learning on this task, perhaps
as a result of consolidation processes (Eysenck & Thompson,
1966). In other words, subjects appeared to develop
programs for successfully completing the task while resting,
rather than through correction of errors during the task
(Eysenck & Frith, 1977).
Performance of Children on the Pursuit Rotor
Children demonstrated the ability to perform the rotary
pursuit task and to learn over repeated trials (Davol,
Hastings, & Klein, 1965; Dunham, Allan, & Winter, 1985).
The performance of children between kindergarten and third
grade was measured at two preset speeds (33 & 45 rpm). Age
had a significant effect on the performance and the slower

82
speed appeared necessary for younger children. Older
children showed greater improvement with practice, but never
achieved adult levels of performance (Davol, Hastings, &
Klein, 1965). Socioeconomic status may affect motor
learning at younger ages, but this difference disappears
among older children (Davoll & Breakell, 1968) . Davoll,
Hastings, and Klein (1965) noted that young children may
find the rotary pursuit task fatiguing and repetitive. In
order to increase the motivation of these children,
reinforcement should be applied.
Children defined as "clumsy," who had significant motor
incoordination but were normal on neurological examination,
performed worse than normal controls on the rotary pursuit
task (Lord & Hulme, 1988). However, they did show a steady
increase in their ability to stay on target across trials,
suggesting a transfer from visual feedback control of motor
systems to the development of motor programs (Heindel,
Butters, & Salmon, 1988). Impairment in initial encoding,
through processing of visual feedback, may be a more
important factor in clumsiness than the inability of these
children to develop effective motor programs (Lord & Hulme,
1988). Nonetheless, these children did not approach normal

83
performance even after several trials, suggesting deficient
programming of motor sequences.
Children who are mildly mentally retarded have
significantly more difficulty in motor learning than normal
controls (Simenson, 1973). Use of an audible feedback
signal for errors did not facilitate performance, but extra
practice trials did, suggesting that these children may
actually experience feedback as noxious (Simenson, 1973).
Later research contradicted this conclusion, as visual,
tactile, and auditory feedback were found to enhance motor
learning in both retarded and control children (Horgan,
1982). In fact, auditory feedback given when a subject was
on target helped retarded children attain normal levels of
performance. These results suggested that task conditions
affect motor learning in retarded children and that optimal
conditions result in normal levels of motor learning
(Horgan, 1982).
Heitman and Gilley (1989) investigated the performance
of mentally retarded adolescents using either blocks of
same-speed trials or a random distribution of speeds. There
was no significant effect for the blocked condition,
suggesting that inattention to assigned tasks plays a role

84
in poor rotary pursuit performance by mentally retarded
children (Heitman & Gilley, 1989). The learning curves of
these children were correlated with on-task behaviors
(Heitman & Gilley, 1989), and feedback appeared to improve
attention to a task, consistent with earlier results
(Horgan, 1982). Retarded children appeared to gain from
consolidation, as second-day performance was improved over
the first day learning (Heitman & Gilley, 1989). This was
consistent with other evidence that skill retention in these
children is not significantly different from normal children
(Simenson, 1973).
No significant effect for either massed or distributed
practice was found in mildly mentally retarded children
(Rider & Abdulahad, 1991). Improved performance was again
found on the second day of testing, consistent with
consolidation and skill retention, but attention problems
had a negative impact on performance (Rider & Abdulahad,
1991). There seemed to be an optimal number of trials for
the acquisition of motor skills in autistic children, as the
use of more than 10 trials resulted in significant off-task
behavior (Wek & Husak, 1989). Within these limitations, it

85
appeared that autistic children are also capable of learning
a novel motor skill (Wek & Husak, 1989).
The impact of attention difficulties on rotary pursuit
performance may be relevant to children with ADHD.
Inattention and the inability to form motor programs may
both play a role in their motor learning. To determine the
effect of motor programming deficits, the motivation of
children with ADHD should be controlled to prevent the
additional effects of inattention and impulsivity on
results.
Sex Differences on the Pursuit Rotor
Research findings regarding sex differences in pursuit
rotor performance have been inconsistent. No sex
differences were found in the performance of children in
kindergarten through third grade (Davol, Hastings, & Klein,
1965), a finding replicated with a group that also contained
children in the fourth and fifth grades (Davol & Breakell,
1968). Another study indicated that the performance of boys
is significantly better than that of girls, but used a
subject pool that included children with mild mental
retardation (Simenson, 1973). Under massed practice

86
conditions, there were no significant differences between
first-grade boys and girls at lower speeds (15 & 30 rpm),
but boys demonstrated better learning than girls at the
highest speed (45 rpm; Horn, 1975). Consistent with this
finding, elementary school girls had lower ceiling speeds
than boys (Dunham, Allan, & Winter, 1985). Although
children were not compared in each grade, the major
differences appeared to exist in kindergarten, and sixth
grades, while girls in grades two through five appeared to
more closely match the performance of boys (Dunham, Allan, &
Winter, 1985). When speed of rotation was held constant,
the performances of boys and girls were not significantly
different (Ruffer, 1984). In addition, the performance of
college-age women was not significantly different from men
in distributed practice conditions with rest periods of 10
seconds or longer (McBride & Payne, 1980) . No research to
date has compared the performance of boys and girls when
speeds were set individually, the method used in the current
study.

87
Motor Skill Acquisition in Children with ADHD
As noted above, little research has been done on motor
skill acquisition in children with ADHD. On a visual-motor
tracking task requiring the subject to use a control stick
to keep a lighted dot centered on a moving target, children
with ADHD performed significantly worse than normal controls
(Conners & Delamater, 1980). Although some practice effects
were recorded, the children were tested under several
different conditions and the task did not allow for
continuous practice of any one condition, making it
difficult to make any judgements about motor skill
acquisition (Conners & Delamater, 1980). Examination of the
effect of Ritalin on baseball skills indicated that it
improved the attention and on-task behaviors during games,
but had little effect on improving baseball skills (Pelham
et al. , 1990). However, the children had relatively little
chance to practice their skills and baseball skills often
involve multiple coordinated movements and cognitions,
making it difficult to determine all variables involved in
their acquisition (Pelham et al., 1990).

88
On the rotary pursuit task, children with ADHD and with
ADD/WO demonstrated no differences from normal controls in
motor skill learning or retention (Leavell, Ackerson, &
Fischer, 1995). The times on target for children with ADHD
each of five 20-second trials and after a 30-minute delay
were significantly worse than normal controls (Leavell,
Ackerson, & Fischer, 1995), a finding consistent with
research on "clumsy11 children (Lord & Hulme, 1988) . First-
trial scores for children with ADHD were significantly
correlated with neuropsychological measures of visual-motor
integration, suggesting that deficits in these skills may be
responsible for incoordination in children with ADHD
(Leavell, Ackerson, & Fischer, 1995). However, it is
difficult to make conclusions about motor skill learning
from these results, as five trials may be insufficient for
even normal children to acquire the necessary motor
programs. In addition, the children were drawn from a wide
age range (6-16) and a relatively slow, uniform speed (15
rpm) was used. Use of this speed may have made the task too
easy for some of the children, especially the older ones.
Finally, the effect of motivation was not controlled.

89
Neuroanatomy of Motor Systems
Motor systems involve a number of neurological
substrates, both cortical and subcortical. Parietal lobe
lesions lead to difficulties in copying meaningless arm
movements (Kolb & Milner, 1981), while frontal lobe lesions
result in deficits in both facial and arm movement
imitation. The supplementary motor cortex is thought of as
the area responsible for programming complex movements
(Alexander, DeLong, & Strick, 1986), but the lesions in Kolb
and Milner (1981) varied widely, making precise localization
impossible. Nevertheless, it appeared that the frontal
lobes were responsible for the programming of movement
sequences. Movement programming may be represented
bilaterally in the frontal lobes (Kolb & Milner, 1981) and a
lack of coordination between hemispheres may lead to
increased severity of impairment (Milner & Kolb, 1985) .
Patients with callosotomies (cutting of the corpus callosum)
performed significantly worse on a facial movement task than
did frontal lobe patients. While these effects may be
explained by memory difficulties, there were no significant
errors on single facial movements, suggesting that it is the

90
sequencing of movements that is affected (Milner & Kolb,
1985) .
Frontal lobe lesions affected performance of sequential
tapping tasks (Leonard, Milner, & Jones, 1988) . When the
coordination of both hands was required, subjects with
frontal lobe lesions had the greatest difficulty relative to
normal controls and subjects with temporal lobe lesions.
Subjects with left frontal lesions performed worse than
those with right frontal lesions. Subjects with temporal
lobe lesions demonstrated difficulties similar to frontal
lobe subjects on a sequenced tapping task using only one
hand. This result may have been influenced by task demands,
as speed rather than coordination was important in the one-
handed tapping task, and there is a general slowing of motor
speed in most cases of brain injury (Leonard, Milner, &
Jones, 1988) .
The importance of right frontal lobe involvement in
movement has been demonstrated. Subjects with large right
frontal lesions have significant difficulty in recalling the
distance of arm movements (Leonard & Milner, 1991a). This
deficit was seen without regard to interference tasks, an
indicator that the right frontal lobe is involved in the

91
processing of this information. It is the maintenance,
rather than the encoding, of information about the distance
of arm movements that appeared to be a right frontal lobe
function, as immediate recall was not impaired in these
subjects (Leonard & Milner, 1991b). The right frontal lobe
subjects with large lesions were equally impaired with
either hand, and were more impaired than subjects with
either left frontal lesions or small right frontal lesions.
These findings indicated that localization and size are
important, with large right-sided frontal lesions disrupting
motor systems that maintain kinesthetic distance information
(Leonard & Milner, 1991a) .
The basal ganglia (caudate nucleus, putamen, and
globus pallidus) play a role in motor skill learning (Saint-
Cyr, Taylor, Trepanier, & Lang, 1992) . Subjects with
Huntington's disease, a movement disorder arising from basal
ganglia dysfunction, performed significantly worse than
groups of subjects with amnesia, Alzheimer's disease, and
normal controls on the pursuit rotor task (Heindel, Butters,
& Salmon, 1988). Neither global amnesia nor the early
stages of Alzheimer's disease impaired the performance of
these patients on a mirror-tracing task, suggesting that the

92
mechanisms for motor skills learning are separate from other
memory systems (Gabrieli, Corkin, Mickel, & Growdon, 1993).
Motor learning may also be separable from spatial location
ability. Spatial location was deficient in the amnesic
patient, H.M. (Smith, 1988), who demonstrated relatively
intact motor learning (Gabrieli, Corkin, Mickel, & Growden,
1993). The finding that subjects with Huntington's disease
were not as impaired as those with Alzheimer's on a verbal
recall task supported the dissociation between motor and
verbal learning (Heindel, Butters, & Salmon, 1988). The
basal ganglia are part of a loop involving the motor cortex
and thalamic nuclei that control motor behavior (Penny &
Young, 1986). Damage to the basal ganglia causes an
inability to direct and control movements. Other motor
control areas, such as the cerebellum, did not appear to
influence motor skill learning (Gabrieli, Corkin, Mickel, &
Growden, 1993) .

CHAPTER 4
SUMMARY AND RATIONALE
Summary
Children with attention deficit hyperactivity disorder
(ADHD) are characterized by impulsivity, inattention, and
motor hyperactivity. A debate about possible subtypes
existed for some time, and research provided support for two
categories of attention deficit disorder (ADD), ADD with
hyperactivity (ADD/H) and ADD without hyperactivity
(ADD/WO) . Behavioral ratings of children with ADD./WO
indicated that these children were lethargic, with more
internalizing behaviors, while ADD/H children displayed
motor hyperactivity and aggressiveness. Few differences
between these groups were found on neuropsychological
measures, and behavioral assessment is the method that best
distinguishes between them. The DSM-IV took this research
into consideration and recognized three subtypes of ADHD; a
Primarily Inattentive type, a Primarily Hyperactive type,
and a Combined type. The children with ADHD-combined type
93

94
were the group of interest in this study because of the
combined motor and attentional components of their symptom
pattern. Significant differences between boys and girls
with ADHD have not been identified by the research.
Children with ADHD may be at greater risk for accident and
injury than controls. Developmental, health and family
problems are highly correlated with ADHD, as are
oppositional and conduct problem behaviors. ADHD has a
high correlation with learning disabilities, possibly as a
result of similar neural substrates, but with the
independent contribution of attentional deficits. The
academic learning of these children has been well
investigated, but motor coordination deficits have not.
Differences have been found between the brains of
children with ADHD and those of normal controls. The
caudate nucleus of children with ADHD has been found to have
important differences from those of normal children, and
this structure is involved in learning motor skills. The
corpus callosum of these children may be involved in the
regulation of executive, motor, and sensory functions.
Children with ADHD may have frontal lobe dysfunction,
although tests of executive function yielded inconsistent

95
results. It is possible that dysfunction in cortical-
subcortical systems of attention and motor control lead to
the characteristic features of ADHD. The hypothesis that
these children are physiologically underaroused continues to
be debated. Some evidence has been found to support this
theory, while other research has indicated that difficulties
in self-regulation explain apparent deficits in arousal.
Incoordination in these children may result from
difficulties in forming motor programs. An inability to
learn motor tasks may have an impact on both social and
academic functioning and may be related to the neural
substrate of ADHD. This study compared the performance of
children with ADHD on the rotary pursuit task to that of
normal children in an attempt to answer some of these
questions.
Specific Aims and Hypotheses
Although motor skills deficits have been noted, little
research to date has investigated motor learning in children
with ADHD. Motor learning deficits were often explained by
inattention during skill learning (Pelham et al, 1990). The
present study provided information about motor skill

96
acquisition in children with ADHD and attempted to explain
any differences that were found when these children were
compared to normal controls. Deficits in performance were
believed to be primarily due to deficits in the formation of
motor programs, with impulsivity and inattention resulting
in additional deficits. The inattention and impulsivity
characteristic of children with ADHD was modulated in a
reward for performance condition.
Specific hypotheses were as follows:
(1) Children with ADHD in the reward for performance
condition were expected to have deficits in motor learning
compared to normal controls. The reward situation attempted
to control for attention without the use of medication that
might have also enhanced motor skill acquisition (Douglas,
1984) .
(2) Children with ADHD in the no reward learning situation
were expected to have added deficits resulting from
impulsive responding and inattention to the task (Douglas,
1984) .
(3) Significant group differences were expected between
children with ADHD and normal controls on measures of fine
motor coordination (Barkley &. Grodzinsky, 1994) and

97
attention (Corkum & Siegel, 1993). No significant group
difference was expected on a test of visuospatial ability
(Douglas, 1984).

CHAPTER 5
DESIGN
This was a 2x2, between subjects design, with pursuit
rotor performance as the primary dependent variable. The
independent variables, ADHD and reward status, are depicted
in Figure 1. Each child in the ADHD and control groups were
randomly assigned either to a reward for performance
condition or a no-reward condition. The reward condition
was based on research suggesting that small rewards increase
the motivation and attention of children with ADHD (Pelham,
Milich, & Walker, 1986; Carlson, Pelham, Milich, & Dixon,
1992) without using medication that may improve the overall
functioning of the cortical-subcortical loops involved in
attention and motor programming (Lou, et al., 1989).
Children in the reward for performance groups were given
stickers or some other small reward for maintaining or
improving their level of performance on each trial.
Children in the no-reward groups did not receive any
98

99
tangible incentives for improved performance. Verbal
encouragement was given to both groups.
ADHD STATUS
ADHD
n = 31
CONTROL
n = 33
REWARD STATUS
REWARD
NO
REWARD
NO
REWARD
REWARD
n = 15
n = 16
n = 17
n = 16
1
Figure 1

CHAPTER 6
PROCEDURE AND METHODS
Subjects
This study investigated motor learning in children with
ADHD compared to normal controls on the rotary pursuit task.
All subjects participated voluntarily and parents completed
informed consent letters for each child. Subjects with ADHD
were drawn from a private mental health office, a support
group for parents of children with ADHD, and a university
neurology clinic. Control subjects were recruited from
community groups and a local elementary school.
Complete demographic information for both the ADHD and
control groups are presented in Table 1. To avoid the
maturation effects that may effect the performance of older
children with ADHD (Fischer, Barkley, Edelbrock, & Smallish,
1990), subjects for this study were between the ages of 7
and 11. Only right-handed children were used for this
study, as there may be confounding differences in motor
performance between right- and left-handed children. Gender
100

101
was not used as an exclusion criteria, as few significant
differences have been found between boys and girls with ADHD
(Breen, 1989). The experimental group consisted of 31
children (27 boys, 4 girls) who had been given a clinical
diagnosis of ADHD either prior to, or soon after, their
participation in the study. There were 33 children in the
control group (19 boys, 14 girls). Children with a
diagnosis of developmental learning disability, a WISC-III
interpolated IQ below 80, or placement in special education
were excluded from this study. However, 10 of the children
with ADHD were receiving tutoring or academic enrichment.
Twenty-six of the children with ADHD reported no comorbid
diagnosis, three had co-occurring Oppositional Defiant
Disorder, one had an unspecified emotional disorder, and one
had multiple comorbid diagnoses. No children in the control
group reported academic difficulties, comorbid diagnoses, or
use of psychiatric medications. Twenty-seven of the
children with ADHD were prescribed stimulant medication, one
child was prescribed an antihypertensive, and three children
were prescribed no medication to control symptoms of ADHD.
To control possible neurobiological and behavioral effects
of medication, parents of children with ADHD were asked to

102
withhold medication for at least 12 hours prior to their
child's participation in the study.
Measures
Behavior Rating Scales
Parents completed two rating scales designed to
estimate symptoms of ADHD in children, the 48-item revised
version of the Conners Parent Rating Scale (CPRS-R; Goyette,
Conners, & Ulrich, 1978) and an 18-item checklist of ADHD
symptoms drawn from the DSM-IV (American Psychiatric
Association, 1994; Appendix A). The CPRS-R has been found
to be reliable in assessing symptoms of ADHD (Barkley,
1990). These measures were used to compare the behavioral
profiles of the ADHD and control groups, but not to diagnose
ADHD. As noted above, the children in the ADHD group were
diagnosed by clinicians outside of this study.
Democrranhi o.q
Parents completed a short demographic questionnaire
(Appendix B). This provided information on age, ethnicity,

103
gender, socioeconomic status, comorbid diagnoses, tutoring,
and medications.
Neuropsychological Measures
Four brief screening measures were incorporated into
the protocol. As noted above, an interpolated Full Scale IQ
was used as a determinant of each child's ability to
understand and complete the protocol. Screening measures of
attention, fine motor coordination, and spatial judgment
were incorporated because these skills were believed to be
elements of motor skill acquisition.
The interpolated FSIQ was derived from a short form of
the WTSC-ITT (Wechsler, 1991) that consisted of the
Vocabulary and Block Design subtests (Sattler, 1992). The
Vocabulary subtest is a language-based task requiring
children to orally define words. Block Design involves
visual-spatial reasoning and coordination in the
construction of abstract designs to pictured models.
Correlations of r=.79 between Vocabulary and the Full Scale
IQ (FSIQ) have been reported (Sattler, 1992), while Block
Design correlated with FSIQ at r= .74. These subtests were

104
correlated with g, or general cognitive ability at r=.79 and
r=.74, respectively (Sattler, 1992).
The Continuous Performance Test (CPT) was used as a
measure of sustained attention and impulsivity. The CPT has
been shown to be a valid measure of attention problems,
especially through the number of correctly identified
targets, and errors of omission score (Barkley, Grodzinsky,
& DuPaul, 1992; Barkley & Grodzinsky, 1994). Impulsivity is
often measured through the errors of commission score
(Barkley & Grodzinsky, 1994) . The version of the CPT used
in this study (Conners, 1994) was divided into two five-
minute subtests. During that time, a sequence of letters
was displayed on a computer screen. The first subtest was a
cancellation task that required a response when the target
letter "X” appeared, while the second subtest was a
conditional cancellation task, requiring responses to a
target letter sequence, "XA". The CPT was scored by
computer and errors of commission, errors of omission, hit
percentage (percentage correct), and reaction time scores
were produced. Errors of commission and reaction time
provided a baseline estimate of the child's impulsivity,

105
while hit percentage and omission errors were used to
estimate inattention.
The Grooved Peaboard provided an estimate of fine motor
coordination. Each child was timed while placing grooved
pegs into 10 slotted holes, with the slots varied by angle
of rotation (Lezak, 1983). Time to completion was used as
the measure of performance. This test has been found to be
a valid measure of motor performance and normative data for
children has been established (Klonoff & Low, 1974) .
Spatial abilities were assessed by the Judgement of
Line Orientation task (Benton, Hansher, Varney, & Spreen,
1983). Subjects were required to match the orientation of
line segments with those target lines, a task that requires
the cognitive ability to extend the segments and recognize
their angular placement. Number of correct matches was used
as the measure of performance. The results of this measure
were used to determine what effect, if any, that spatial
deficits had on motor skill acquisition.
Primary Dependent Measure
The primary dependent measure was the Photoelectric
Pursuit Rotor. The pursuit rotor apparatus consisted of a

106
lighted target embedded in a turntable, a stylus held by the
subject, and an attached electronic counter to measure time
on target. The lighted target rotated in a circular motion
around the turntable, and the stylus was used to track the
motion of the target. The counter recorded the amount of
time that a subject successfully kept the stylus in contact
with the target. Performance scores on the pursuit rotor
vary between individuals, but learning curves tend to be
similar. The test has been found to have reliabilities of
around x = -90, indicating that differences in individual
performance are constant (Eysenck & Frith, 1977). When
given to cadet pilots as part of a motor test battery, the
pursuit rotor had good correlations with tests of motor
ability such as complex coordination (x = .65), rudder
control (x = .43) and finger dexterity (x = .45; Eysenck &
Frith, 1977) . Factor analysis on the motor battery found
that the pursuit rotor loaded highly on a "coordination" or
"psychomotor" factor that included other tests of dexterity
and gross motor coordination (Eysenck & Frith, 1977). These
findings suggested that the pursuit rotor would provide a
satisfactory measure of motor learning ability.

107
Experimenter Training
This study was primarily conducted by the principal
investigator and two graduate research assistants in
clinical psychology. Two undergraduate research assistants
were also involved in the study and participated in
protocols under the supervision of the principal
investigator. Research assistants were trained in the
standardized administration of the research measures and a
script was provided for the research protocol. The
performance of the assistants was evaluated by the principal
investigator and they demonstrated knowledge of standardized
procedures on all measures before they were permitted to
administer tests. To control for experimenter differences,
each investigator performed the protocol with both
experimental and control subjects.
Procedure
Parents of children with ADHD were contacted through
several sources. Letters were sent through a private
psychology practice and a support group for parents of
children of ADHD. These letters informed the parents of the

108
design and purpose of this study, and the exclusionary
criteria. The parents of children contacted through the
university neurology clinic were approached during clinic
appointments or contacted by phone and given the same
information.
Control children from were contacted through letters to
parents sent home through community groups or P.K. Yonge
Developmental Research School. The psychologist at the
school was contacted by the principal investigator and
access to classes with children in the target age range was
requested. A graduate research assistant gave letters
asking for parental permission to the teachers of these
classes, who sent the letters home with the children. The
children whose parents returned the signed consent forms
were taken out of class one at a time by the graduate
research assistant for participation in the study. Two
children in the control group who scored in the clinical
range of the CPRS-R, met DSM-IV checklist criteria for ADHD,
and were observed to be inattentive and hyperactive were
excluded from the study.
Placement into either the reward or no-reward
conditions was randomized by the placement of small slips of

109
paper with equal numbers of either a "1" or a "2", into four
paper bags, two for the ADHD group and two for the control
group. Children were not told the meaning of the numbers
and only children in the reward conditions were asked to
choose a reward prior to the rotary pursuit task. These
children were allowed to choose from a selection of small
rewards (baseball cards, stickers, etc.), and told that they
would receive a reward each time that their performance
improved or stayed the same. This was to avoid a loss of
motivation that may have occurred when the children reached
performance ceilings and could no longer be rewarded for
improvements. Children in the no-reward groups were
encouraged to do their best on the rotary pursuit, but did
not receive any rewards based on performance. These
children received a small reward after completing the
protocol, but were unaware of this during the task.
Following assignment to a condition, the pursuit rotor
task was demonstrated to each child and they were told that
the goal was to keep the stylus in contact with the
rotating target. Performance on the pursuit rotor was
measured by the number of seconds the child spent on target.
Subjects were given between one and four practice trials on

110
the pursuit rotor and speed of rotation was adjusted for
each child based on performance during the practice trials.
After the child either met a criterion of 30% time on
target, or completed four practice trials, the experiment
began. Individualized speeds were used to avoid ceiling
effects that may have occurred in earlier studies of motor
skill acquisition. After completion of the practice trials,
the abbreviated form of the WISC-III was administered. The
Vocabulary subtest was administered first, followed by the
Block Design subtest. Two subjects had an interpolated IQ
below 80 and were allowed to complete the study, but
excluded from the data analysis.
Children completed a total of 6 blocks of 5, 30-second
rotary pursuit trials, with 10 second intertrial intervals.
The short trial length and the intertrial interval were used
to minimize fatigue (Wek & Husak, 1989). The first two
blocks of trials were given immediately following the Block
Design subtest and there was a one-minute break between
trials. Placement of breaks between blocks of rotary
pursuit trials was a method of distributing practice, and
allowed for the formation of motor programs during
consolidation (Eysenck & Frith, 1977). After the second

Ill
pursuit rotor trial was complete, the first part of the CPT
was administered. This was a five-minute letter
cancellation task and the children were told to press the
space bar when the letter "X" appeared. The examiner was
not in the room during administration of the CPT to control
the effect of examiner presence on performance (Power,
1992) . Following the first CPT administration, two more
blocks of pursuit rotor trials were administered, with a
one-minute break between blocks. The fourth block was
followed by the second part of the CPT, a five-minute
conditional cancellation. This task required the children
to respond only when the "AX" sequence of letters appeared
on the display. The final two blocks of rotary pursuit
trials were then administered, again separated by a one-
minute break. The sixth block was followed by the Grooved
Pegboard. Children were instructed to place the pegs into
the holes as fast as they could and were allowed to place
two practice pegs before beginning the task. The final
measure given was the Judgement of Line Orientation, with
the child directed to match line segments to the orientation
of target lines. The experimental sequence is depicted in
Figure 2.

112
Demonstration/Practice => WISC-III Short Form => Block 1 =>
1 min. break => Block 2 => CPT/Cancellation => Block 3 =>
1 min. break => Block 4 => CPT Conditional Cancellation =>
Block 5 => 1 min. break => Block 6 => Grooved Pegboard / JLO
Figure 2
Each child participated in this study for only one day,
and the protocol was completed in approximately ninety
minutes. The investigation of retention in motor learning
was not within the scope of this study, so a second day of
experimentation was not necessary. All participating
children completed the protocol.

TABLE 1
DEMOGRAPHICS
113
TOTAL
ADHD
CONTROL
SAMPLE
GROUP
GROUP
(N=64)
(N=31)
(N=33)
CHILD'S SEX
Male
46
27
19
Female
18
4
14
CHILD'S AGE
7
9
6
3
8
19
9
10
9
11
3
8
10
15
7
8
11
10
6
4
SOCIOECONOMIC STATUS (Hollingshead)
1 1
1
0
2
8
6
2
3
10
8
2
4
25
8
17
5
20
8
12
RACE
White
51
27
24
Minority
13
4
9
African-American
5
2
3
Hispanic
6
0
6
Native American
1
1
0
Biracial
1
1
0
PSYCHIATRIC MEDICATION
None
36
3
33
Stimulants
27
27
0
Other
1
1
0
COMORBID DIAGNOSES
None
59
26
33
Oppositional/Defiant
3
3
0
Other/Combined
2
2
0

CHAPTER 7
RESULTS
Initial Analyses
Experimenter Effects
T-tests were performed to compare the protocols
completed by the primary investigator and the graduate
research assistant most involved in the study. The second
graduate assistant completed too few protocols (n = 4) for
analysis. No significant differences between the two raters
were found on IQ estimates, measures of attention, fine
motor coordination, and judgement of spatial orientation, or
pursuit rotor performance.
Demographic Analyses
No significant differences were found between the ADHD
group and the control group for age (£ (62) = -.19, ns) or
ethnicity (X2 (4) = 8.32, ns). Socioeconomic status of the
control group, based on Hollingshead's (1975) four-factor
114

115
index of social status, was significantly higher than that
of the group of children with ADHD (X2 (4) =10.59, p =
.05). There were significantly more girls in the control
group than in the ADHD group (X2 (1) = 6.89, p = .01).
Significantly more children in the ADHD group than in the
control group were receiving tutoring or other academic
assistance (X2 (1) = 12.62, p < .01) and there was a trend
towards more comorbid diagnoses in the ADHD group compared
to the control group (X2 (2) = 5.77, p = .06).
Parent Report Measures
Parents of children in the ADHD group reported
significantly more disruptive behaviors on the CPRS-R than
parents of children in the control group (p (62) =7.57, p <
.001; Table 2). Children in the ADHD group were reported to
meet significantly more of the DSM-IV diagnostic criteria
for ADHD than children in the control group (p (62) = 12.84,
P< .001; Table 2).

116
Neuropsychological Measures
Continuous Performance Test
On the CPT cancellation task, no significant
differences were found between the group of children with
ADHD and the control group on hit percentage (£. (62) = -.02,
ns) or omission errors (£. (62) = -.02, ns; Table 3) .
Children with ADHD made significantly more commission errors
(£ (62) = 2.55, ¡D <. 05) and the reaction time of children
with ADHD on the cancellation task was significantly faster
than the control group (£, (62) = -2.01, g < .05). On the
CPT conditional cancellation task, no significant
differences were found between the ADHD and control groups
on hit percentage (£ (62) = -1.22, ns), omission errors (t
(62) = 1.10, ns) or reaction time (£ (62) = -.74, ns; Table
3). The ADHD group made significantly more commission
errors than the control group (£. = 2.07, g < .05).
10 Screening, Grooved Pegboard and
Spatial Orientation
There was no significant difference between the
interpolated IQ scores of the ADHD and control groups (£

117
(62) = -1.55, ns; Table 3). No significant difference was
found between the groups on Grooved Pegboard performance
with the dominant (right) hand (£. (62) = 1.29, ns). The
ADHD group was significantly slower than the control group
with the non-dominant (left) hand (t = 2.23, p = .03; Table
3). No significant difference was found between the groups
on the spatial orientation task (£ (62) = -1.34, ns; Table
3) .
Analyses of Pursuit Rotor Performance
Overview
To control for the intertrial variability in time on
target evident among the children with ADHD, the median
score for each block was used as the primary measure of
performance for each individual. Individual median scores
were then collapsed across each group to provide a mean
score for group performance on each block. Means, standard
deviations, and ranges for the four experimental groups
(ADHD/Reward, ADHD/No Reward, Control/Reward, Control/No
Reward) on all blocks are displayed in Table 4. There was
no significant effect for group on rotation speed (£ (3,60)

118
= .23, ns). Rotation speeds ranged from 16 to 45 rpm, with
a mean speed of 26.78 rpm. Pursuit rotor performance was
found to meet the assumptions of independence, normality of
distribution, and homogeneity of variance for use of
Analysis of Variance. Therefore, variations of this
statistical method were used for all primary analyses.
Between-group pairwise comparisons used t-tests, as this was
the most sensitive method for detecting significant
differences in performance.
Power
Power analysis indicated sufficient power (.8) for
detecting significant group differences with Analysis of
Variance. Power for pairwise t-tests was variable, with a
value of .3 for between-group differences of around one
second, but adequate power (.8) for larger between-group
comparisons. Power was adequate (.8) for a multiple
regression analysis using the total sample and six
independent variables, but there may not have been
sufficient power (.67) to interpret separate simple linear
regressions for the ADHD and control groups.

119
Pursuit Rotor - Analyses of Group Performances
A repeated measures ANOVA was used to analyze the
effect of ADHD status and reward condition on pursuit rotor
performance. Initially, socioeconomic status, gender,
comorbid diagnoses, and tutoring/other academic help were
used as covariates, as preliminary analyses found
significant differences between the ADHD and control groups
on these variables. However, no significant effect was
found for any covariate and these variables were removed
from the model. The reward condition was also not found to
be significant as a main effect or in any interaction.
Therefore, this variable was removed from the model and the
four conditions were collapsed into ADHD and Control groups.
Further analyses were performed on this reduced model.
The reduced-model repeated measures ANOVA found
significant effects for ADHD status, F (1,62) = 28.20, p <
.001, and learning over blocks, £ (5,310) = 21.17, p < .001.
A significant interaction was found between ADHD status and
learning, F (5,310) = 9.52, p < .001.
Separate repeated measures ANOVAs were performed for
the ADHD and control groups to investigate the interaction

120
between ADHD status and change in performance over blocks.
No significant change was found in the performance of the
ADHD group over blocks.
In contrast to the ADHD group, the control group
demonstrated a significant change in performance over
blocks, £ (5, 160) = 36.17, g < .001. T-tests were then
used for pairwise comparisons between blocks to determine
when motor learning took place. For the control group,
Block 1 time on target was significantly lower than Block 2
and Block 2 was significantly lower than Block 3 (Table 5).
There were no other significant differences between
successive blocks (Table 5).
Comparison of Group Differences on Blocks
T-tests were used in pairwise comparisons to
investigate group differences on the six blocks of rotary
pursuit trials. The ADHD group had significantly less time
on target than the Control group on each of the six blocks
(Table 6).

121
Multiple Regression Analyses
An index of learning was created by subtracting Block 1
performance from Block 6 performance. A multiple regression
analysis was conducted for the entire sample to examine the
relationship between this index and attention, impulsivity,
fine motor coordination, and spatial judgement. The number
of subjects made it necessary to limit the number of
independent variables entered into the equation to six.
Omission scores for both OPT tasks were chosen as the best
measures of attention, and both commission scores were used
as the best measures of impulsivity. Grooved Pegboard
performance for the non-dominant hand was used to measure
fine motor coordination, because group differences made it
more likely that this measure would be related to problems
in motor learning. The number correct on the Judgement of
Line Orientation was used as a measure of spatial judgment.
A stepwise multiple regression procedure was used to find
the predictive values of these variables. The only variable
found to be a significant predictor of learning was
commission errors on the CPT conditional cancellation task.
Results of the multiple regression are listed in Table 7.

122
Simple linear regression was performed with both the
ADHD and control groups to further define the relationship
of the CPT conditional cancellation errors and the pursuit
rotor learning index. A trend was found towards a
relationship between these variables for the ADHD group
(Beta = -.34, £ (29) = -1.95, p = .06). No significant
relationship between the two variables was found for the
control group (Beta = -.06, £ (31) = -.32, ns).
Additional Analyses
As there was a wide range of performance (Table 4), the
relationship between time on target for each pursuit rotor
block and motor skill acquisition was examined. Pearson x's
were calculated for correlations between the median time on
target for each block and the learning index. Correlations
became progressively stronger for the entire sample, with an
insignificant correlation found between Block 1 and the
learning index, but positive correlations of moderate to
high significance found in later blocks (Table 8). A
similar progression in positive correlation strength was
found for the ADHD and control groups when that data was
analyzed separately (Table 8). A Pearson correlation found

123
no significant relationship between socioeconomic status and
the learning index (r = .27).
To identify the factors underlying the range of motor
learning abilities, the relationship between fine motor
coordination (Grooved Pegboard) and the learning index was
examined using t-tests to compare children in the top and
bottom quartiles of the learning index. No significant
differences were found between these groups on either the
dominant (£ (30) = 1.04, ns) or nondominant hands (£ (30) =
1.88, ns). ADHD group children in the upper and lower
quartiles of the learning index were not significantly
different on the dominant (£ (14) = 1.92, ns) or nondominant
(£ (14) = 1.14, ns) hands. No significant differences in
fine motor coordination were found in control group children
in the upper and lower quartiles of the learning index
(Dominant hand, £ (14) = .00, ns; Nondominant hand, £ (14) =
.26, ns).

TABLE 2
PARENT REPORT MEASURES
124
ADHD
GROUP
CONTROL
GROUP
MEAN
(SD)
MEAN (SD)
CONNERS PARENT RATING SCALE
-REVISED
57.71
(22
.80)
21.82 (14
.40) 1
DSM-IV CHECKLIST
13.10
(3.
97)
2.12 (2.
80)1
1 E < .001

125
TABLE 3
NEUROPSYCHOLOGICAL MEASURES
ADHD CONTROL
GROUP GROUP
MEAN (SD)
MEAN (SD)
INTERPOLATED FSIQ 104.61 (13.42)
GROOVED PEGBOARD (seconds)
Dominant hand 32.45 (7.95)
Non-dominant hand 37.77 (11.03)
JUDGEMENT OF LINE ORIENTATION
(# correct) 17.35 (5.90)
110.45 (16.39)
30.00 (7.28)
32.58 (7.34)1
19.18 (5.03)
CONTINUOUS PERFORMANCE TEST: CANCELLATION
Hit percentage
Omission errors
Commission errors
Reaction time (ms)
90.97 (12.94)
1.77 (2.60)
10.90 (15.51)
590.16 (98.44)
91.06 (18.06)
1.79 (3.61)
3.82 (3.71) 1
644.24 (115.41)1
CONTINUOUS PERFORMANCE TEST: CONDITIONAL CANCELLATION
Hit percentage
Omission errors
Commission errors
Reaction time (ms)
91.61 (13.25)
1.29 (1.88)
10.92 (19.43)
508.16 (103.66)
94.70 (5.72)
.88 (1.02)
3.61 (5.86)1
528.12 (110.77)
1
£ < .05

126
TABLE 4
GROUP PERFORMANCES ON THE ROTARY PURSUIT*
(1)
GROUP
(2)
(3)
(4)
ADHD/
ADHD/
CONTROL/
CONTROL/
REWARD
NO REWARD
REWARD
NO REWARD
BLOCK 1
Mean
11.38
10.50
12.78
13.08
SD
2.85
3.57
2.46
2.54
Range
6.15-
3.51-
7.84-
10.17-
16.62
16.47
17.50
19.52
BLOCK 2
Mean
11.62
10.23
14.90
14.76
SD
3.15
3.52
3.17
3.09
Range
7.46-
3.53-
7.79-
11.77-
17.23
16.85
19.90
23.14
BLOCK 3
Mean
12.58
11.37
16.37
16.04
SD
4.11
3.21
2.60
3.77
Range
5.94-
5.60-
11.47-
11.77-
19.34
18.34
22.91
25.32
BLOCK 4
Mean
12.29
10.63
16.49
15.94
SD
3.76
3.44
3.22
3.73
Range
6.67-
5.40-
10.96-
11.42-
17.62
17.18
22.71
25.23
BLOCK 5
Mean
12.69
10.06
17.29
16.01
SD
4.34
4.21
3.72
3.91
Range
7.13-
2.02-
8.01-
11.23-
20.34
16.49
22.21
24.98
BLOCK 6
Mean
12.90
10.64
17.51
16.91
SD
4.07
4.75
3.65
3.85
Range
6.70-
2.32-
10.31-
12.39-
19.95
18.69
23.47
26.12
*Measured in seconds on target

TABLE 5
PERFORMANCE OF CONTROL GROUP OVER BLOCKS
127
COMPARISON t df Significance
BLOCK
1
vs.
BLOCK
2
-7.13
32
E <
. 001
BLOCK
2
vs.
BLOCK
3
-4.19
32
E <
.001
BLOCK
3
vs.
BLOCK
4
- . 04
32
ns
BLOCK
4
vs.
BLOCK
5
-1.32
32
ns
BLOCK
5
vs.
BLOCK
6
-1.71
32
ns

TABLE 6
ADHD VS. CONTROL GROUP PERFORMANCE OVER BLOCKS
128
COMPARISON
£
df
Significance
BLOCK 1
-2.79
62
E <
.01
BLOCK 2
-4.87
62
E <
. 001
BLOCK 3
-4.98
62
E <
. 001
BLOCK 4
-5.42
62
E <
. 001
BLOCK 5
-5.19
62
E <
.001
BLOCK 6
-5.33
62
E <
. 001

TABLE 7
REGRESSION MODEL
ATTENTION
Omission errors
Omission errors
IMPULSIVITY
Commission errors
Commission errors
(Cancellation)
(Conditional)
(Cancellation)
(Conditional)
(non-dominant)
Beta £
.004 .03
- . 138
-.070 -.44
-.359 -3.03
-.192 -1.28
.075 .58
FINE MOTOR COORDINATION
Grooved Pegboard
SPATIAL JUDGEMENT
JLO (# correct)
129
E
ns
ns
<.01
ns
ns

130
TABLE 8
CORRELATIONS BETWEEN TIME ON TARGET AND LEARNING INDEX
TOTAL SAMPLE
Block 1
Block 2
Block 3
Block 4
Block 5
Block 6
ADHD GROUP
Block 1
Block 2
Block 3
Block 4
Block 5
Block 6
CONTROL GROUP
Block 1
Block 2
Block 3
Block 4
Block 5
Block 6
r
.14
.46
.57
.64
.71
.80
- . 13
.24
.41
.48
.60
. 71
. 15
.33
.43
.54
. 63
. 75
P
ns
.001
.001
. 001
.001
. 001
ns
ns
ns
.01
. 001
. 001
ns
ns
. 01
. 01
. 001
.001

CHAPTER 8
DISCUSSION
Although children with ADHD are frequently reported to
have poor motor coordination (Barkley, 1990), little
research to date has investigated the mechanisms of this
incoordination. Motor incoordination in children with ADHD
has been attributed to inattention and impulsivity (Pelham
et al. , 1990) . However, children with ADHD have been found
to have abnormalities in both the metabolism (Lou et al.,
1989) and structure (Hynd et al., 1993; Castellanos et al.,
1996) of brain areas associated with both orientation to
stimuli (Rolls & Johnstone, 1992) and the formation of motor
programs (Saint-Cyr, Taylor, Trepanier, & Lang, 1992).
These findings suggested that the incoordination of children
with ADHD is primarily related to deficits in the formation
of motor programs and not only inattention and impulsivity.
131

132
Sample Characteristics
This study examined the development of motor programs
in 7-11 year old children with ADHD compared to normal
controls from the same age group. Prepubertal children were
chosen to avoid maturation effects that may effect motor
learning. The groups were not significantly different by
ethnicity or interpolated Full Scale IQ. There was no
relationship found between motor learning and academic
tutoring received by children; however, children with
learning disorders were excluded from the study. The
control group had a significantly higher socioeconomic
status (Hollingshead, 1975) than the ADHD group.
Socioeconomic status has been reported to have a significant
effect on motor learning, with lower-status children having
more difficulty (Davol & Breakell, 1968), but no effect was
found in this study. Unlike the current study, the previous
research (Davol & Breakell, 1968) did not control for the
effects of disruptive behavior or learning disabilities.
However, it is difficult to draw firm conclusions because
this study contained few subjects in the two lower
socioeconomic classes. The significant difference in gender

133
distribution between the ADHD and control groups had no
significant effect on motor skill acquisition. This was
consistent with research indicating a lack of sex
differences in the motor learning performance of children
(Davol, Hastings, & Klein, 1965; Davol & Breakell, 1968) .
Overall, it appeared that differences on demographic
variables did not have an impact on the results of the
primary task.
Children in the ADHD group were diagnosed by clinicians
outside of this study. However, parent reports were used to
provide behavioral profiles of the two groups and reflected
significantly more inattention, impulsivity, hyperactivity,
and disruptive behavior in the ADHD group compared to the
control group. The differences in behavioral profiles
between groups were expected (Barkley, 1990) and suggested
that children in the ADHD group had been accurately
diagnosed.
Rotary Pursuit Performance
The major hypothesis of this study was that children
with ADHD would have significant difficulty in motor
learning compared to normal controls. Deficits in motor

134
learning stemming from dysfunction in a motor control loop
(Penney & Young, 1986) were expected for the children in the
ADHD/Reward condition compared to both control children in
both conditions. Small rewards were selected for these
children because research has suggested that children with
ADHD may over-anticipate large rewards, attending to the
reward rather than the task (Douglas, 1984; Carlson, Pelham,
Milich, & Dixon, 1992). Children in the ADHD/No Reward
condition were expected to have additional deficits as a
result of inattention and impulsivity. This study used the
pursuit rotor task to measure motor learning, as success on
the pursuit rotor requires the formation, over repeated
trials, of a motor program for keeping the stylus in contact
with the rotating target (Eysenck & Frith, 1977).
Significant differences in pursuit rotor performance
between children with ADHD and controls supported the
hypothesis that children with ADHD have deficits in forming
new motor programs. In spite of the opportunity to practice
the task and individually adjusted rotation speeds, the ADHD
group began the task with a significantly lower time on
target than the control group and failed to demonstrate any
improvement. In contrast to the ADHD group, the control

135
group demonstrated significant learning on the pursuit
rotor, but reached a plateau after the first three blocks.
This finding indicated that the use of fewer blocks in
future research would not significantly impact results and
may make the task less fatiguing for children. Controlling
attention and motivation- through the use of small rewards
had no significant effect on motor learning in either the
ADHD or control groups.
Secondary Analyses
Hypotheses concerning performance on neuropsychological
measures received mixed support. The ADHD group
demonstrated significant impulsivity, or errors of
commission, on both CPT tasks compared to children in the
control group. The ADHD group was not significantly
different from the control group on the percentage of
correctly identified targets or errors of omission, scores
that are believed to measure task-related attention (Corkum
& Siegel, 1993). These results were consistent with earlier
findings indicating that the errors of commission score is
the most effective neuropsychological measure in
discriminating between ADHD children and normal controls

136
(Barkley & Grodzinsky, 1994) and supported the hypothesis
that deficits in response inhibition underlie the symptoms
of ADHD (Douglas, 1984).
There were no significant differences between the ADHD
and control groups in dominant (right) hand fine motor
coordination, but the ADHD group demonstrated deficits in
fine motor coordination with the non-dominant (left) hand.
This did not support the hypothesis of overall deficits in
fine motor coordination in the ADHD group, but was similar
to earlier findings on this task (Barkley & Grodzinsky,
1994). There was no strong support for the hypothesis of
right-hemisphere dysfunction in children with ADHD (Voeller,
1991) . Although results of the fine motor task suggested
right-hemisphere dysfunction, the lack of significant
differences between the ADHD and control groups on
visuospatial judgement, another right-hemisphere task,
prevented the drawing of any firm conclusions.
Errors of commission on the CPT conditional
cancellation task was the only neuropsychological measure
found to be a significant predictor of pursuit rotor
performance for the entire sample. This was consistent with
the hypothesis that impulsivity increases motor learning

137
deficits in children with ADHD. However, this finding was
not significant for either the ADHD or control groups
separately, making interpretation of this finding difficult.
Larger sample sizes in later studies may allow for
confirmation and interpretation of this finding.
There were significant individual differences in the
ability to acquire motor skills. Correlations between the
learning index and time on target for each block indicated
that motor ability and motor learning were separable, as it
was difficult to predict good and bad learners from their
initial performance.
Implications
The current results contradict the suggestion that the
motor difficulties of children with ADHD lie in their
initial processing of task demands, rather than their
ability to form motor programs through practice (Leavell,
Ackerson, & Fischer, 1995) . Methodological differences
between the current study and the study conducted by
Leavell, Ackerson, and Fischer (1995) may help explain the
contradictory findings. In the earlier study, children only
completed five total trials, followed by a single delay

138
trial, rather than the thirty total trials completed in the
current study. This may have limited the opportunity for
development of differences in motor skill acquisition
between the ADHD and control groups. The relatively slow,
uniform speed (15 rpm) used by Leavell, Ackerson, & Fischer
(1995) may have resulted in children reaching a ceiling
performance more quickly than the individually-set speeds
used in the current study. Finally, the relatively
restricted age range used in the current study controlled
for maturation effects that may have influenced earlier
results, as children in the earlier study were aged 6-16
(Leavell, Ackerson, & Fischer, 1995) .
Results of this study provided further evidence that
ADHD symptoms are influenced by developmental differences in
the brains of children with ADHD. The deficits in motor
skill acquisition demonstrated by children with ADHD were
similar to those seen in adult patients with basal ganglia
disease (Heindel, Butters, & Salmon, 1988). Recent research
has suggested that children with ADHD have differences in
the morphometry of the right prefrontal cortex and right
globus pallidus, and a lack of the normal asymmetry seen in
the caudate nucleus (Castellanos et al., 1996). Children

139
with ADHD may also have abnormal development of the caudate
nucleus as they age (Castellanos et al., 1996).
Morphometric differences in prefrontal cortex and basal
ganglia structures may disrupt voluntary control of behavior
(Luria, 1973; Hynd et al., 1993), causing the impulsivity
and inattention seen in children with ADHD.
In addition to effects on attention and behavioral
inhibition, morphological differences in the brains of
children with ADHD may also disrupt a cortical-subcortical
loop responsible for the encoding of motor programs.
Children in the top quartile of pursuit rotor learning were
not significantly different from those in the lowest
quartile on a measure of fine motor coordination. This
suggested that the encoding of motor programs is at least
partially separated from motor response to a novel task.
The hypothetical encoding loop would involve excitatory
projections from cortical association areas that provide
feedback about task requirements to the parts of the basal
ganglia (caudate nucleus and globus pallidus) responsible
for the formation of motor programs (Penney & Young, 1986;
Rolls & Johnstone, 1992) . Inhibitory projections from the
basal ganglia to the thalamus mediate excitatory input from

140
the thalamus to premotor cortex, which is responsible for
the storage and consolidation of information needed for
successful completion of motor tasks. Premotor cortex is
also responsible for the activation of motor responses from
storage (Alexander, Delong, & Strick, 1986; Rolls &
Johnstone, 1992). In patients with basal ganglia disease,
such as Huntington's chorea, this loop is disrupted at the
level of the basal ganglia, resulting in poor encoding of
the necessary motor programs (Heindel, Butters, & Salmon,
1988). If the mechanisms of motor control in ADHD are
similar to those of Huntington's disease, there may be other
neuropsychological similarities between the disorders.
Comparing the neuropsychological profiles of children with
ADHD with those of patients with early Huntington's disease
may provide evidence of any other similarities resulting
from caudate dysfunction.
Dysfunction in motor control systems is consistent with
the hypothesis of a deficit in selecting and modulating
appropriate behavioral responses to stimuli, rather than
underarousal, in children with ADHD (Douglas, 1984).
Underaroused children should be able to generate motor
programs, especially if stimulated by a reward, but children

141
in the ADHD/Reward group failed to demonstrate acquisition
of motor skills. Therefore, it appears that children with
ADHD have problems in generating appropriate behavioral
responses, even when adequately stimulated.
Although the magnitude of the statistically significant
differences between groups in time on target, ranging from
approximately 3 to approximately 7 seconds, did not appear
large, these differences occurred on a relatively simple
gross motor task. The lack of motor learning demonstrated
by children with ADHD on the pursuit rotor would most likely
be magnified by the more complex motor tasks in school or at
play. Lacking the ability to successfully learn motor
tasks, these children may become frustrated and act out,
leading to punishment from parents and teachers. They may
also be excluded from games because of their incoordination,
resulting in lowered self-esteem.
Knowledge of how children with ADHD acquire motor
skills may lead to effective methods of academic remediation
and increase their participation in sports and other games,
thereby improving peer relationships (Szatmari, Offord, &
Boyle, 1989b). Educating parents and teachers about the
motor learning difficulties of children with ADHD may lead

142
to lower frustration in the adults and less conflict between
them and the children with ADHD.
When combined with the impulsive, high-risk behaviors
often engaged in by children with ADHD, incoordination may
make a significant contribution to the higher rate of injury
reported in these children (Farmer & Peterson, 1995) .
Dopaminergic stimulants, such as Ritalin, may bring the
functioning of the cortical-subcortical systems responsible
for response inhibition and motor control closer to normal
levels (Lou et al., 1989). Thus, it is likely that in
addition to decreasing the behavioral symptoms of ADHD,
psychopharmacologic treatment would also improve motor
programming ability.
The number of subjects in this study was limited and
may have reduced the strength of the findings. However, the
effects appeared fairly robust and expansion of this study
with more subjects would help to confirm the current
findings. A larger study would also increase the
interpretability of the multiple regression, and allow for

143
it to be performed separately for both the ADHD and control
groups.
Rewards used in this study were small (baseball cards,
pencils, etc.) and may have been insufficient to maintain
the motivation of the children in the ADHD/Reward group.
Rewards that were somewhat larger than those used in the
current study may have increased the motivation of those
children and enhanced their motor skill acquisition.
Rewards were not varied after a child selected a
reward. Children in the ADHD/Reward group may have
habituated to the reward they selected, reducing its
effectiveness in controlling motivation and attention.
Allowing a group of children to select a novel reward at the
beginning of each block and comparing their performance to
the performance of children receiving unvaried rewards may
control for habituation effects.
The conditions set for obtaining a reward may have also
affected the performance of the children with ADHD. Rewards
were received for maintenance of performance as well as for
improvement. Therefore, the performance of children with
ADHD may have improved if rewards were given only for
improvement.

144
Time on target was the only measure of motor learning
used in this study. The use of error scores may have
provided additional information about the nature of between-
group differences in motor skill acquisition.
The children with ADHD who participated in this study
were diagnosed by several outside clinicians, perhaps
introducing significant variability into the ADHD group.
Individual clinicians may differ somewhat in rating the
symptoms of ADHD and in their criteria for diagnosing the
disorder. Diagnosis by a single clinician would help
control this source of variability in future research.
Summary and Directions for Future Research
This study investigated motor learning in children with
ADHD and the results suggested that as a group, children
with ADHD have significant deficits in acquiring new motor
skills. These deficits appeared to be a result of
dysfunction in forming motor programs, dysfunction that is
likely related to developmental abnormalities in the brains
of children with ADHD. An expansion of the current study
would be to investigate the effect of stimulant medications
on the motor skill acquisition of children with ADHD. If

145
medication were to significantly improve motor skill
acquisition in these children, it would provide supporting
evidence for dysfunction in a cortical-subcortical motor
programming loop. Significantly better motor learning in
medicated children with ADHD would also support the use of
stimulants as an effective intervention for incoordination.
Although the ADHD group as a whole demonstrated
deficits in motor learning, there was some overlap in the
performances of individual children in the ADHD and control
groups. Traditionally, children with ADHD have been
subtyped based on symptoms of inattention, impulsivity, and
hyperactivity. However, these symptoms may be only part of
the picture for some children with ADHD. The wide
variability in individual motor abilities within the ADHD
group suggested that developmental motor problems may
overlay inattention and impulsivity in some children with
ADHD. It may be important to identify the subgroup of ADHD
children with these problems, as they may have additional
difficulties in academic and athletic situations.
Children with a formal diagnosis of learning disability
were excluded from this study, but comorbid learning
disabilities are common in children with ADHD. Research

146
into the motor learning of ADHD-only and ADHD-LD children
may provide information that would further discriminate
between the two groups. Children with ADHD-LD may have a
different pattern of problems in learning complex motor
tasks, given differences in the brain structure of these
children compared to ADHD-only children (Hynd et al., 1990).
As noted above, the differences in motor skill
acquisition between children with ADHD and normal controls
observed in this study may be amplified in more complex
motor tasks. Investigating this hypothesis using computer¬
generated maze tracking or other complex tests of motor
skills may further define the motor learning deficits seen
in this study. Deeper knowledge of the mechanisms of motor
learning in children with ADHD may help to develop a better
understanding of the neural underpinnings of the disorder.

APPENDIX A
BACKGROUND INFORMATION
Please circle the appropriate answer or fill in the blank.
1. What is your relationship to this child?
1= Mother / 2 = Father / 3 = Other (specify)
2. How old is your child?
3. Is your child a BOY (1) or a GIRL (2)
4. Who does the child live with now?
1 = mother and father 4 = mother and stepfather
2 = mother only 5 = father and stepmother
3 = father only 6 = foster parents
7=other
5. How many brothers and sisters does this child have?
6. What is the highest grade you finished?
7. What is the highest grade your spouse finished?
8. Do you have a job? YES NO
If yes, what is your job?
9. Does your spouse have a job? YES NO
If yes, what is your spouse's job?
10. Please estimate your family's current yearly income:
= 0 - 4,999 4 = 15,000 - 19,999 7 = 30,000 - 34,999
= 5,000 - 9,999 5 = 20,000 - 24,999 8 = 35,000 - 39,999
= 10,000 - 14,999 6 = 25,000 - 29,999 9 = over 40,000
1
2
3
147

148
10. What state do you live in?
11. What county in that state?
12. Ethnicity:
l=White (not Hispanic) 4=Asian or Pacific Islander
2=African-American 5=American Indian
3=Hispanic 6=Other
13. Is your child currently placed in a class for Specific
Learning Disabilities (SLD)? YES NO
14. Has your child been diagnosed with a behavior disorder
(Oppositional-Defiant Disorder, Conduct Disorder)?
YES NO IF YES, please specify

APPENDIX B
BEHAVIOR CHECKLIST
Please indicate if your child displays any of the following
behaviors to a degree that (1) is greater than other
children the same age, and (2) causes problems for you, your
child, or for others (e.g., teachers, other children):
YES
NO
1.
Fails to give close attention to details or
makes careless mistakes in schoolwork, work,
or other activities
YES
NO
2 .
Has difficulty sustaining attention in tasks
or play activities
YES
NO
3 .
Does not seem to listen when spoken to
directly
YES
NO
4 .
Does not follow through on instructions and
fails to finish schoolwork, or chores (but
not because of oppositional behavior or
failure to understand instructions)
YES
NO
5.
Has difficulty organizing tasks or activities
YES
NO
6 .
Avoids, dislikes, or is reluctant to engage
in tasks that require sustained mental effort
(such as schoolwork or homework)
YES
NO
7 .
Loses things necessary for tasks or
activities (assignments, toys, pencils,
books)
YES
NO
8.
Easily distracted
YES
NO
9.
Often forgetful in daily activities
149

150
YES
NO
10.
Fidgets with hands or squirms in seat
YES
NO
11.
Leaves seat in classroom or in other
situations when staying seated is expected
YES
NO
12 .
Runs about or climbs excessively in
inappropriate situations
YES
NO
13 .
Has difficulty playing quietly
YES
NO
14 .
Often "on the go" or acts as if "driven by
motor"
YES
NO
15.
Talks too much
YES
NO
16 .
Blurts out answers before questions are
finished
YES
NO
17.
Difficulty taking turns
YES
NO
18 .
Interrupts or intrudes on others

REFERENCES
Achenbach, T.M. (1991). Manual for the Child Behavior
Checklist/4-1 B and 1991 Profile. Burlington, VT:
University of Vermont Department of Psychiatry.
Alessandri, S.M. (1992). Attention, play, and social
behavior in ADHD preschoolers. Journal of Abnormal
Child Psychology. 2Ü, 289-302.
Alessi, M., Hottons, M.D., & Coates, J.K. (1993). The gene
for ADHD? Not yet. Journal of the American Academy of
Child and Adolescent Psychiatry, 1Z, 1073-1074.
Alexander, G.E., DeLong, M.R., & Strick, P.L. (1986).
Parallel organization of functionally segregated
circuits linking basal ganglia and cortex. Annual
Review of Neuroscience. 1, 357-381.
Amen, D.G., Paldi, J.H., & Thisted, R.A. (1993). Brain SPECT
imaging. Journal of the American Academy of Child and
Adolescent Psychiatry, 22, 1080-1081.
American Psychiatric Association. (1968) . Diagnostic and
statistical manual of mental disorders, Second Edition.
Washington, DC: American Psychiatric Association.
American Psychiatric Association. (1980) . Diagnostic and
statistical manual of mental disorders. Third Edition.
Washington, DC: American Psychiatric Association.
American Psychiatric Association. (1987). Diagnostic and
statistical manual of mental disorders. Third Edition,
Revised. Washington, DC: American Psychiatric
Association.
151

152
American Psychiatric Association. (1994). Diagnostic and
Statistical Manual of Mental Disorders. Fourth Edition.
Washington, D.C: American Psychiatric Association.
Anastopoulos, A.D., Guevremont, D.C., Shelton, T.L., &
DuPaul, G.J. (1992). Parenting stress among families of
children with attention deficit hyperactivity disorder.
Journal of Abnormal Child Psychology. 2Ü, 503-520.
Arnold, L.E., Barneby, N.S., & Smeltzer, D.J. (1981). First
grade norms, factor analysis, and cross correlation for
Conners, Davids, and Quay-Peterson rating scales.
Journal of T,earning Disabilities. 14., 269-275.
Atkins, M.S., Pelham, W.E., & Licht, M.H. (1981). A
comparison of objective classroom measures and teacher
ratings of attention deficit disorder. Journal of
Abnormal Child Psychology. 12, 155-167.
Barkley, R.A. (1983). Hyperactivity. In Morris, R.J. &
Kratochwill, T.R. (Eds.) The Practice of Child Therapy,
pp. 87-112. New York: Pergamon Press.
Barkley, R.A. (1990). Attention Deficit Hyperactivity
Disorder: A Handbook for Diagnosis and Treatment. New
York: Guilford Press.
Barkley, R.A., DuPaul, G.J., & McMurray, M.B. (1990).
Comprehensive evaluation of attention deficit disorder
with and without hyperactivity as defined by research
criteria. Journal of Consulting and Clinical
Psychology. 58. 775-789.
Barkley, R.A., Fischer, M., Edelbrock, C.S., & Smallish, L.
(1990). The adolescent outcome of hyperactive children
diagnosed by research criteria, I: An 8 year
prospective follow-up study. Journal of the American
Academy of Child and Adolescent Psychiatry. 22, 546-
557.

153
Barkley, R.A., Fischer, M., Edelbrock, C.S., & Smallish, L.
(1991). The adolescent outcome of hyperactive children
diagnosed by research criteria, III: Mother-child
interactions, family conflicts, and maternal
psychopathology. Journal of Child Psychology and
Psychiatry. 32. 233-255.
Barkley, R.A. & Grodzinsky, G.M. (1994). Are tests of
frontal lobe functions useful in the diagnosis of
attention deficit disorders? The Clinical
Nguropsychologist., a, 121-139.
Barkley, R.A., Grodzinsky, G., & DuPaul, G.J. (1992).
Frontal lobe functions in attention deficit disorder
with and without hyperactivity: A review and research
report. Journal of Abnormal Child Psychology. 23, 163-
188 .
Barrickman, L., Noyes, R., Kuperman, S., Schumacher, E., &
Verda, M. (1991). Treatment of ADHD with fluoxetine: A
preliminary trial. Journal of the American Academy of
Child and Adolescent Psychiatry, la, 762-767.
Benton, A.L., Hamsher, K.deS., Varney, N.R., & Spreen, 0.
(1983). Contributions to Neuropsychological Assessment.
New York: Oxford University Press.
Berry, C.A., Shaywitz, S.E., & Shaywitz, B.A. (1985). Girls
with attention deficit disorder: A silent minority? A
report on behavioral and cognitive characteristics.
Pediatrics. 23, 801-809.
Biederman, J., Faraone, S.V., Keenen, K., Knee, D., &
Tsuang, M.T. (1990). Family-genetic and psychosocial
risk factors in DSM-III attention deficit disorder.
Journal of the American Academy of Child and Adolescent
, 23, 526-533.

154
Biederman, J., Faraone, S.V., Spencer, T., Wilens, T.,
Norman, D., Lapey, K.A., Mick, E., Lehman, B.K., &
Doyle, A. (1993) Patterns of psychiatric comorbidity,
cognition, and psychosocial functioning in adults with
attention deficit hyperactivity disorder. American
Journal of Psychiatry. 150. 1792-1798.
Biederman, J., Wilens, T., Mick, E., Milberger, S., Spencer,
T.J., & Faraone, S.V. (1995). Psychoactive substance
use disorders in adults with Attention Deficit
Hyperactivity Disorder (ADHD): Effects of ADHD and
psychiatric comorbidity. American Journal of
Psychiatry. 152. 1652-1658.
Blouin, A.G., Conners, C.K., Seidel, W.T., & Blouin, J.
(1989) . The independence of hyperactivity from conduct
disorder: Methodological considerations. Canadian
Journal of Psychiatry, 14, 279-282.
Breen, M.J. (1989). Cognitive and behavioral differences in
ADHD boys and girls. Journal of Child Psychology and
Psychiatry. 10, 711-716.
Buhrmester, D., Whalen, C.K., Henker, B., MacDonald, V. , &
Hinshaw, S.P. (1992). Prosocial Behavior in hyperactive
boys: Effects of stimulant medication and comparison
with normal boys. Journal of Abnormal Child Psychology,
10, 103-121.
Cantwell, D.P. & Baker, L. (1991). Association between
Attention Deficit Hyperactivity Disorder and learning
disorders. Journal of Learning Disabilities. H, 88-95.
Cantwell, D.P. & Baker, L. (1992). Attention deficit
disorder with and without hyperactivity: A review and
comparison of matched groups. Journal of the American
Academy of Child and Adolescent Psychiatry. 21, 432-
438 .

155
Carlson, C.L., Pelham, W.E., Milich, R., & Dixon, J. (1992).
Single and combined effects of methylphenidate and
behavior therapy on the classroom performance of
children with attention deficit hyperactivity disorder.
Journal of Abnormal Child Psychology. 211, 213-232.
Carter, C.S., Krener, P., Chaderjian, M., Northcutt, C., &
Wolfe, V. (1995). Asymmetrical visual-spatial
attentional performance in ADHD: Evidence for a right
hemispheric deficit. Biological Psychiatry. 37. 789-
797.
Castellanos, F.X., Giedd, J.N., Marsh, W.L., Hamburger,
S.D., Vaituzis, A.C., Dickstei, D.P., Sarfatti, S.E.,
Vauss, Y.C., Snell, J.W., Lange, N., Kaysen, D., Krain,
A., Ritchie, G.F., Rajapske, J.C., Rapoport, J.L.
(1996). Quantitative Brain Magnetic Resonance Imaging
in Attention-Deficit Hyperactivity Disorder. Archives
Qf. .General Psychiatry, ¿3, 607-616.
Chugani, H.T., Phelps, M.E., & Mazziotta, J.C. (1987).
Positron emission tomography study of human brain
functional development. Annals of Neurology. 22. 487-
497.
Cohen, R.A. (1993). The Neuropsychology of Attention. New
York: Plenum Press.
Conners, C.K. & Delamater, A. (1980). Visual-motor tracking
by hyperkinetic children. Perceptual and Motor Skills.
51. 487-497.
Conners, C.K. & Taylor, E. (1980) . Pemoline,
Methylphenidate, and placebo in children with minimal
brain dysfunction. Archives of General Psychiatry. 22,
922-930.
Corkum, P.V. & Siegel, L.S. (1993). Is the continuous
performance test a valuable research tool for use with
children with attention deficit hyperactivity disorder?
Journal of Child Psychology and Psychiatry. 34. 1217-
1239 .

156
Davol, S.H., & Breakell, S.L. (1968). Sex differences in
rotary pursuit performance of young children: A follow¬
up. Perceptual and Motor Skills. 2£, 1199-1202.
Davol, S.H., Hastings, M.L., Sc Klein, D.A. (1965). Effect of
age, sex, and speed of rotation on rotary pursuit
performance by young children. Perceptual and Motor
Skills. 21, 351-357.
Douglas, V.I. (1983). Attentional and cognitive problems. In
M. Rutter (Ed.), Developmental Neuropsychiatry, pp.
280-328. New York: Guilford Press.
Douglas, V.I. (1984). The psychological processes implicated
in ADD. In L. Bloomingdale (Ed.), Attention Deficit
Disorder: Diagnostic, cognitive, and therapeutic
understanding. pp. 147-162. Jamaica, NY: Spectrum
Publications.
Douglas, V.I., Barr, R.G., Amin, K. , O'Neill, M.E., Sc
Britton, B.G. (1988). Dosage effects and individual
responsivity to methylphenidate in attention deficit
disorder. Journal of Child Psychology and Psychiatry.
29. 453-475.
Douglas, V.I., Barr, R.G., O'Neill, M.E., & Britton, B.G.
(1986). Short term effects of methylphenidate on the
cognitive, learning, and academic performance of
children with attention deficit disorder in the
laboratory and the classroom. Journal of Child
Psychology and Psychiatry. 27, 191-211.
Dulcan, M. (1985) . The psychopharmacologic treatment of
children and adolescents with attention deficit
disorder. Psychiatric Annals. 15, 69-86.
Dunham, Jr., P., Allan, R., & Winter, R. (1985). Tracking
ability of elementary school-age children. Perceptual
and Motor Skills. £2, 771-774.

157
Dupaul, G.J. & Barkley, R.A. (1990). Medication treatment.
In Barkley, R.A. (Ed.), Attention Deficit Hyperactivity
Disorder: A Handbook for Diagnosis and Treatment. New
York: Guilford Press.
DuPaul, G.J., Barkley, R.A., & McMurray, M.B. (1991).
Therapeutic effects of medication on ADHD: Implications
for school psychologists. School Psychology Review. 20.,
203-219.
DuPaul, G.J., Barkley, R.A., & McMurray, M.B. (1994).
Response of children with ADHD to methylphenidate:
Interaction with internalizing symptoms. Journal of the
American Academy of Child and Adolescent Psychiatry,
22, 894-903.
Eysenck, H.J. & Frith, C.D. (1977). Reminiscence.
Motivation, and Personality; A case study in
experimental psychology. New York: Plenum.
Eysenck, H.J. & Thompson, W. (1966). The effects of
distraction on pursuit rotor learning, performance, and
reminiscence. British Journal of Psychology. ¿2, 99-
106 .
Faraone, S.V., Biederman, J., Lehman, B.K., Spencer, T.,
Norman, D., Seidman, L.J., Kraus, I, Perrin, J., Chen,
W.J., & Tsuang, M.T. (1993). Intellectual performance
and school failure in children with attention deficit
hyperactivity disorder and in their siblings. Journal
of Abnormal Psychology. 102. 616-623.
Farmer, J.E. & Peterson, L. (1995). Injury risk factors in
children with Attention Deficit Hyperactivity Disorder.
Health Psychology. 14., 325-332.
Fischer, M., Barkley, R.A., Edelbrock, C.S., & Smallish, L.
(1990). The adolescent outcome of hyperactive children
diagnosed by research criteria, II: Academic,
attentional, and neuropsychological status. Journal of
Consulting and Clinical Psychology. 58, 580-588.

158
Flicek, M. (1992). Social status of boys with both academic
problems and attention deficit hyperactivity disorder.
Journal of Abnormal Child Psychology. 20., 353-366.
Gabrieli, J.D.E., Corkin, S., Mickel, S.F., & Growden, J.H.
(1993). Intact acquisition and long-term retention of
mirror-tracing skill in Alzheimer's disease and global
amnesia. Behavioral Neuroscience. 107, 899-910.
Gillis, J.J., Gilger, J.W., Pennington, B.F., & DeFries,
J.C. (1992). Attention deficit disorder in reading-
disabled twins: Evidence for a genetic etiology.
Journal of Abnormal Child Psychology. 2H, 303-315.
Goodyear, P. & Hynd, G.H. (1992). Attention deficit disorder
with (ADD/H) and without (ADD/WO) hyperactivity:
Behavioral and neuropsychological differences. Journal
of Clinical Child Psychology. 21, 273-305.
Goyette, C.H., Conners, C.K., & Ulrich, R.F. (1978).
Normative data on Revised Conners Parent and Teacher
Rating Scales. Journal of Abnormal Child Psychology.
¿(2), 221-236.
Grodzinsky, G.M. & Diamond, R. (1992). Frontal lobe
functioning in boys with attention deficit
hyperactivity disorder. Developmental Neuropsychology.
1, 427-445.
Halperin, J.M., Newcorn, J.H., Matier, K., Sharma, V.,
McKay, K.E., Schwartz, S. (1993). Discriminant validity
of attention deficit hyperactivity disorder. Journal of
the American Academy of Child and Adolescent
Psychiatry. 32. 1038-1043.
Hartsough, C.S. & Lambert, N.M. (1985). Medical Factors in
hyperactive and normal children: Prenatal,
developmental, and health history findings. American
Journal of Orthopsychiatry. ¿5, 190-201.

159
Haxby, J.V., Grady C.L., Ungerlieder, L.G., & Horwitz, B.
(1991). Mapping the functional neuroanatomy of the
intact human brain with brain work imaging.
Neuropsycho logia â–  22, 539-555.
Heiligenstein, E. & Keeling, R.P. (1995) . Presentation of
unrecognized Attention Deficit Hyperactivity Disorder
in college students. Journal of American College
Health. 41, 226-228.
Heindel, W.C., Butters, N., & Salmon, D.P. (1988). Impaired
learning of a motor skill in patients with Huntington's
disease. Behavioral Neuroscience. 102. 141-147.
Heitman, R.J. & Gilley, W.F. (1989). Effects of blocked
versus random practice by mentally retarded subjects
learning a novel skill. Perceptual and Motor Skills.
69. 443-447.
Hinshaw, S.P. (1992). Academic underachievement, attention
deficits, and aggression: Comorbidity and implications
for intervention. Journal of Consulting and Clinical
Psychology. 60. 893-903.
Horgan, J.S. (1982). Comparison of mildly mentally retarded
and nonretarded children on a rotary pursuit task under
optimal task conditions. American Journal of Mental
Deficiency. 21, 316-324.
Horn, P.W. (1975). Pursuit rotor speed, sex differences, and
reminiscence in young children. The Journal of
Psychology. 91. 81-85.
Hynd, G.W., Hern, K.L., Novey, E.S., Eliopulos, D.,
Marshall, R., Gonzalez, J.J., & Voeller, K.K. (1993).
Attention deficit disorder and asymmetry of the caudate
nucleus. Journal of Child Neurology. 2, 339-347.

160
Hynd, G.W., Nieves, N., Conner, R.T., Stone, P., Town, P.,
Becker, M.G., Lahey, B.B., & Lorys, A. R. (1989).
Attention deficit disorder with and without
hyperactivity: Reaction time and speed of cognitive
processing. Journal of Learning Disabilities. 22, 573-
580.
Hynd, G.W., Semrud-Clikeman, M., Lorys, A.R., Novey, E.S., &
Eliopulos, D. (1990) . Brain morphology in developmental
dyslexia and attention deficit disorder/hyperactivity.
Archives of Neurology. 47â–  919-926.
Hynd, G.W., Semrud-Clikeman, M., Lorys, A.R., Novey, E.S.,
Eliopulos, D., & Lyytinen, H. (1991) Corpus callosum
morphology in attention deficit hyperactivity disorder:
Morphometric analysis of MRI. Journal of Learning
Disabilities. 24, 141-146.
Hynd, G.W., Voeller, K.K., Hern, K. J., & Marshall, R.M.
(1991). Neurobiological basis of attention deficit
hyperactivity disorder (ADHD). School Psycholoay
Review. 2Q., 174-186.
Kataria, S., Wong, M.M., Hall, C.W., & Keys, G.F. (1992).
Learning styles of LD and NLD ADHD children. Journal of
Clinical Psychology. M, 371-378.
Klonoff, H. & Low, M. (1974) Disordered brain function in
young children and early adolescents:
Neuropsychological and electroencephalographic
correlates. In Reitan, R.M. & Davison, L.A., Clinical
neuropsychology: Current status and applications, pp.
121-178. Washington, D.C.; V.H. Winston & Sons.
Kolb, B. & Milner, B. (1981). Performance of complex arm and
facial movements after focal brain lesions.
Neuropsycholoaia. 19. 491-503.
Koziol, L.F. & Stout, C.E. (1992). Use of a verbal fluency
measure in understanding and evaluating ADHD as an
executive function disorder. Perceptual and Motor
Skills. 23, 1187-1192.

161
Lahey, B.B., Pelham, W.E., Schaughency, E.A., Atkins, M.S.,
Murphy, A., Hynd, G., Russo, M., Hartdagen, S., &
Lorys-Vernon, A. (1988) . Dimensions and types of
attention deficit disorder. Journal of the American
Academy of Child and Adolescent Psychiatry. 22, 330-
335 .
Lahey, B.B., Schaughency, E.A., Frame, C.L., & Strauss, C.C.
(1985). Teacher ratings of attention problems in
children experimentally classified as exhibiting
attention deficit disorders with and without
hyperactivity. Journal of the American Academy of Child
and Adolescent Psychiatry. 24., 613-616.
Lahey, B.B., Schaughency, E.A., Hynd, G.W., Carlson, C.L., &
Nieves, N. (1987). Attention deficit disorder with and
without hyperactivity: Comparison of behavioral
characteristics of clinic-referred children. Journal of
the American Academy of Child and Adolescent
Psychiatry. 2£, 718-723.
Leavell, C.A., Ackerson, J.D., & Fischer, R.S. (1995).
Procedural learning difficulties in children with
attention and/or overactivity: Is it motor skill or
motor acquisition? Paper presented at the Annual
Meetings of the International Neuropsychological
Society (INS); Seattle, WA.
Leonard, G. & Milner, B. (1991a). Contribution of the right
frontal lobe to the encoding and recall of kinesthetic
distance information. Neuropsvcholoaia. 29. 47-58.
Leonard, G. & Milner, B. (1991b). Recall of the end-position
of examiner-defined arm movements by patients with
frontal-or temporal-lobe lesions. Neuroosvrhnloaia. 29.
629-640.
Leonard, G., Milner, B., & Jones, L. (1988). Performance on
unimanual and bimanual tapping tasks by patients with
lesions of the frontal or temporal lobe.
Neuropsvcholoaia. 26. 79-91.

162
Lezak, M.D. (1983). Neuropsychological assessment - Third
Edition. New York: Oxford University Press.
Loge, D.V., Staton, D., & Beatty, W.W. (1990). Performance
of children with ADHD on test sensitive to frontal lobe
dysfunction. Journal of the American Academy of Child
and Adolescent Psychiatry. 21, 540-545.
Lord, R. & Hulme, C. (1988) . Patterns of rotary pursuit
performance in clumsy and normal children. Journal of
Child Psychology and Psychiatry, 21, 691-701.
Lou, H.C., Henrikson, L., & Bruhn, P. (1990). Focal cerebral
dysfunction in developmental learning disabilities.
Lancet. 335. 8-11.
Lou, H.C., Henrikson, L., Bruhn, P., Borner, H., & Bieber-
Nielson, J. (1989). Striatal dysfunction in attention
deficit and hyperkinetic disorder. Archives of
Neurology. 46. 48-52.
Luria, A.R. (1973). The Working Brain. New York: Basic
Books.
Mannuzza, S., Klein, R.G., Bessler, A., Malloy, P., &
LaPadula, M. (1993). Adult outcome of hyperactive boys.
Archives of General Psychiatry, 20, 565-576.
McBride, D.K. & Payne, R.B. (1980). The sex difference in
rotary pursuit performance: Aptitude or inhibition?
Journal of Motor Behavior. 12, 270-280.
McGee, R. & Share, D.L. (1988). Attention deficit
hyperactivity disorder and academic failure: Which
comes first and what should be treated? Journal of the
American Academy of Child and Adolescent Psychiatry.
27, 318-325.
Milberger, S., Biederman, J., Faraone, S.V., Murphy, J., &
Tsuang, M.T. (1995). Attention deficit hyperactivity
disorder and comorbid disorders: Issues of overlapping
symptoms. American Journal of Psychiatry. 152, 1793-
1799 .

163
Milner, B. & Kolb, B. (1985). Performance of complex arm
movements and facial movement sequences after cerebral
commissurotomy. Neuropsycholoaia. 23. 791-799.
Mirsky, A.F., Anthony, B.J., Duncan, C.C., Ahearn, M.B., &
Kellam, S.G. (1991). Analysis of the elements of
attention: A neuropsychological approach.
Neuropsychology Review. 2, 109-145.
Mitchell, E.A., Aman, M.G., Turbott, S.H., & Manku, M.
(1987) . Clinical Pediatrics. 2fL, 406-411.
Ott, D.A. & Lyman, R.D. (1993). Automatic and effortful
memory in children exhibiting attention deficit
hyperactivity disorder. Journal, of Child Clinical
Psychology. 22, 420-427.
Pelham, W.E., Atkins, M.S., & Murphy, H.A. (1981). Attention
deficit disorder with and without hyperactivity:
definitional issues and correlates. In W. Pelham (ed.)
DSM-III Category of Attention Deficit Disorders:
Rationale. Operationalization, and Correlates. Los
Angeles: American Psychological Association.
Pelham, W.E., Harper, G.W., McBurnett, K., Milich, R.,
Murphy, D.A., Clinton, J., & Thiele, C. (1990).
Methylphenidate and baseball playing in ADHD children:
Who's on first? Journal of Consulting and Clinical
Psychology. ££., 130-133.
Penney, J.B. & Young, A.B. (1986). Striatal inhomogeneities
and basal ganglia function. Movement Disorders. 1, 3-
15.
Pennington, B.F., Groisser, D., & Welsh, M.C. (1993).
Contrasting cognitive deficits in attention deficit
hyperactivity disorder versus reading disability.
Developmental Psychology. 22, 511-523.
Posner, M.I. (1992). Attention as a neural and cognitive
system. Current Directions in Psychological Science.
11-14.

164
Power, T.J. (1992) Contextual factors in vigilance testing
of children with ADHD. Journal of Abnormal Child
Psychology. 20, 579-593.
Quay, R.C. & Peterson, D.R. (1983). Interim Manual for the
Revised Behavior Problem Checklist. Available from
Herbert C. Quay. Box 248074, University of Miami, Coral
Gables, FL 33124.
Rapport, M.D., Denney, C., DuPaul, G.J., & Gardner, M.J.
(1994). Attention deficit disorder and methylphenidate:
Normalization rates, clinical effectiveness, and
response prediction in 76 children. Journal of the
American Academy of Child and Adolescent Psychiatry,
i!, 882-893.
Rider, R.A. & Abdulahad, D.T. (1991). Effects of massed
versus distributed practice on gross and fine motor
proficiency of educable mentally handicapped
adolescents. Perceptual and Motor Skills. 73. 219-224.
Roizen, N.J., Blondis, T.A., Irwin, M., Rubinoff, A.,
Kieffer, J., & Stein, M.A. (1996). Psychiatric and
developmental disorders in families of children with
attention-deficit hyperactivity disorder. Archives of
Pediatric and Adolescent Medicine, 150, 203-208.
Rolls, E.T. & Johnstone, S. (1992). Neurophysiological
analysis of striatal function. In Vallar, G., Cappa,
S.F., & Wallesch, C-W. (Eds.) Neuropsychological
Disorders Associated with Subcortical Lesions, pp. 61-
97. New York: Oxford University Press.
Ross, R.G., Hommer, D., Breiger, D., Varley, C., & Radant,
A. (1994). Eye movement task related to frontal lobe
functioning in children with attention deficit
disorder. Journal of the American Academy of Child and
Adolescent Psychiatry. ¿1, 869-874.
Ruffer, W.A. (1984). Comparisons of four psychomotor tasks:
Grade and sex of elementary school children. Perceptual
and Motor Skills. 58, 323-328.

165
Saint-Cyr, J.A., Taylor, A.E., Trepanier, L.L., & Lang, A.E.
(1992). The caudate nucleus: Head ganglion of the habit
system. In Vallar, G., Cappa, S.F., & Wallesch, C-W.
(Eds.) Neuropsychological Disorders Associated with
Subcortical Lesions, pp. 61-97. New York: Oxford
University Press.
Sattler, J.M. (1992). Assessment of Children: Third Edition-
Expanded and Revised. San Diego: Jerome M. Sattler.
Schachar, R.J., Tannock, R., & Logan, G. (1993) . Inhibitory
control, impulsiveness, and attention deficit
hyperactivity disorder. Clinical Psychology Review, 13.,
721-739.
Seidman, L.J., Biederman, J., Faraone, S.V., Milberger, S.,
Norman, D., Seiverd, K., Benedict, K., Guite, J., Mick,
E., Kiely, K. (1995). Effects of family history and
comorbidity on the neuropsychological performance of
children with ADHD: Preliminary findings. Journal of
the American Academy of Child and Adolescent,
Psychiatry. 24, 1015-1924.
Semrud-Clikeman, M., Biederman, J., Sprich-Buckminster S.,
Krichfer-Lehman, B., Faraone, S.V., & Norman, D.
(1992). Comorbidity between ADDH and learning
disability: A review and report in a clinically
referred sample. Journal of the American Academy of
Child and Adolescent Psychiatry. 11, 439-448.
Semrud-Clikeman, M., Filipek, P.A., Biederman, J.,
Steingard, R., Kennedy, D., Renshaw, P, Bekken, K.
(1994). Attention-deficit hyperactivity disorder:
Magnetic resonance imaging morphometric analysis of the
corpus callosum. Journal of the American Academy of
Child and Adolescent Psychiatry. 21, 875-881.
Shaw, G.A. Sc Giambra, L. (1993) . Task-unrelated thoughts of
college students diagnosed as hyperactive in childhood.
Developmental Neuropsychology. 2, 17-30.

166
Shue, K.L. & Douglas, V.I. (1992). Attention deficit
hyperactivity disorder and the frontal lobe syndrome.
Brain and Cognition. 20. 104-124.
Simenson, R.J. (1973). Acquisition and retention of a motor
skill by normal and retarded students. Perceptual and
Motor Skills. 2l£l, 791-799.
Simeon, J.G. & Wiggins, D.M. (1993). Pharmacotherapy of
attention deficit hyperactivity disorder. Canadian
Journal of Psychiatry. 443-448.
Smith, M.L. (1988). Recall of spatial location by the
amnesic patient H.M. Brain and Cognition. 2, 178-183.
Spreen, O., Tupper, D., Risser, A., Tuokko, H., & Edgell, D.
(1984) . Human Developmental Neuropsychology. New York:
Oxford Press.
Still, G.F. (1902). Some abnormal psychical conditions in
children. Lancet. i, 1008-1012, 1077-1082, 1163-1168.
Swanson, J.M., Cantwell, D., Lerner, M., McBurnett, K., &
Hanna, G. (1991). Effects of stimulant medication on
learning in children with ADHD. Journal of Learning
Disabilities. 24., 219-230.
Szatmari, P., Offord, D.R., & Boyle, M.H. (1989a). Ontario
Child Health Study: Prevalence of attention deficit
disorder with hyperactivity. Journal of Child
Psychology and Psychiatry, 2J2, 219-230.
Szatmari, P., Offord, D.R., & Boyle, M.H. (1989b).
Correlates, associated impairments, and patterns of
service utilization of children with attention deficit
disorder: Findings from the Ontario Child Health Study.
Journal of Child Psychology and Psychiatry, M, 205-
217.
Trites, R.L., Blouin, A.G.A., & Laprade, K. (1982). Factor
analysis of the Conners Teacher Rating Scale based on a
large normative sample. Journal of Consulting and
Clinical Psychology, ¿2,(5), 615-623.

167
Trites, R.L., Dugas, E., Lynch, G., & Ferguson, H.B. (1979).
Prevalence of hyperactivity. Journal of Pediatric
Psychology. 4(2), 179-188.
Voeller, K.K.S. (1986). Right hemisphere deficit syndrome in
children. American Journal of Psychiatry. 143. 1004-
1009.
Voeller, K.K.S. (1991). What can neurological models of
attention, intention, and arousal tell us about
attention deficit hyperactivity disorder? Journal of
Neuropsychiatry. 2, 209-216.
Voeller, K.K.S. & Heilman, K.M. (1988a). Attention deficit
disorder in children: A neglect syndrome? Neurology.
38. 806-808.
Voeller, K.K.S. & Heilman, K.M. (1988b). Motor impersistence
in children with attention deficit hyperactivity
disorder: Evidence for right hemisphere dysfunction.
Annals of Neurology. 2A, 323.
Watson, R.T., Valenstein, E., & Heilman, K.M. (1981).
Thalamic neglect: Possible role of the medial thalamus
and nucleus reticularis in behavior. Neurology. 38.
501-506 .
Wechsler, D. (1991). Manual for the Wechsler Intelligence
Sc&le for.children-Third Edition. New York:
Psychological Corporation.
Weinberg, W.A. & Harper, C.R. (1993) . Vigilance and its
disorders. Neurologic Clinics. 11. 59-78.
Wek, S.R. & Husak, W.S. (1989). Distributed and massed
practice effects on motor performance and learning of
autistic children. Perceptual and Motor Skills. M,
107-113.
Wells, K.C. & Forehand, R. (1985). Conduct and oppositional
disorders. In P.H. Bornstein & A.E. Kazdin (Eds.),
Handbook of clinical behavior therapy with children
(pp. 218-265). Homewood, IL: Dorsey.

168
Yeates, K.O. & Bornstein, R.A. (1994). Attention deficit
disorder and neuropsychological functioning in children
with Tourette's syndrome. Neuropsychology. £, 65-74.
Zametkin, A.J., Liebenauer, L.L., Fitzgerald, G.A., King,
A.C., Minkunas, D.V., Herscovitch, P., Yamada, E.M., &
Cohen, R.M. (1993). Brain metabolism in teenagers with
attention deficit hyperactivity disorder. Archives of
General Psychiatry. £Q, 333-340.
Zametkin, A.J., Nordahl, T.E., Gross, M., King, A.C.,
Semple,W.E., Rumsey, J., Hamburger, S., & Cohen, R.M.
(1990). Cerebral glucose metabolism in adults with
hyperactivity of childhood onset. The New England
Journal of Medicine. 321, 1361-1366.

BIOGRAPHICAL SKETCH
I graduated high school in 1983 and received a National
Merit Scholarship from the Ohio State University. While at
Ohio State, I majored in Psychology and graduated in 1987
with a Bachelor of Arts degree. I was employed for two
years in Columbus, Ohio, as a Licensed Social Worker,
working with adolescents and their families. In order to
receive further training, I applied to graduate school and
was accepted into the clinical psychology program at the
University of Florida. Under the supervision of Dr. Sheila
Eyberg, I completed a restandardization of the Eyberg Child
Behavior Inventory and received my Master's degree in 1994.
I developed an interest in pediatric neuropsychology while
in graduate school and Dr. Fennell's supervision has helped
me gain more knowledge of this area. I completed an
internship in clinical neuropsychology at Columbia-
Presbyterian Medical Center in June, 1996, and will begin
post-doctoral training at the Columbus, Ohio, Children's
Hospital in September, 1996.
169

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
("3.
Eileen B. Fennell, Chair
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Sheila M. Eyberg \
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Stephen R. Boggs
Associate Professor of
Clinical and Health
Psychology

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
cu
•
rM
f4>^
rynnhia Griffin
Kssgpiate Profes
—^
i^or o
&
f
Special Education
This dissertation was submitted to the Graduate Faculty
of the College of Health Professions and to the Graduate
School and was accepted as partial fulfillment of the
requirements for the degree of Doctor of Philosophy.
December, 1996
Dean, College of Health
Professions
Dean, Graduate School




48
hours (DuPaul & Barkley, 1990). However, slow-release
preparations may take significantly longer to affect
behavioral change following dose administration (DuPaul,
Barkley, & McMurray, 1991) and behavioral effects may not
last as long as with a small afternoon dose of normal-acting
Ritalin (Simeon & Wiggins, 1993).
Side effects of stimulant medication can include
decreased appetite, insomnia, anxiety, and irritability
(DuPaul, Barkley, & McMurray, 1991). An afternoon increase
in ADHD behaviors is also common in children with ADHD who
take medication during the day. The lack of normal growth
is frequently seen in children with ADHD who are taking
stimulant medication and Dexedrine has been found to have a
more deleterious effect on growth than other stimulants
(Dulcan, 1985). Duration of treatment and amount of
appetite suppression appear to be important factors
affecting the child's growth, and this effect can be
modulated with drug holidays (Dulcan, 1985). Development of
motor tics is a relatively rare side effect and it can
difficult to predict, but a family history of motor
syndromes is a contraindication to stimulant treatment. As
with any pharmacologic treatment, a careful history should


117
(62) = -1.55, ns; Table 3). No significant difference was
found between the groups on Grooved Pegboard performance
with the dominant (right) hand <£. (62) = 1.29, ns) The
ADHD group was significantly slower than the control group
with the non-dominant (left) hand (t = 2.23, p = .03; Table
3). No significant difference was found between the groups
on the spatial orientation task (p (62) = -1.34, ns; Table
3) .
Analyses of Pursuit Rotor Performance
Overview
To control for the intertrial variability in time on
target evident among the children with ADHD, the median
score for each block was used as the primary measure of
performance for each individual. Individual median scores
were then collapsed across each group to provide a mean
score for group performance on each block. Means, standard
deviations, and ranges for the four experimental groups
(ADHD/Reward, ADHD/No Reward, Control/Reward, Control/No
Reward) on all blocks are displayed in Table 4. There was
no significant effect for group on rotation speed (E (3,60)


69
Neuropsychological ..Testing of Children with ADHD
Although frontal lobe dysfunction has long been
implicated in ADHD, formal testing of frontal lobe functions
produced inconsistent results (Barkley & Grodzinsky, 1994).
Some studies have found few differences between children
with ADHD and normal controls on tests of frontal lobe
functioning (Loge, Staton & Beatty, 1990), but this study
analyzed distractibility and vigilance tasks separately from
other tests of frontal lobe functioning. When those tests
were analyzed, it was concluded that ADHD children had
difficulty in directing and sustaining attention, a function
localized to the right parietal lobe (Posner, 1992).
However, subjects in this study may have had developmental
learning disabilities and parietal dysfunction unrelated to
their attention problems (Grodzinsky & Diamond, 1992).
Other authors indicated that symptoms of ADHD resemble
frontal lobe deficits, with subcortical involvement (Barkley
Sc Grodzinsky, 1994) Vigilance tests like the CPT are more
often used to measure frontal lobe function, rather than
parietal lobe function (Loge, Staton, & Beatty, 1990), in
children with ADHD, as inhibition and voluntary attention


75
environmental stimulation, filter those sensations, and
initiate a response appeared to be within normal limits.
This provided support for the importance of self-regulatory
deficits in these children (Douglas, 1983). Children with
ADHD also appeared to have a normal attentional capacity, as
measured by overall intellectual ability (Cohen, 1993).
Their ability to encode information, a function subserved by
the hippocampus and amygdala, was found to be normal (Ott &
Lyman, 1993) .
The mesencephalic reticular formation is involved in
the arousal states necessary for attention (Watson,
Valenstein, & Heilman, 1981). Arousal can be defined as the
physiological readiness to attend to incoming stimulation
(Cohen, 1993). The reticular formation is believed to
modulate the function of the nucleus reticularis, which
influences the screening of sensory information by the
thalamus, and results in selective activation of cortical
areas (Watson, Valenstein, & Heilman, 1981). The ability to
sustain attention is mediated by the activation of these
structures, as they control the flow of sensory information
to higher cortical structures (Mirsky et al., 1991).
Cortical areas that play a role in the "higher" forms of


38
control children (Barkley, Fischer, Edelbrock, & Smallish,
1990). Married mothers of children with ADHD rated their
marriages as less satisfying than mothers of control
children {Barkley, Fischer, Edelbrock, & Smallish, 1991).
Family conflict was significantly more frequent in the
lives of children with ADHD than in children without
attention problems (Barkley, Fischer, Edelbrock, & Smallish,
1991). Mothers of ADHD children rated their family
environment as extremely stressful, with the impulsivity and
hyperactivity of the child playing an important role in
exacerbating this stress (Anastopoulos, Guevremont, Shelton,
& DuPaul, 1992). Aggressiveness in a child with ADHD added
to this stress, and comorbid oppositional-defiant disorder
led to higher levels of parenting stress than ADHD alone.
Health problems in childhood, often a characteristic of ADHD
(Hartsough & Lambert, 1985), was the final child-related
stressor identified in parents of children with ADHD
(Anastopoulos, Guevremont, Shelton, & DuPaul, 1992). These
findings were similar to parent ratings of the behavior of
adolescents with ADHD, who continue to have conflicts with
family members (Barkley, Fischer, Edelbrock, & Smallish,
1991). Although ADHD symptoms appeared to have an


90
sequencing of movements that is affected (Milner & Kolb,
1985) .
Frontal lobe lesions affected performance of sequential
tapping tasks (Leonard, Milner, & Jones, 1988). When the
coordination of both hands was required, subjects with
frontal lobe lesions had the greatest difficulty relative to
normal controls and subjects with temporal lobe lesions.
Subjects with left frontal lesions performed worse than
those with right frontal lesions. Subjects with temporal
lobe lesions demonstrated difficulties similar to frontal
lobe subjects on a sequenced tapping task using only one
hand. This result may have been influenced by task demands,
as speed rather than coordination was important in the one-
handed tapping task, and there is a general slowing of motor
speed in most cases of brain injury (Leonard, Milner, &
Jones, 1988) .
The importance of right frontal lobe involvement in
movement has been demonstrated. Subjects with large right
frontal lesions have significant difficulty in recalling the
distance of arm movements (Leonard & Milner, 1991a). This
deficit was seen without regard to interference tasks, an
indicator that the right frontal lobe is involved in the


78
structured format (Ott & Lyman, 1993). Their free recall of
the pictures, which required self-generated organization of
information for output, was significantly worse than normal
controls (Ott & Lyman, 1993). Impulsivity and
distractibility are considered to be modulated by
frontal/executive functions (Voeller, 1991). ADHD children
have been found to have difficulties inhibiting responses to
one stimulus and then reengaging attention on second
stimulus, also considered to be a frontal/executive function
(Schachar, Tannock, & Logan, 1993).
Explanation for the inability of children with ADHD to
shift attention is probably not limited to frontal/executive
dysfunction (Yeates & Bornstein, 1994) Research has
suggested that a loop involving the caudate nucleus,
thalamus, and cortical areas is involved in ADHD (Yeates &
Bornstein, 1994). The frontal lobe-caudate nucleus
interconnection appeared to be important for regulation of
directed attention (Mirsky, et al., 1991) and modulation of
responses (Cohen, 1993). Dysfunction in frontal-caudate
systems may be involved in deficits of response inhibition
and motor overactivity (Voeller, 1991). When subjects are
asked to perform tasks with a substantial attentional


58
by children with ADHD when they learn any novel skill
(Leavell, Ackerson, & Fischer, 1995).


11
1987). In fact, research has indicated that children with
ADD/H were referred to clinics one year earlier than
children with ADD/WO (Goodyear & Hynd, 1992), and clinic
referrals of ADD/H children resulted from their disruptive
behaviors (Cantwell & Baker, 1992). ADD/WO children were
more likely to be referred for academic difficulties and
depression, symptoms that could be secondary to attention
deficits (Cantwell & Baker, 1992).
Children with ADD/WO have been rated by their teachers
as having a slower cognitive tempo, or speed of problem
solving (Lahey et al. 1987; Lahey, Schaughency, Frame, &
Strauss, 1985). Other researchers have described these
children as daydreamy, confused, and lost in thought
(Barkley, DuPaul, & McMurray, 1990). Symptoms of
internalizing behavior problems, such as anxiety,
depression, and obsessive-compulsive behaviors, were found
in children with ADD/WO by (Lahey et al., 1987), a result
confirmed in later studies (Barkley, DuPaul, & McMurray,
1990). Children with ADD/H had significantly more overt
conduct problems, but the two groups did not have
significant differences in the number of covert problems
such as lying and truancy.


146
into the motor learning of ADHD-only and ADHD-LD children
may provide information that would further discriminate
between the two groups. Children with ADHD-LD may have a
different pattern of problems in learning complex motor
tasks, given differences in the brain structure of these
children compared to ADHD-only children {Hynd et al., 1990).
As noted above, the differences in motor skill
acquisition between children with ADHD and normal controls
observed in this study may be amplified in more complex
motor tasks. Investigating this hypothesis using computer
generated maze tracking or other complex tests of motor
skills may further define the motor learning deficits seen
in this study. Deeper knowledge of the mechanisms of motor
learning in children with ADHD may help to develop a better
understanding of the neural underpinnings of the disorder.


67
The prefrontal regions of adults and children with ADHD
may deactivate when challenged with a simple attention task
(Amen, Paldi, & Thisted, 1993) Children with ADHD who
failed to demonstrate reduced prefrontal activity during an
intellectual task already had a lower resting metabolic rate
in that area. Prefrontal cortex controls attention,
concentration, problem-solving abilities and judgment (Amen,
Paldi, Thisted, 1993). Planning and execution of motor
activities are also functions of this part of the brain
(Zametkin et al., 1990). It is possible that the motor
incoordination seen in ADHD children is a result of abnormal
functioning in the prefrontal areas and in the subcortical
structures connected to it.
Issue? oL Subject- Selection
The outcome of morphological and physiological studies
may be influenced by the inclusion of children with ADHD and
a comorbid diagnosis, especially a learning disability.
Although the right frontal cortices of both ADHD and
dyslexic children were significantly smaller than in normal
controls, dyslexic children differed from ADHD children in
the size of other brain regions (Hynd et al., 1990). The


indicated that it may be significantly smaller in children
with ADHD than in normal controls (Hynd et al., 1991), but
62
later studies using more sophisticated imaging equipment
contradicted this finding (Semrud-Clikeman et al., 1994).
The genu was smaller in children with ADHD who were
unresponsive to stimulant medication, but there were not
enough subjects for a statistical analysis (Semrud-Clikeman
et al., 1994). The genu contains fibers connecting the
prefrontal, orbitofrontal, and premotor cortices, and
although measures of callosal size may not accurately
reflect the number of interhemispheric fibers, a smaller
genu may be responsible for disruption in motor control and
behavioral inhibition systems (Hynd et al., 1991).
Posterior sections of the corpus callosum, the splenium and
the area just anterior to it, were also found to be smaller
in children with ADHD (Hynd et al., 1991; Semrud-Clikeman et
al., 1994). This may explain the difficulties ADHD children
have in attending to sensory information (Semrud-Clikeman et
al., 1994), although other research has suggested that the
sensory areas in these children may be overactive (Lou et
al, 1989), rather than the reverse.


156
Davol, S.H., & Breakell, S.L. (1968). Sex differences in
rotary pursuit performance of young children: A follow
up. Perceptual and Motor Skills. 2£, 1199-1202.
Davol, S.H., Hastings, M.L., & Klein, D.A. (1965). Effect of
age, sex, and speed of rotation on rotary pursuit
performance by young children. Perceptual and Motor
Skills, 21, 351-357.
Douglas, V.I. (1983). Attentional and cognitive problems. In
M. Rutter (Ed.), Developmental Neuropsychiatry, pp.
280-328. New York: Guilford Press.
Douglas, V.I. (1984). The psychological processes implicated
in ADD. In L. Bloomingdale (Ed.), Attention Deficit
Disorder: Diagnostic, cognitive, and therapeutic
understanding, pp. 147-162. Jamaica, NY: Spectrum
Publications.
Douglas, V.I., Barr, R.G., Amin, K., ONeill, M.E., &
Britton, B.G. (1988). Dosage effects and individual
responsivity to methylphenidate in attention deficit
disorder. Journal of Child Psychology and Psychiatry.
29, 453-475.
Douglas, V.I., Barr, R.G., O'Neill, M.E., & Britton, B.G.
(1986). Short term effects of methylphenidate on the
cognitive, learning, and academic performance of
children with attention deficit disorder in the
laboratory and the classroom. Journal of Child
Psychology and Psychiatry, 27, 191-211.
Dulcan, M. (1985). The psychopharmacologic treatment of
children and adolescents with attention deficit
disorder. Psychiatric Annals. 12, 69-86.
Dunham, Jr., P., Allan, R.# & Winter, R. (1985). Tracking
ability of elementary school-age children. Perceptual
and Motor Skills. M, 771-774.


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47
abnormally low metabolic rates in the striatal and
periventricular regions of these children (Lou et al, 1989).
The other stimulant medications apparently have similar
effects, although Cylert has been found to be slightly less
effective in moderating the behavior of ADHD children
(Conners & Taylor, 1980). Cylert is slower to act than
Ritalin, often requiring 3 to 4 weeks to have a therapeutic
effect (Dulcan, 1985) and it has a longer half-life,
averaging 12 hours, as opposed to 2 to 3 hours for Ritalin
(DuPaul & Barkley, 1990). The behavioral effects of Ritalin
and Dexedrine last around 4 hours (Dulcan, 1985), while
these effects are seen for up to 2 weeks after ending
administration of Cylert (Conners & Taylor, 1980). Ritalin
does not accumulate in the system (Dulcan, 1985), and no
traces of this drug are found in the urine after 12 hours
(DuPaul, Barkley, & McMurray, 1991) Slow-release forms of
Ritalin (methylphenidate SR) are commonly prescribed,
especially when administration of medication during the
school day (DuPaul, Barkley, & McMurray, 1991) or after
school behavior (Simeon & Wiggins, 1993) are concerns.
Slow-release forms of Ritalin have plasma half-lives ranging
from 2 to 6 hours and behavioral effects that last up to 8


122
Simple linear regression was performed with both the
ADHD and control groups to further define the relationship
of the CPT conditional cancellation errors and the pursuit
rotor learning index. A trend was found towards a
relationship between these variables for the ADHD group
(Beta = -.34, £. (29) = -1.95, p = .06). No significant
relationship between the two variables was found for the
control group (Beta = -.06, £ (31) = -.32, ns).
Additional Analyses
As there was a wide range of performance (Table 4), the
relationship between time on target for each pursuit rotor
block and motor skill acquisition was examined. Pearson r's
were calculated for correlations between the median time on
target for each block and the learning index. Correlations
became progressively stronger for the entire sample, with an
insignificant correlation found between Block 1 and the
learning index, but positive correlations of moderate to
high significance found in later blocks (Table 8). A
similar progression in positive correlation strength was
found for the ADHD and control groups when that data was
analyzed separately (Table 8). A Pearson correlation found


43
order to fully evaluate a child's behavior. Checklists
require raters to report frequencies of various problem
behaviors in children and these ratings are then combined to
produce a profile of the child's behavior. The Conners
rating scales have been shown to be a valid measure of
hyperactive and inattentive behaviors (Trites, Blouin, &
Laprade, 1982). Children with ADHD tended to score highly
on the Externalizing Behaviors scale of the CBCL (Barkley,
1990) because of their overactivity and disruptive
behaviors.
It has been hypothesized that deficits in self
regulation underlie the symptoms of ADHD (Douglas, 1983).
Poor self-regulation can be defined by four behavioral
components characteristic of children with ADHD (Douglas,
1984). An unusual need for immediate gratification, an
unwillingness to invest effort in demanding tasks, an
inability to inhibit impulsive responses, and a lack of
arousal modulation have all been found in children with
ADHD. The lack of self-regulation in ADHD children has a
number of effects on behavior. These children fail to
utilize knowledge and skills they are known to possess, an
inconsistency in performance often noted by teachers


163
Milner, B. & Kolb, B. (1985). Performance of complex arm
movements and facial movement sequences after cerebral
commissurotomy. Neuropsychologia. 22, 791-799.
Mirsky, A.F., Anthony, B.J., Duncan, C.C., Ahearn, M.B., &
Kellam, S.G. (1991) Analysis of the elements of
attention: A neuropsychological approach.
Neuropsychology Review. 2, 109-145.
Mitchell, E.A., Aman, M.G., Turbott, S.H., & Manku, M.
(1987). Clinical Pediatrics. 21, 406-411.
Ott, D.A. & Lyman, R.D. (1993). Automatic and effortful
memory in children exhibiting attention deficit
hyperactivity disorder. Journal, of Child Clinical
Psychology, 22, 420-427.
Pelham, W.E., Atkins, M.S., & Murphy, H.A. (1981). Attention
deficit disorder with and without hyperactivity:
definitional issues and correlates. In W. Pelham (ed.)
p$M-m Category of Attention Deficit Disorders;
Rationale. Operationalization, and Correlates. Los
Angeles: American Psychological Association.
Pelham, W.E., Harper, G.W., McBurnett, K., Milich, R.,
Murphy, D.A., Clinton, J., & Thiele, C. (1990).
Methylphenidate and baseball playing in ADHD children:
Who's on first? Journal of Consulting and Clinical
Psychology, 2, 130-133.
Penney, J.B. & Young, A.B. (1986). Striatal inhomogeneities
and basal ganglia function. Movement, Disorders. 1, 3-
15.
Pennington, B.F., Groisser, D., & Welsh, M.C. (1993).
Contrasting cognitive deficits in attention deficit
hyperactivity disorder versus reading disability.
Developmental Psychology, 22, 511-523.
Posner, M.I. (1992). Attention as a neural and cognitive
system. Current Directions in Psychological Science.
11-14.


the entire sample suggested that impulsivity may be a
significant predictor of pursuit rotor performance, but this
was not found for either group separately. The motor
programming deficits found in the children with ADHD were
discussed in terms of their relationship to neural
structures.
viii


92
mechanisms for motor skills learning are separate from other
memory systems (Gabrieli, Corkin, Mickel, & Growdon, 1993).
Motor learning may also be separable from spatial location
ability. Spatial location was deficient in the amnesic
patient, H.M. (Smith, 1988), who demonstrated relatively
intact motor learning (Gabrieli, Corkin, Mickel, & Growden,
1993). The finding that subjects with Huntington's disease
were not as impaired as those with Alzheimer's on a verbal
recall task supported the dissociation between motor and
verbal learning (Heindel, Butters, & Salmon, 1988). The
basal ganglia are part of a loop involving the motor cortex
and thalamic nuclei that control motor behavior (Penny &
Young, 1986). Damage to the basal ganglia causes an
inability to direct and control movements. Other motor
control areas, such as the cerebellum, did not appear to
influence motor skill learning (Gabrieli, Corkin, Mickel, &
Growden, 1993).


21
children with ADHD (Szatmari, Offord, & Boyle, 1989b).
Children with ADHD frequently suffer four or more serious
accidents during childhood, and these may include head, eye,
and tooth injuries (Hartsough & Lambert, 1985). Although
this characteristic of ADHD can be quite problematic for
caregivers, many of these accidents may be preventable if
parents are aware of the need for extra precautions
(Szatmari, Offord, & Boyle, 1989b).
Health Problems in Children with ADHD
and Their Mothers
Chronic health problems in infancy and childhood have
also been associated with ADHD (Hartsough & Lambert, 1985).
Controlling for medication prescribed to treat ADHD
symptoms, children with ADHD are prescribed medication
significantly more often than normal controls (Szatmari,
Offord, & Boyle, 1989b). Asthma, allergies, and ear
infections have all been found in ADHD children at a higher
rate than in normal controls (Hartsough & Lambert, 1985).
Barkley (1990) noted that minor physical anomalies, such as
increased head circumference, eyes placed farther apart than


44
(Barkley, 1990). Compared to normal children, they are
inefficient in their management of resources, and so they
have difficulty completing tasks even if well motivated
(Douglas, 1984). Self-regulation deficits may cause
deficiencies in sustained attention unrelated to increased
responsiveness to extraneous stimuli (Douglas, 1983). In
addition to impulsive responses to environmental changes,
children with ADHD have problems maintaining attention for
any task (Douglas, 1983).
Sustained attention in ADHD children is commonly
assessed using vigilance tasks such as the Continuous
Performance Test (CPT; Corkum & Siegel, 1993), which
measures sustained attention for infrequent events. During
the CPT, a series of numbers or letters are presented and
the child's goal is to identify the target number/letter or
number/letter sequence. Performance on the CPT can be
influenced by variables related to the task itself, such as
longer intervals between stimuli and the length of time that
the stimulus is displayed (Corkum & Siegel, 1993). When
task difficulty was increased, children with ADHD were
increasingly separated from normal children on performance
measures (Corkum & Siegel, 1993). Children with ADHD became


103
gender, socioeconomic status, comorbid diagnoses, tutoring,
and medications*
Neuropsychological Measures
Four brief screening measures were incorporated into
the protocol. As noted above, an interpolated Full Scale IQ
was used as a determinant of each child's ability to
understand and complete the protocol. Screening measures of
attention, fine motor coordination, and spatial judgment
were incorporated because these skills were believed to be
elements of motor skill acquisition.
The interpolated FSIQ was derived from a short form of
the WISC-III (Wechsler, 1991) that consisted of the
Vocabulary and Block Design subtests (Sattler, 1992). The
Vocabulary subtest is a language-based task requiring
children to orally define words. Block Design involves
visual-spatial reasoning and coordination in the
construction of abstract designs to pictured models.
Correlations of r=.79 between Vocabulary and the Full Scale
IQ (FSIQ) have been reported (Sattler, 1992), while Block
Design correlated with FSIQ at r= .74. These subtests were


101
was not used as an exclusion criteria, as few significant
differences have been found between boys and girls with ADHD
(Breen, 1989). The experimental group consisted of 31
children (27 boys, 4 girls) who had been given a clinical
diagnosis of ADHD either prior to, or soon after, their
participation in the study. There were 33 children in the
control group (19 boys, 14 girls). Children with a
diagnosis of developmental learning disability, a WISC-III
interpolated IQ below 80, or placement in special education
were excluded from this study. However, 10 of the children
with ADHD were receiving tutoring or academic enrichment.
Twenty-six of the children with ADHD reported no comorbid
diagnosis, three had co-occurring Oppositional Defiant
Disorder, one had an unspecified emotional disorder, and one
had multiple comorbid diagnoses. No children in the control
group reported academic difficulties, comorbid diagnoses, or
use of psychiatric medications. Twenty-seven of the
children with ADHD were prescribed stimulant medication, one
child was prescribed an antihypertensive, and three children
were prescribed no medication to control symptoms of ADHD.
To control possible neurobiological and behavioral effects
of medication, parents of children with ADHD were asked to


37
than parents of children with developmental delays (Roizen
et al., 1996).
Fathers of children with ADHD were reported to have
high rates of antisocial behavior and frequent changes in
employment (Barkley, Fischer, Edelbrock, & Smallish, 1990).
For example, fathers of children with ADHD engaged in
significantly more childhood antisocial behaviors and 11.2%
of these fathers were diagnosed as having antisocial
personality disorder, while only 1.6% of the fathers of
normal controls received this diagnosis. Fathers of
children with comorbid ADHD and conduct disorder had
somewhat higher rates of antisocial behaviors than fathers
of children with uncomplicated ADHD. However, this
difference did not reach significance, which indicated that
antisocial behavior in the father is an important correlate
of uncomplicated ADHD. Psychopathology in fathers of
children with ADHD may render the father ineffective as a
parent and produce an unstable environment for the child,
negatively impacting the child's behavior (Barkley, Fischer,
Edelbrock, & Smallish, 1990). Mothers of children with ADHD
have been found to be younger, less educated, and had a
higher rate of separation and divorce than mothers of


32
normal controls (Alessandri, 1992). Preschoolers with ADHD
were less creative and developmentally advanced in their
play. They played alone more often than control children
and had significantly fewer conversations with peers. In
group situations, ADHD children failed to understand social
rules, became overstimulated, and lost control of their
behavior (Berry, Shaywitz, & Shaywitz, 1985). Peer
rejection likely has an increasingly negatively impact on a
child's self-esteem, leading to a higher frequency of
disruptive behaviors in older children with ADHD
(Alessandri, 1992).
The combination of ADHD and LD significantly increases
the risk for social rejection (Flicek, 1992) Peer
nomination identified ADHD children as disruptive, while LD
children were seen as having low peer popularity and few
leadership skills. The group of combined ADHD/LD children
was rejected by, and fought with, peers significantly more
often than normal controls, a finding that was not repeated
in the ADHD-only or LD-only groups (Flicek, 1992). Although
ADHD alone did not result in significant social rejection,
these children were rated as more disruptive. Children with
ADHD/LD may combine aggressive, disruptive ADHD symptoms


87
Motor Skill Acquisition in Children with ADHD
As noted above, little research has been done on motor
skill acquisition in children with ADHD. On a visual-motor
tracking task requiring the subject to use a control stick
to keep a lighted dot centered on a moving target, children
with ADHD performed significantly worse than normal controls
{Conners & Delamater, 1980). Although some practice effects
were recorded, the children were tested under several
different conditions and the task did not allow for
continuous practice of any one condition, making it
difficult to make any judgements about motor skill
acquisition {Conners & Delamater, 1980). Examination of the
effect of Ritalin on baseball skills indicated that it
improved the attention and on-task behaviors during games,
but had little effect on improving baseball skills (Pelham
et al., 1990) However, the children had relatively little
chance to practice their skills and baseball skills often
involve multiple coordinated movements and cognitions,
making it difficult to determine all variables involved in
their acquisition (Pelham et al., 1990).


TABLE 2
PARENT REPORT MEASURES
124
ADHD
CONTROL
GROUP
GROUP
MEAN
(SD)
MEAN (SD)
CONNERS PARENT RATING SCALE
-REVISED
57.71
(22.80)
21.82 (14.40)1
DSM-IV CHECKLIST
13.10
(3.97)
2.12 (2.80)1
P < .001


84
in poor rotary pursuit performance by mentally retarded
children (Heitman & Gilley, 1989). The learning curves of
these children were correlated with on-task behaviors
(Heitman & Gilley, 1989), and feedback appeared to improve
attention to a task, consistent with earlier results
(Horgan, 1982) Retarded children appeared to gain from
consolidation, as second-day performance was improved over
the first day learning (Heitman & Gilley, 1989). This was
consistent with other evidence that skill retention in these
children is not significantly different from normal children
(Simenson, 1973).
No significant effect for either massed or distributed
practice was found in mildly mentally retarded children
(Rider & Abdulahad, 1991). Improved performance was again
found on the second day of testing, consistent with
consolidation and skill retention, but attention problems
had a negative impact on performance (Rider & Abdulahad,
1991). There seemed to be an optimal number of trials for
the acquisition of motor skills in autistic children, as the
use of more than 10 trials resulted in significant off-task
behavior (Wek & Husak, 1989). Within these limitations, it


52
Cognitive problems may precede behavioral problems when
a child is responding adversely to medication (Swanson et
al., 1991). Medication may be overprescribed as clinicians
ignore negative cognitive reactions in favor of positive
changes in behavior (Swanson et al., 1991). In addition,
there appeared to be a subset of children with ADHD who
receive minimal benefit from medication, especially in
classroom situations (Rapport, Denney, DuPaul, & Gardner,
1994; DuPaul, Barkley, & McMurray, 1994). Using a paired-
associate task, approximately 30% of children with ADHD were
classified as having a negative cognitive response to
Ritalin, as measured by a quadratic response curve, a curve
most often seen in difficult tasks (Swanson et al., 1991) .
Absolute doses of medication may also be more beneficial to
children than dosage based on weight, as learning curves
indicated that absolute doses provided stable improvement in
learning for children of various weights. Learning curves
revealed that heavier children may actually need less
medication than indicated by a standard weight-based
prescription (Swanson et al., 1991).
Although stimulant medication appeared to improve
academic performance in children with ADHD, questions remain


46
reward (Douglas, 1983). Specific tasks, especially
experimental tests of attention, may not be interesting to
children with ADHD, leading to the appearance of low arousal
(Douglas, 1984). These same children may overreact when the
stimulus is interesting, suggesting that the true deficit is
in modulating their level of arousal. In order to more
fully define the underlying deficits of ADHD, the components
of vigilance need to be analyzed separately (Corkum &
Siegel, 1993) .
Pharmacological Treatment of ADHD
Methylphenidate (Ritalin) is one of the most common
psychostimulants used for treatment of children with ADHD
(Barkley, 1990), and up to 77% of children who are placed on
Ritalin experience improvement in behavior (Murray, 1987),
Ritalin is a dopamine agonist, as are its companion
medications, Dexedrine (d-amphetamine) and Cylert (pemoline)
(Murray, 1987). Dopamine and other catecholamines are
believed to be involved in the control of attention (Hynd,
Voeller, Hern, & Marshall, 1991) and most children with ADHD
respond positively to these drugs (DuPaul, Barkley, &
McMurray, 1991). Ritalin is generally believed to increase


CHAPTER 5
DESIGN
This was a 2x2, between subjects design, with pursuit
rotor performance as the primary dependent variable. The
independent variables, ADHD and reward status, are depicted
in Figure 1. Each child in the ADHD and control groups were
randomly assigned either to a reward for performance
condition or a no-reward condition. The reward condition
was based on research suggesting that small rewards increase
the motivation and attention of children with ADHD (Pelham,
Milich, & Walker, 1986; Carlson, Pelham, Milich, & Dixon,
1992) without using medication that may improve the overall
functioning of the cortical-subcortical loops involved in
attention and motor programming (Lou, et al., 1989).
Children in the reward for performance groups were given
stickers or some other small reward for maintaining or
improving their level of performance on each trial.
Children in the no-reward groups did not receive any
98


6
impairment in functioning at home and school and with
peers.
(DSM-III-R. 50-53)
Considerable research, to be discussed below, provided
strong data in support of multiple subtypes and Attention
deficit disorder was again divided into subtypes with the
appearance of the DSM-IV American Psychiatric Association,
1994).
Current Diagnostic Criteria
The Fourth Edition of the Diagnostic and Statistical
Manual for Mental Disorder (DSM-IV; American Psychiatric
Association, 1994) recognizes three subtypes of ADHD; ADHD-
combined type, ADHD-predominantly inattentive type, and
ADHD-predominantly hyperactive/impulsive type. Children who
meet criteria for the predominantly inattentive type do not
meet hyperactive/impulsive criteria, while children who fall
into the hyperactive/impulsive category are overactive, but
not distractible. The complete DSM-IV diagnostic criteria
are as follows:
DSM-IV Criteria for Attention Deficit/Hyperactivity
Disorder


138
trial, rather than the thirty total trials completed in the
current study. This may have limited the opportunity for
development of differences in motor skill acquisition
between the ADHD and control groups. The relatively slow,
uniform speed (15 rpm) used by Leavell, Ackerson, & Fischer
(1995) may have resulted in children reaching a ceiling
performance more quickly than the individually-set speeds
used in the current study. Finally, the relatively
restricted age range used in the current study controlled
for maturation effects that may have influenced earlier
results, as children in the earlier study were aged 6-16
(Leavell, Ackerson, & Fischer, 1995).
Results of this study provided further evidence that
ADHD symptoms are influenced by developmental differences in
the brains of children with ADHD. The deficits in motor
skill acquisition demonstrated by children with ADHD were
similar to those seen in adult patients with basal ganglia
disease (Heindel, Butters, & Salmon, 1988). Recent research
has suggested that children with ADHD have differences in
the morphometry of the right prefrontal cortex and right
globus pallidus, and a lack of the normal asymmetry seen in
the caudate nucleus (Castellanos et al., 1996). Children


29
child would be unlikely to experience the levels of academic
frustration described by McGee and Share (1988). Each child
should be evaluated independently and interventions should
be directed at the primary deficit (McGee & Share, 1988), as
comorbidity between learning disabilities and ADHD resulted
in greater learning problems than ADHD alone (Kataria, Hall,
Wong, & Keys, 1992).
As noted above, past comorbidity studies used
inconsistent criteria for defining learning disabilities,
resulting in considerably different conclusions (Semrud-
Clikeman et al.f 1992). Children with ADHD are at
significant risk for school failure, and remediation of
academic deficits may be as important as treatment of
disruptive behaviors (Hinshaw, 1992). Research suggested
that, regardless of learning disability, children with ADHD
are more likely to be placed in a classroom for children
with disruptive behaviors, perhaps making them less likely
to receive academic remediation (Barkley, DuPaul, &
McMurray, 1990). Inconsistent criteria for defining
learning disabilities in the literature ranged from labeling
any academic deficit as a learning disability to extremely
stringent criteria limiting learning disabilities to those


150
YES
NO
10.
Fidgets with hands or squirms in seat
YES
NO
11.
Leaves seat in classroom or in other
situations when staying seated is expected
YES
NO
12 .
Runs about or climbs excessively in
inappropriate situations
YES
NO
13 .
Has difficulty playing quietly
YES
NO
14 .
Often "on the go" or acts as if "driven by
motor"
YES
NO
15.
Talks too much
YES
NO
16 .
Blurts out answers before questions are
finished
YES
NO
17.
Difficulty taking turns
YES
NO
18.
Interrupts or intrudes on others


63
The caudate nucleus has been called the "head ganglion
of the habit system, a designation that underlines its
importance in motor skill learning (Saint-Cyr, Taylor,
Trepanier, & Lang, 1992). This large subcortical nucleus
also influences behavioral responses to stimuli (Rolls &
Johnstone, 1992), suggesting that it is integrated into
attention systems (Lou, Henrikson, & Bruhn, 1990). Children
with ADHD have been found to have a smaller left than right
caudate nucleus, the reverse of what is found in normal
controls, but had no significant differences in overall
brain size (Hynd et al.# 1993). The lack of differences in
overall brain size indicated regional differences in
development, rather than variations in the brain as a whole
(Hynd et al., 1990). Abnormal asymmetries may result in a
bias for right-sided control mechanisms and the disruption
of subcortical control of attention, as neurotransmitter
systems favor the non-dominant hemisphere. As dominant
hemisphere controls on the motor systems are disrupted,
overactivity may result. Behavioral disinhibition in
children with ADHD may also be influenced by subcortical
neurotransmitter systems and their relationship to the
frontal lobes, especially the prefrontal cortex. Abnormal


158
Flicek, M. (1992). Social status of boys with both academic
problems and attention deficit hyperactivity disorder.
Journal of Abnormal Child Psychology. 22, 353-366.
Gabrieli, J.D.E., Corkin, S., Mickel, S.F., & Growden, J.H.
(1993). Intact acquisition and long-term retention of
mirror-tracing skill in Alzheimer's disease and global
amnesia. Behavioral Nevroociencg, 1Q7, 899-910.
Gillis, J.J., Gilger, J.W., Pennington, B.F., & DeFries,
J.C. (1992). Attention deficit disorder in reading-
disabled twins: Evidence for a genetic etiology.
Journal of Abnormal Child Psychology, 20, 303-315.
Goodyear, P. & Hynd, G.H. (1992). Attention deficit disorder
with (ADD/H) and without (ADD/WO) hyperactivity:
Behavioral and neuropsychological differences. Journal
of_ .Clinical Child Psychology. 21, 273-305.
Goyette, C.H., Conners, C.K., & Ulrich, R.F. (1978).
Normative data on Revised Conners Parent and Teacher
Rating Scales. Journal of Abnormal Child .Psychology,
2(2), 221-236.
Grodzinsky, G.M. & Diamond, R. (1992). Frontal lobe
functioning in boys with attention deficit
hyperactivity disorder. Developmental Neuropsychology.
2, 427-445.
Halperin, J.M., Newcorn, J.H., Matier, K., Sharma, V.,
McKay, K.E., Schwartz, S. (1993). Discriminant validity
of attention deficit hyperactivity disorder. Journal of
the American Academy of Child and Adolescent
Psychiatry, 2, 1038-1043.
Hartsough, C.S. & Lambert, N.M. (1985). Medical Factors in
hyperactive and normal children: Prenatal,
developmental, and health history findings. American
Journal of Orthopsychiatry, 21, 190-201.


39
independent contribution, comorbid oppositional-defiant or
conduct disorders made a significant contribution to family
conflicts (Anastopoulos, Guevremont, Shelton, & DuPaul,
1992) .
Observed interactions between children with ADHD and
their mothers provided evidence that, in a neutral
situation, children with ADHD used a more negative
conversational style than controls (Barkley, Fischer,
Edelbrock, & Smallish, 1991). Mothers of children with
comorbid Oppositional-Defiant Disorder (ODD) and ADHD used
more commands and put-downs than mothers of normal controls
or of children with uncomplicated ADHD (Barkley, Fischer,
Edelbrock, & Smallish, 1991). Mothers of children with
comorbid ADHD/ODD also reported significantly more
subjective stress than mothers of children with
uncomplicated ADHD (Anastopoulos, Guevremont, Shelton, &
DuPaul, 1992). Symptoms of depression, anxiety,
somatization, and hostility were all found in the mothers of
aggressive ADHD children (Barkley, Fischer, Edelbrock, &
Smallish, 1991) Maternal psychopathology and increased
subjective stress may interact with the negative behavior of
the child to produce parent-child conflict (Anastopoulos,


118
= .23, ns). Rotation speeds ranged from 16 to 45 rpm, with
a mean speed of 26.78 rpm. Pursuit rotor performance was
found to meet the assumptions of independence, normality of
distribution, and homogeneity of variance for use of
Analysis of Variance. Therefore, variations of this
statistical method were used for all primary analyses.
Between-group pairwise comparisons used t-tests, as this was
the most sensitive method for detecting significant
differences in performance.
Power
Power analysis indicated sufficient power (.8) for
detecting significant group differences with Analysis of
Variance. Power for pairwise t-tests was variable, with a
value of .3 for between-group differences of around one
second, but adequate power (.8) for larger between-group
comparisons. Power was adequate (.8) for a multiple
regression analysis using the total sample and six
independent variables, but there may not have been
sufficient power (.67) to interpret separate simple linear
regressions for the ADHD and control groups.


99
tangible incentives for improved performance. Verbal
encouragement was given to both groups.
ADHD STATUS
ADHD
n = 31
CONTROL
n = 33
REWARD STATUS
REWARD
NO
REWARD
NO
REWARD
REWARD
n = 15
n = 16
n = 17
n = 16
Figure 1


13
consistent with teacher ratings that identified ADD/WO
children as daydreamy, apathetic, and lethargic (Barkley,
DuPaul, & McMurray, 1990).
The slowed tempo, daydreaminess, and lethargy displayed
by children with ADD/WO may result from a greater
preoccupation with internal stimuli, rather than the
disinhibition that characterizes children with ADD/H
(Barkley, DuPaul, & McMurray, 1990). Although children of
both subtypes were rated as inattentive in school, children
with ADD/H exhibited more disruptive behaviors, while
children with ADD/WO were more often seen as unmotivated
(Barkley, DuPaul, & McMurray, 1990). There were also
differences between the family psychiatric histories of the
two groups. Relatives of children with ADD/WO were more
likely to have a history of anxiety disorder, while
relatives of children with ADD/H had a higher incidence of
aggressive behavior and substance abuse (Barkley, DuPaul, &
McMurray, 1990). This was consistent with the conclusions
of a review that suggested an
"attentional/cognitive/anxiety" constellation of symptoms in
ADD/WO, rather than the "attentional/behavioral/impulsive"
characteristics of ADD/H (Goodyear & Hynd, 1992).


164
Power, T.J. (1992) Contextual factors in vigilance testing
of children with ADHD. Journal of Abnormal Child
Psychology, 2£, 579-593.
Quay, R.C. & Peterson, D.R. (1983) Interim. Manual for .the
Revised gehayjQX Problem Checklist. Available from
Herbert C. Quay. Box 248074, University of Miami, Coral
Gables, FL 33124.
Rapport, M.D., Denney, C., DuPaul, G.J., & Gardner, M.J.
(1994). Attention deficit disorder and methylphenidate:
Normalization rates, clinical effectiveness, and
response prediction in 76 children. Journal of the
American _Academy_Qf Child and Adolescent-Psychiatry,
a, 882-893.
Rider, R.A. & Abdulahad, D.T. (1991). Effects of massed
versus distributed practice on gross and fine motor
proficiency of educable mentally handicapped
adolescents. Perceptual and Motor Skills. 73., 219-224.
Roizen, N.J., Blondis, T.A., Irwin, M., Rubinoff, A.,
Kieffer, J., & Stein, M.A. (1996). Psychiatric and
developmental disorders in families of children with
attention-deficit hyperactivity disorder. Archives of
Pediatric and Adolescent Medicine, 10, 203-208.
Rolls, E.T. & Johnstone, S. (1992). Neurophysiological
analysis of striatal function. In Vallar, G., Cappa,
S.F., & Wallesch, C-W. (Eds.) Neuropsychological
Disorders Associated with Subcortical Designs, PP- 61-
97. New York: Oxford University Press.
Ross, R.G., Hommer, D., Breiger, D., Varley, C., & Radant,
A. (1994). Eye movement task related to frontal lobe
functioning in children with attention deficit
disorder. Journal of the American Academy of Child and
Adolescent Psychiatry. H, 869-874.
Ruffer, W.A. (1984). Comparisons of four psychomotor tasks:
Grade and sex of elementary school children. Perceptual
and Motor Skills, 323-328.


34
comorbid ADHD and conduct disorder were at significantly
greater risk for substance abuse (Barkley, Fischer,
Edelbrock, & Smallish, 1990).
Symptoms of ADHD may manifest themselves in college
students as poor study skills and learning difficulties, and
students with previously undiagnosed ADHD may feel that they
are not working up to their potential (Heiligenstein &
Keeling, 1995). Although college students with ADHD may
have developed compensatory strategies, they still have
noticeable problems in sustained attention (Heiligenstein &
Keeling, 1995). College students with a childhood diagnosis
of ADHD demonstrated poor concentration on a 20-minute
letter cancellation task (Shaw & Giambra, 1993). When
compared to control groups that included both normals and
students who reported some childhood ADHD symptoms, students
with ADHD reported more spontaneous thoughts unrelated to
the task, and were impulsive in their responses to the task.
The results suggested that symptoms of ADHD do not always
disappear with age, and adults with ADHD continue to have
poor modulation of internal processes, especially when bored
(Shaw & Giambra, 1993; Douglas, 1984). In an attempt to
relieve boredom and achieve an optimal level of stimulation,


33
with deficient cognitive processing and incorrectly view
their peers as hostile and rejecting in all situations
(Flicek, 1992). This perception may lead to increased
conflict with, and rejection by, peers. Evaluations of
social problems may lead to more effective interventions if
they include both cognitive and behavioral factors (Flicek,
1992).
Long-Term Outcome of Children with ADHD
Studies have indicated that up to 80% of children
diagnosed with ADHD continue to show salient characteristics
of the disorder well into adolescence (Barkley, Fischer,
Edelbrock, and Smallish, 1990). Adolescents with ADHD were
significantly more likely than normal controls to have a
comorbid conduct disorder (Barkley, Fischer, Edelbrock, &
Smallish, 1990). Consistent with this, adolescents with
ADHD were more likely to have been involved in antisocial
activities, including theft, assault, and destruction of
others' property (Barkley, Fischer, Edelbrock, & Smallish,
1990). Adolescents with ADHD were somewhat more likely to
have been in auto accidents than control subjects, but the
risk was not significantly higher. Adolescents with


Neuroanatomy of Motor Systems 89
4. SUMMARY AND RATIONALE 93
Summary 93
Specific Aims and Hypotheses 95
5. DESIGN 98
6. PROCEDURE AND METHODS 100
Subjects 100
Measures 102
Procedure 107
7. RESULTS 114
Initial Analyses 114
Neuropsychological Measures 116
Analyses of Pursuit Rotor Performance .... 117
8. DISCUSSION 131
Sample Characteristics 132
Rotary Pursuit Performance 133
Secondary Analyses 135
Implications 137
Limitations 142
Summary and Directions for Future Research 144
APPENDICES
A BACKGROUND INFORMATION 147
B BEHAVIOR CHECKLIST 149
REFERENCES 151
BIOGRAPHICAL SKETCH 169
v


TABLE 6
ADHD VS. CONTROL GROUP PERFORMANCE OVER BLOCKS
128
COMPARISON
L
df
Significance
BLOCK 1
-2.79
62
£ <
. 01
BLOCK 2
-4.87
62
£ <
.001
BLOCK 3
-4.98
62
£ <
.001
BLOCK 4
-5.42
62
£ <
.001
BLOCK 5
-5.19
62
£ <
. 001
BLOCK 6
-5.33
62
E <
. 001


72
the WCST has proved disappointing as a test of ADHD, even in
younger children (Barkley & Grodzinsky, 1994).
Children with ADHD had difficulty alternating responses
during sequencing tasks (Shue & Douglas, 1992), but even
when the difference was nonsignificant, normal children were
somewhat faster than children with ADHD (Grodzinsky &
Diamond, 1992). Tests of planning and organization also
produced mixed results (Grodzinsky & Diamond, 1992; Barkley
& Grodzinsky, 1994). Motor control difficulties in children
with ADHD are similar to deficits found in adults with
frontal lobe dysfunction (Shue & Douglas, 1992). Children
with ADHD had deficits inhibiting motor responses, made
impulsive errors in responding, and were echopraxic (Shue &
Douglas, 1992). Children with ADHD also had significantly
greater difficulty inhibiting memory-guided eye movements
compared to normal controls (Ross et al., 1994). These
results are consistent with what would be expected, given
abnormal asymmetry of the caudate nucleus and the subsequent
disruption of connections with the prefrontal lobes (Hynd et
al., 1993).
Verbal fluency tests, especially those which require
generation of words to a target letter, were a useful


142
to lower frustration in the adults and less conflict between
them and the children with ADHD.
When combined with the impulsive, high-risk behaviors
often engaged in by children with ADHD, incoordination may
make a significant contribution to the higher rate of injury
reported in these children {Farmer & Peterson, 1995}.
Dopaminergic stimulants, such as Ritalin, may bring the
functioning of the cortical-subcortical systems responsible
for response inhibition and motor control closer to normal
levels (Lou et al., 1989). Thus, it is likely that in
addition to decreasing the behavioral symptoms of ADHD,
psychopharmacologic treatment would also improve motor
programming ability.
The number of subjects in this study was limited and
may have reduced the strength of the findings. However, the
effects appeared fairly robust and expansion of this study
with more subjects would help to confirm the current
findings. A larger study would also increase the
interpretability of the multiple regression, and allow for


74
children from normal controls (Barkley & Grodzinsky, 1994).
A family history of ADHD may negatively impact the
performance of a child with ADHD on neuropsychological
tests, but comorbid diagnoses did not appear to have a
significant effect (Seidman et al., 1994).
Neuroanatomy of Attention
The primary factors in defining attention are the
ability to focus on environmental stimuli, sustain
attention, encode information, respond to stimuli, and shift
attention to new targets (Mirsky et al., 1991). These
factors are similar to those proposed by other
neuropsychological models of attention (Cohen, 1993). Cohen
(1993) noted that a weakness of this model is that it is
based on responses to traditional neuropsychological
measures and may not measure the impact of differences in
motivation and behavior. An alternate model of attention
includes sensory attention, attentional capacity, selection
and control of responses to stimulation, and sustained
attention (Cohen, 1993). Children with ADHD were seen as
having impairments in most areas of attention, with
important exceptions. Their ability to focus on


108
design and purpose of this study, and the exclusionary
criteria. The parents of children contacted through the
university neurology clinic were approached during clinic
appointments or contacted by phone and given the same
information.
Control children from were contacted through letters to
parents sent home through community groups or P.K. Yonge
Developmental Research School. The psychologist at the
school was contacted by the principal investigator and
access to classes with children in the target age range was
requested. A graduate research assistant gave letters
asking for parental permission to the teachers of these
classes, who sent the letters home with the children. The
children whose parents returned the signed consent forms
were taken out of class one at a time by the graduate
research assistant for participation in the study. Two
children in the control group who scored in the clinical
range of the CPRS-R, met DSM-IV checklist criteria for ADHD,
and were observed to be inattentive and hyperactive were
excluded from the study.
Placement into either the reward or no-reward
conditions was randomized by the placement of small slips of


112
Demonstration/Practice => WISC-III Short Form => Block 1 =>
1 min. break => Block 2 => CPT/Cancellation => Block 3 =>
1 min. break => Block 4 => CPT Conditional Cancellation =>
Block 5 => 1 min. break => Block 6 => Grooved Pegboard / JLO
Figure 2
Each child participated in this study for only one day,
and the protocol was completed in approximately ninety
minutes. The investigation of retention in motor learning
was not within the scope of this study, so a second day of
experimentation was not necessary. All participating
children completed the protocol.


I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Cdu Qu
Eileen B. Fennell, Chair
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Professor of Clinical and
Health Psychology
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Stephen R. Boggs
Associate Professor of
Clinical and Health
Psychology


7
A. Either (1) or (2):
(1) six (or more) of the following symptoms of
inattention have persisted for at least 6 months to a
degree that is maladaptive and inconsistent with
developmental level:
Inattention
(a) often fails to give close attention to details or
makes careless mistakes in schoolwork, work, or other
activities
(b) often has difficulty sustaining attention in tasks
or play activities
(c) often does not seem to listen when spoken to
directly
(d) often does not follow through on instructions and
fails to finish schoolwork, chores, or duties in the
workplace (not due to oppositional behavior or failure
to understand instructions)
(e) often has difficulty organizing tasks and
activities
(f) often avoids, dislikes, or is reluctant to engage
in tasks that require sustained mental effort (such as
schoolwork or homework)
(g) often loses things necessary for tasks or
activities (e.g., toys, school assignments, pencils,
books, or tools)
(h) is often easily distracted by extraneous stimuli
(i) is often forgetful in daily activities
(2) six (or more) of the following symptoms of
hyperactivity-impulsivity have persisted for at least 6
months to a degree that is maladaptive and inconsistent
with developmental level:


91
processing of this information. It is the maintenance,
rather than the encoding, of information about the distance
of arm movements that appeared to be a right frontal lobe
function, as immediate recall was not impaired in these
subjects (Leonard & Milner, 1991b). The right frontal lobe
subjects with large lesions were equally impaired with
either hand, and were more impaired than subjects with
either left frontal lesions or small right frontal lesions.
These findings indicated that localization and size are
important, with large right-sided frontal lesions disrupting
motor systems that maintain kinesthetic distance information
(Leonard & Milner, 1991a).
The basal ganglia (caudate nucleus, putamen, and
globus pallidus) play a role in motor skill learning (Saint-
Cyr, Taylor, Trepanier, & Lang, 1992). Subjects with
Huntington's disease, a movement disorder arising from basal
ganglia dysfunction, performed significantly worse than
groups of subjects with amnesia, Alzheimer's disease, and
normal controls on the pursuit rotor task (Heindel, Butters,
Sc Salmon, 1988) Neither global amnesia nor the early
stages of Alzheimer's disease impaired the performance of
these patients on a mirror-tracing task, suggesting that the


3
Although inattention continued to be recognized as a
symptom of the disorder, motor overactivity was the basis
for the next diagnostic schema, hyperkinetic reaction of
childhood (American Psychiatric Association, 1968; Cantwell
Sc Baker, 1992). However, inattention and impulsivity were
often essential characteristics of these childrens' symptoms
and the diagnostic nomenclature was changed to reflect this
(Goodyear & Hynd, 1992) Attention deficit disorder (ADD),
a diagnosis that included the three essential features of
inattention, impulsivity, and hyperactivity, was recognized
in the third edition of the Diagnostic and Statistical
Manual of Mental Disorders (DSM-III; American Psychiatric
Association, 1980) Two subtypes of ADD were described in
the DSM-III; the first included all three behavioral
characteristics, with emphasis on motor hyperactivity
(ADD/H), and the second group was characterized by attention
deficits, with little or no overactivity (ADD/WO). The
existence of ADD/WO was the subject of considerable debate
following publication of the DSM-III and during development
of the next diagnostic system, the DSM-III-R (American
Psychiatric Association, 1987). Attention deficit disorder
without hyperactivity is a rare symptom cluster (Szatmari,


167
Trites, R.L., Dugas, E., Lynch, G., & Ferguson, H.B. (1979).
Prevalence of hyperactivity. Journal of Pediatric
Psychology. 4(2), 179-188.
Voeller, K.K.S. (1986). Right hemisphere deficit syndrome in
children. American Journal of Psychiatry, 14,1, 1004-
1009.
Voeller, K.K.S. (1991). What can neurological models of
attention, intention, and arousal tell us about
attention deficit hyperactivity disorder? Journal of
Neuropsychiatry, 1, 209-216.
Voeller, K.K.S. Sr Heilman, K.M. (1988a). Attention deficit
disorder in children: A neglect syndrome? Neurology.
18, 806-808.
Voeller, K.K.S. & Heilman, K.M. (1988b). Motor impersistence
in children with attention deficit hyperactivity
disorder: Evidence for right hemisphere dysfunction.
Annals of Neurology, 24, 323.
Watson, R.T., Valenstein, E., & Heilman, K.M. (1981).
Thalamic neglect: Possible role of the medial thalamus
and nucleus reticularis in behavior. Neurology. 38.
501-506.
Wechsler, D. (1991). Manual for the Wechsler intelligence
Scale for Children-Third Edition. New York:
Psychological Corporation.
Weinberg, W.A. & Harper, C.R. (1993). Vigilance and its
disorders. Neurologic Clinics. 11, 59-78.
Wek, S.R. & Husak, W.S. (1989). Distributed and massed
practice effects on motor performance and learning of
autistic children. Perceptual and Motor Skills, M,
107-113.
Wells, K.C. & Forehand, R. (1985). Conduct and oppositional
disorders. In P.H. Bornstein & A.E. Kazdin (Eds.),
Handbook of clinical behavior therapy with,children
(pp. 218-265). Homewood, IL: Dorsey.


64
caudate asymmetries may negatively impact the activation of
frontal lobe functions that rely on subcortical modulation
with lowered behavioral control similar to that seen in
adult cases of frontal dysfunction (Hynd et al., 1993).
Cerebral Blood Flow in Children with ADHD
Studies of regional cerebral blood flow, from which a
structure's functional involvement in behavior can be
inferred, provided further evidence of subcortical
involvement in ADHD (Chugani, Phelps, & Mazziotta, 1987).
Children with ADHD had significantly lower levels of blood
flow in both the caudate nucleus {Lou et al., 1989) and
posterior periventricular areas (Lou, Henrikson, & Bruhn,
1990). Lesions in these subcortical areas caused attention
problems and motor hyperactivity in animal studies (Lou et
al., 1989). Interconnections between these structures and
the frontal lobes (Hynd et al., 1993) provided evidence that
deficiencies in subcortical metabolism are responsible for
poorly modulated activity in the prefrontal cortex (Lou,
Henrikson, and Bruhn, 1990). As noted above, these areas of
cortex are responsible for behavioral inhibition and have


73
measure of frontal lobe functioning in children with ADHD
(Koziol & Stout, 1992). Significantly fewer words were
generated by groups of ADHD children compared to normal
controls (Koziol & Stout, 1992; Barkley & Grodzinsky, 1994).
Adolescents with ADHD did not show deficits on these tasks
(Fischer, Barkley, Edelbrock, & Smallish, 1990). The
deficits in children were attributed to deficits in self
regulation (Koziol & Stout, 1992; Douglas, 1983), and an
inability to focus and sustain attention. These deficits
may be attributable to frontal lobe dysfunction, although
research on this as a definitive test of ADHD is not yet
conclusive (Barkley & Grodzinsky, 1994).
It is difficult to draw any solid conclusions about
frontal lobe functions in ADHD children at this time, as
most of the tests used were designed for adults and may not
translate well to children (Barkley, Grodzinsky, & DuPaul,
1992). In addition, frontal lobe measures may miss subtle
defects in functioning resulting from developmental factors,
as they were designed to measure the results of more severe
brain insults. Vigilance tasks, which were designed
specifically to measure the ADHD symptoms of attention and
impulsivity, were most effective in distinguishing ADHD


CHAPTER 1
CHILDREN WITH ADHD
Prevalence
Attention deficit hyperactivity disorder (ADHD) is one
of the most common childhood psychiatric disorders. It is
estimated that 3%-5% of school-age children meet criteria
for ADHD (American Psychiatric Association, 1994) but the
prevalence may be as high as 12% (Trites, Dugas, Lynch, &
Ferguson, 1979) Depending on the population studied, four
to nine times as many boys as girls are diagnosed with ADHD
(American Psychiatric Association, 1994). A child's age has
not been shown to have a significant effect on the diagnosis
of ADHD, although there may a trend towards fewer symptoms
as the child ages (Szatmari, Offord, & Boyle, 1989a).
Children with ADHD are estimated to be 30% to 40% of
referrals to clinicians (Barkley, 1990) and so research into
ADHD is critical as a basis for clinical work.
1


107
Experimenter Training
This study was primarily conducted by the principal
investigator and two graduate research assistants in
clinical psychology. Two undergraduate research assistants
were also involved in the study and participated in
protocols under the supervision of the principal
investigator. Research assistants were trained in the
standardized administration of the research measures and a
script was provided for the research protocol. The
performance of the assistants was evaluated by the principal
investigator and they demonstrated knowledge of standardized
procedures on all measures before they were permitted to
administer tests. To control for experimenter differences,
each investigator performed the protocol with both
experimental and control subjects.
Procedure
Parents of children with ADHD were contacted through
several sources. Letters were sent through a private
psychology practice and a support group for parents of
children of ADHD. These letters informed the parents of the


TABLE OF CONTENTS
ACKNOWLEDGMENTS
ABSTRACT vi
CHAPTERS
1.CHILDREN WITH ADHD 1
Prevalence 1
History 2
Current Diagnostic Criteria 6
ADHD With and Without Hyperactivity 10
Characteristics of ADHD 17
Assessment and Treatment 42
2.CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD . 59
Impact of Right Hemisphere Dysfunction on
ADHD 59
Morphological Differences in Children with
ADHD 60
Cerebral Blood Flow in Children with ADHD . 64
Brain Metabolism in Children with ADHD ... 65
Issues of Subject Selection 67
Neuropsychological Testing of Children with
ADHD 69
Neuroanatomy of Attention 74
3.THE PURSUIT ROTOR AND MOTOR SKILL
ACQUISITION 80
The Pursuit Rotor 80
Motor Skill Acquisition in Children with
ADHD 87
IV


139
with ADHD may also have abnormal development of the caudate
nucleus as they age (Castellanos et al., 1996).
Morphometric differences in prefrontal cortex and basal
ganglia structures may disrupt voluntary control of behavior
(Luria, 1973; Hynd et al., 1993), causing the impulsivity
and inattention seen in children with ADHD.
In addition to effects on attention and behavioral
inhibition, morphological differences in the brains of
children with ADHD may also disrupt a cortical-subcortical
loop responsible for the encoding of motor programs.
Children in the top quartile of pursuit rotor learning were
not significantly different from those in the lowest
quartile on a measure of fine motor coordination. This
suggested that the encoding of motor programs is at least
partially separated from motor response to a novel task.
The hypothetical encoding loop would involve excitatory
projections from cortical association areas that provide
feedback about task requirements to the parts of the basal
ganglia (caudate nucleus and globus pallidus) responsible
for the formation of motor programs (Penney & Young, 1986;
Rolls & Johnstone, 1992). Inhibitory projections from the
basal ganglia to the thalamus mediate excitatory input from


161
Lahey, B.B., Pelham, W.E., Schaughency, E.A., Atkins, M.S.,
Murphy, A., Hynd, G., Russo, M., Hartdagen, S., &
Lorys-Vernon, A. (1988). Dimensions and types of
attention deficit disorder. Journal of the American
Academy of Child and Adolescent Psychiatry, 21, 330-
335.
Lahey, B.B., Schaughency, E.A., Frame, C.L., & Strauss, C.C.
(1985). Teacher ratings of attention problems in
children experimentally classified as exhibiting
attention deficit disorders with and without
hyperactivity. Journal of the American Academy of Child
and Adolescent Psychiatry, 2, 613-616.
Lahey, B.B., Schaughency, E.A., Hynd, G.W., Carlson, C.L., &
Nieves, N. (1987). Attention deficit disorder with and
without hyperactivity: Comparison of behavioral
characteristics of clinic-referred children. Journal of
the American Academy of Child and Adolescent
Psychiatry, 2£, 718-723.
Leavell, C.A., Ackerson, J.D., & Fischer, R.S. (1995).
Procedural learning difficulties in children with
attention and/or overactivity: Is it motor skill or
motor acquisition? Paper presented at the Annual
Meetings of the International Neuropsychological
Society (INS); Seattle, WA.
Leonard, G. & Milner, B. (1991a). Contribution of the right
frontal lobe to the encoding and recall of kinesthetic
distance information. Neuropsychologia. 29. 47-58.
Leonard, G. & Milner, B. (1991b). Recall of the end-position
of examiner-defined arm movements by patients with
frontal-or temporal-lobe lesions. Neuropsychologia. 29.
629-640.
Leonard, G., Milner, B., & Jones, L. (1988). Performance on
unimanual and bimanual tapping tasks by patients with
lesions of the frontal or temporal lobe.
Neuropsychologia, 2£, 79-91.


REFERENCES
Achenbach, T.M. (1991). Manual for the Child Behavior
Checklist/4-18 and 1991 Profile. Burlington, VT:
University of Vermont Department of Psychiatry.
Alessandri, S.M. (1992). Attention, play, and social
behavior in ADHD preschoolers. Journal of Abnormal
Child Psychology, 22, 289-302.
Alessi, N., Hottons, M.D., & Coates, J.K. (1993). The gene
for ADHD? Not yet. Journal of the American Academy of
Child and Adolescent Psychiatry. 32. 1073-1074.
Alexander, G.E., DeLong, M.R., & Strick, P.L. (1986).
Parallel organization of functionally segregated
circuits linking basal ganglia and cortex. Annual
Review of Neuroscience, 1/ 357-381.
Amen, D.G., Paldi, J.H., & Thisted, R.A. (1993). Brain SPECT
imaging. Journal of the American Academy of .Child and
Adolescent Psychiatry. 22, 1080-1081.
American Psychiatric Association. (1968). Diagnostic and
statistical manual of mental disorders. Second Edition.
Washington, DC: American Psychiatric Association.
American Psychiatric Association. (1980) Diagnostic and
statistical manual of mental disorders. Third Edition.
Washington, DC: American Psychiatric Association.
American Psychiatric Association. (1987). Diagnostic and
statistical manual of mental disorders. Third Edition,
Revised. Washington, DC: American Psychiatric
Association.
151


CHAPTER 6
PROCEDURE AND METHODS
Subjects
This study investigated motor learning in children with
ADHD compared to normal controls on the rotary pursuit task.
All subjects participated voluntarily and parents completed
informed consent letters for each child. Subjects with ADHD
were drawn from a private mental health office, a support
group for parents of children with ADHD, and a university
neurology clinic. Control subjects were recruited from
community groups and a local elementary school.
Complete demographic information for both the ADHD and
control groups are presented in Table 1. To avoid the
maturation effects that may effect the performance of older
children with ADHD (Fischer, Barkley, Edelbrock, & Smallish,
1990), subjects for this study were between the ages of 7
and 11. Only right-handed children were used for this
study, as there may be confounding differences in motor
performance between right- and left-handed children. Gender
100


Ill
pursuit rotor trial was complete, the first part of the CPT
was administered. This was a five-minute letter
cancellation task and the children were told to press the
space bar when the letter "X" appeared. The examiner was
not in the room during administration of the CPT to control
the effect of examiner presence on performance (Power,
1992). Following the first CPT administration, two more
blocks of pursuit rotor trials were administered, with a
one-minute break between blocks. The fourth block was
followed by the second part of the CPT, a five-minute
conditional cancellation. This task required the children
to respond only when the "AX'* sequence of letters appeared
on the display. The final two blocks of rotary pursuit
trials were then administered, again separated by a one-
minute break. The sixth block was followed by the Grooved
Pegboard. Children were instructed to place the pegs into
the holes as fast as they could and were allowed to place
two practice pegs before beginning the task. The final
measure given was the Judgement of Line Orientation, with
the child directed to match line segments to the orientation
of target lines. The experimental sequence is depicted in
Figure 2.


110
the pursuit rotor and speed of rotation was adjusted for
each child based on performance during the practice trials.
After the child either met a criterion of 30% time on
target, or completed four practice trials, the experiment
began. Individualized speeds were used to avoid ceiling
effects that may have occurred in earlier studies of motor
skill acquisition. After completion of the practice trials,
the abbreviated form of the WISC-III was administered. The
Vocabulary subtest was administered first, followed by the
Block Design subtest. Two subjects had an interpolated IQ
below 80 and were allowed to complete the study, but
excluded from the data analysis.
Children completed a total of 6 blocks of 5, 30-second
rotary pursuit trials, with 10 second intertrial intervals.
The short trial length and the intertrial interval were used
to minimize fatigue (Wek & Husak, 1989). The first two
blocks of trials were given immediately following the Block
Design subtest and there was a one-minute break between
trials. Placement of breaks between blocks of rotary
pursuit trials was a method of distributing practice, and
allowed for the formation of motor programs during
consolidation {Eysenck & Frith, 1977). After the second


143
it to be performed separately for both the ADHD and control
groups.
Rewards used in this study were small (baseball cards,
pencils, etc.) and may have been insufficient to maintain
the motivation of the children in the ADHD/Reward group.
Rewards that were somewhat larger than those used in the
current study may have increased the motivation of those
children and enhanced their motor skill acquisition.
Rewards were not varied after a child selected a
reward. Children in the ADHD/Reward group may have
habituated to the reward they selected, reducing its
effectiveness in controlling motivation and attention.
Allowing a group of children to select a novel reward at the
beginning of each block and comparing their performance to
the performance of children receiving unvaried rewards may
control for habituation effects.
The conditions set for obtaining a reward may have also
affected the performance of the children with ADHD. Rewards
were received for maintenance of performance as well as for
improvement. Therefore, the performance of children with
ADHD may have improved if rewards were given only for
improvement.


152
American Psychiatric Association. (1994). Diagnostic and
Statistical Manual of Mental Disorders. Fourth Edition.
Washington, D.C: American Psychiatric Association.
Anastopoulos, A.D., Guevremont, D.C., Shelton, T.L., &
DuPaul, G.J. (1992). Parenting stress among families of
children with attention deficit hyperactivity disorder.
Journal.of Abnormal Child Psychology, 2_Q, 503-520.
Arnold, L.E., Barneby, N.S., & Smeltzer, D.J. (1981). First
grade norms, factor analysis, and cross correlation for
Conners, Davids, and Quay-Peterson rating scales.
Journal of Learning Disabilities, IA, 269-275.
Atkins, M.S., Pelham, W.E., & Licht, M.H. (1981). A
comparison of objective classroom measures and teacher
ratings of attention deficit disorder. Journal .of
Abnormal Child Psychology. 12, 155-167.
Barkley, R.A. (1983). Hyperactivity. In Morris, R.J. &
Kratochwill, T.R. (Eds.) The Practice of Child Therapy,
pp. 87-112. New York: Pergamon Press.
Barkley, R.A. (1990). Attention Deficit Hyperactivity
Disorder: A Handbook for Diagnosis._and Treatment. New
York: Guilford Press.
Barkley, R.A., DuPaul, G.J., & McMurray, M.B. (1990).
Comprehensive evaluation of attention deficit disorder
with and without hyperactivity as defined by research
criteria. Journal of Consulting and Clinical
Psychology. 58, 775-789.
Barkley, R.A., Fischer, M., Edelbrock, C.S., & Smallish, L.
(1990). The adolescent outcome of hyperactive children
diagnosed by research criteria, I: An 8 year
prospective follow-up study. Journal of the American
Academy of Child and Adolescent Psychiatry. 2j>, 546-
557.


76
attention such as response selection and shifting attention
are activated by these subcortical structures.
Voeller (1991) discussed the relationship of
impairments in sensory attention, controlled by sensory
association areas and the subcortical structures that
project to these areas, to the symptoms of ADHD (Voeller,
1991). These systems may control the ability to focus
attention on external events (Mirsky, 1991). Automatic
shifts in sensory attention were impaired in children with
ADHD (Cohen, 1993), suggesting difficulty in controlling
responses to environmental stimuli (Douglas, 1983). As
noted earlier, children with ADHD have been described as
having left-sided neglect similar to adults with right
hemisphere dysfunction (Voeller & Heilman, 1988a). This
represented a deficit in directed sensory attention, which
may be a function of the posterior parietal attention system
(Posner, 1992). Processing of incoming sensory information
and automatic shifts of attention appear to be regulated by
the parietal lobe and associated thalamic nuclei (Posner,
1992) .
Weinberg and Harper (1993) examined the literature
regarding the role of the right parietal lobe in sensory


50
planning and precision (Conners & Taylor, 1980). Improved
scores on word generation and paired-associate learning
indicated that stimulant medication does not effect only the
child's effort level, but also the ability to organize and
process material. Positive changes in the children's
behavior accompanied cognitive improvements, an indicator of
increased self-control. Stimulant medication appeared to
increase the ability of children with ADHD to maintain an
optimal level of cognitive effort (Douglas, Barr, O'Neill,
and Britton, 1986).
Dosage levels have been shown to affect both behavioral
and cognitive measures of ADHD (Douglas et al., 1988), and
there seems to be an optimal therapeutic dose, beyond which
there are diminishing returns (Rapport, Denney, DuPaul, &
Gardner, 1994). Improved performance of children with ADHD
on both simple reaction time and complex information
processing tasks was correlated with increased stimulant
dosage (Douglas et al., 1988). Academic and behavioral
improvements have also been reported on clinician and
teacher ratings (Rapport, Denney, DuPaul, & Gardner, 1994),
confirming earlier findings of improvement on parent
behavior ratings (Conners & Taylor, 1980). These findings


140
the thalamus to premotor cortex, which is responsible for
the storage and consolidation of information needed for
successful completion of motor tasks. Premotor cortex is
also responsible for the activation of motor responses from
storage (Alexander, Delong, & Strick, 1986; Rolls &
Johnstone, 1992). In patients with basal ganglia disease,
such as Huntington's chorea, this loop is disrupted at the
level of the basal ganglia, resulting in poor encoding of
the necessary motor programs (Heindel, Butters, & Salmon,
1988). If the mechanisms of motor control in ADHD are
similar to those of Huntington's disease, there may be other
neuropsychological similarities between the disorders.
Comparing the neuropsychological profiles of children with
ADHD with those of patients with early Huntington's disease
may provide evidence of any other similarities resulting
from caudate dysfunction.
Dysfunction in motor control systems is consistent with
the hypothesis of a deficit in selecting and modulating
appropriate behavioral responses to stimuli, rather than
underarousal, in children with ADHD (Douglas, 1984).
Underaroused children should be able to generate motor
programs, especially if stimulated by a reward, but children


49
be taken before stimulant medication is prescribed (DuPaul,
Barkley, & McMurray, 1991)-
Antidepressants have also been found to be effective in
some ADHD children who are unresponsive to psychostimulants,
but their use should be closely monitored because of
potential side effects that may be more severe than those of
the stimulants (DuPaul, Barkley, & McMurray, 1991).
Research into the efficacy of fluoxetine (Prozac) indicated
that it may provide an alternative treatment for ADHD, with
less serious side effects than other antidepressants
(Barrickman et al., 1991).
Effects of Stimulant Medications
on Cognition and Behavior
Ritalin use has produced significant increases in
performance on arithmetic, paired-associate learning, and
complex word generation tasks, but not on a task measuring
spelling ability (Douglas, Barr, O'Neill, & Britton, 1986).
Children with ADHD were able to better focus on tasks and
use their time efficiently. Cylert produced similar
improvements in cognitive functioning and may actually be
somewhat more effective with tasks requiring visuomotor


51
to support the hypothesis that in addition to improved
behavior and greater effort, stimulant medication increases
self-regulation in ADHD children (Douglas et al., 1988).
However, there appeared to be a limit to medication
efficacy. On paired-associate learning, improvement in
performance did not continue to increase with stimulant
dosage (Douglas et al., 1988), and children's academic
performance does not increase significantly with increasing
dosages (Rapport, Denney, DuPaul, & Gardner, 1994). These
results were consistent with the self-regulation hypothesis,
as children with ADHD were believed to have improved their
performance to the limit of their ability at moderate doses
of Ritalin (Douglas et al., 1988). At higher dosage levels,
ADHD children may begin to over-regulate themselves and they
become overly cautious in responding, resulting in decreased
performance. Although not all children responded positively
to the medication in all situations, the authors indicated
that every child displayed positive effects on several
measures. This called into question the practice of
evaluating a child's response to medication based on a
single measure (Douglas et al., 1988).


Developmental Problems Reported
In Children with ADHD
19
Children with ADHD have presented with a number of
developmental problems such as delays in learning to talk,
and speech and language dysfunction (Szatmari, Offord, &
Boyle, 1989b; Barkley, DuPaul & McMurray, 1990). The speech
and language problems manifested by children with ADHD can
become serious enough to require later referral for speech
and language therapy (Cantwell & Baker, 1992). As infants,
children with ADHD may have difficulty in establishing
regular sleeping and eating schedules (Hartsough & Lambert,
1985). They have been found to be significantly more
restless and overactive as infants and may be more
persistent in their demands (Barkley, DuPaul, & McMurray,
1990).
Early motor difficulties and later coordination
problems are common in children with ADHD. They crawl at a
significantly later age compared with normal controls
(Hartsough & Lambert, 1985) Children with ADHD have been
found to be delayed in learning to walk and are reported by
parents to be clumsy as children (Szatmari, Offord, & Boyle,
1989b; Mitchell, Aman, Turbott, & Manku, 1987). Although


94
were the group of interest in this study because of the
combined motor and attentional components of their symptom
pattern. Significant differences between boys and girls
with ADHD have not been identified by the research.
Children with ADHD may be at greater risk for accident and
injury than controls. Developmental, health and family
problems are highly correlated with ADHD, as are
oppositional and conduct problem behaviors. ADHD has a
high correlation with learning disabilities, possibly as a
result of similar neural substrates, but with the
independent contribution of attentional deficits. The
academic learning of these children has been well
investigated, but motor coordination deficits have not.
Differences have been found between the brains of
children with ADHD and those of normal controls. The
caudate nucleus of children with ADHD has been found to have
important differences from those of normal children, and
this structure is involved in learning motor skills. The
corpus callosum of these children may be involved in the
regulation of executive, motor, and sensory functions.
Children with ADHD may have frontal lobe dysfunction,
although tests of executive function yielded inconsistent


61
covert visual orienting task, children with ADHD disengaged
significantly more quickly than normal control from invalid
cues in the left visual field, and more quickly than they
themselves disengaged from targets in the right visual field
(Carter et al., 1995). This suggested that children with
ADHD had difficulty in sustaining attention for any target
in the left visual field and provided supporting evidence
for an underlying right hemisphere deficit (Voeller &
Heilman, 1988a). Although factors other than neurologic
dysfunction influence the development of ADHD symptoms,
developmental abnormalities of, or injury to, the right
hemisphere and its attentional and motor control structures
seem to influence attentional deficits (Voeller & Heilman,
1988a; Carter et al., 1995).
Morphological Differences in Children with adhd
Interhemispheric connections in ADHD children may
influence their ability to control of their behavior, but
the inconsistent results of morphology studies have
precluded any definite conclusions (Hynd et al., 1991;
Semrud-Clikeman et al., 1994). Morphometric analysis of the
genu, or most anterior portion of the corpus callosum,


TABLE 4
GROUP PERFORMANCES ON THE ROTARY PURSUIT*
126
(1)
GROUP
(2)
(3)
(4)
ADHD/
ADHD/
CONTROL/
CONTROL/
REWARD
NO REWARD
REWARD
NO REWARD
BLOCK 1
Mean
11.38
10.50
12.78
13.08
SD
2.85
3.57
2.46
2.54
Range
6.15-
3.51-
7.84-
10.17-
16.62
16.47
17.50
19.52
BLOCK 2
Mean
11.62
10.23
14.90
14.76
SD
3.15
3.52
3.17
3.09
Range
7.46-
3.53-
7.79-
11.77-
17.23
16.85
19.90
23.14
BLOCK 3
Mean
12.58
11.37
16.37
16.04
SD
4.11
3.21
2.60
3.77
Range
5.94-
5.60-
11.47-
11.77-
19.34
18.34
22.91
25.32
BLOCK 4
Mean
12.29
10.63
16.49
15.94
SD
3.76
3.44
3.22
3.73
Range
6.67-
5.40-
10.96-
11.42-
17.62
17.18
22.71
25.23
BLOCK 5
Mean
12.69
10.06
17.29
16.01
SD
4.34
4.21
3.72
3.91
Range
7.13-
2.02-
8.01-
11.23-
20.34
16.49
22.21
24.98
BLOCK 6
Mean
12.90
10.64
17.51
16.91
SD
4.07
4.75
3.65
3.85
Range
6.70-
2.32-
10.31-
12.39-
19.95
18.69
23.47
26.12
Measured in seconds on target


153
Barkley, R.A., Fischer, M., Edelbrock, C.S., & Smallish, L.
(1991). The adolescent outcome of hyperactive children
diagnosed by research criteria, III: Mother-child
interactions, family conflicts, and maternal
psychopathology. Journal of Child Psychology and
Psychiatry, 22, 233-255.
Barkley, R.A. & Grodzinsky, G.M. (1994). Are tests of
frontal lobe functions useful in the diagnosis of
attention deficit disorders? The Clinical
Neuropsychologist, 2, 121-139.
Barkley, R.A., Grodzinsky, G., & DuPaul, G.J. (1992).
Frontal lobe functions in attention deficit disorder
with and without hyperactivity: A review and research
report. Journal of Abnormal Child Psychology, 22, 163-
188 .
Barrickman, L., Noyes, R., Kuperman, S., Schumacher, E., &
Verda, M. (1991). Treatment of ADHD with fluoxetine: A
preliminary trial. Journal of the American Academy of
Child und Adolescent Psychiatry, 22, 762-767.
Benton, A.L., Hamsher, K.deS., Varney, N.R., & Spreen, 0.
(1983). Contributions tP Nouropgychologioal Assessment.
New York: Oxford University Press.
Berry, C.A., Shaywitz, S.E., & Shaywitz, B.A. (1985). Girls
with attention deficit disorder: A silent minority? A
report on behavioral and cognitive characteristics.
Pediatrics. 22, 801-809.
Biederman, J., Faraone, S.V., Keenen, K., Knee, D., &
Tsuang, M.T. (1990). Family-genetic and psychosocial
risk factors in DSM-III attention deficit disorder.
Journal of the American Academy of Child and Adolescent
Psychiatry, 22, 526-533.


54
not as positive as those of a normal control group (Whalen
et al., 1989).
Even in situations that demand prosocial behaviors,
children with ADHD have difficulties, despite a desire to
perform well (Buhrmeister et al., 1992). Although children
with ADHD engaged in prosocial behaviors as frequently as
controls, they simultaneously emitted higher rates of
aversive behaviors (Buhrmeister et al., 1992). Medication
reduced the rate of all social behaviors and there was less
responsiveness to social cues, without any increase in
prosocial behaviors. Medicated children with ADHD were
noted to be sad and withdrawn, (Buhrmeister et al., 1992),
but this was disputed by other research (Whalen et al.,
1989). Sadness and withdrawal appeared to negatively affect
peer ratings of these children and indicated that
controlling aversive behavior with medication alone does not
necessarily lead to more positive interactions for ADHD
children (Buhrmeister et al., 1992). Relatively normal
rates of prosocial behavior in unmedicated children with
ADHD suggested that effective interventions are those
focused on reducing aversive behavior, rather than on
increasing prosocial behavior (Buhrmeister et al., 1992).


26
more experience in evaluating behaviors and deciding whether
or not they are age-appropriate, and they observe the impact
of a child's disruptive behavior (Simeon & Wiggins, 1993).
Disruptive classroom behaviors were coupled with
academic difficulties in children with ADHD, as they were
more likely than normal controls to have been held back in
school, placed in special education, or received tutoring
(Barkley, DuPaul & McMurray, 1990; Faraone et al., 1993).
Compared to the proportion of variance accounted for by
symptoms of ADHD alone, comorbid conduct disorders had
little additive effect on problems in school, although they
increased the risk of dropping out of school in adolescence
(Barkley, Fischer, Edelbrock, & Smallish, 1990). The
independent effect of ADHD symptoms was related to their
adverse impact on academic performance and the correlation
of these symptoms with cognitive deficits (Barkley, Fischer,
Edelbrock, & Smallish, 1990; Faraone et al., 1993).
There is a highly significant association between ADHD
and developmental learning disabilities (Cantwell & Baker,
1991), but the meaning of this association has been disputed
(McGee & Share, 1988). In a review of the literature
related to ADHD and academic difficulties, McGee and Share


CHAPTER 3
THE PURSUIT ROTOR AND MOTOR SKILL ACQUISITION
The Pursuit Rotor
Description
The rotary pursuit task is a commonly used method of
investigating motor skill learning (Eysenck & Frith, 1977).
It is a simple device, consisting of a lighted target on a
rotating turntable. Subjects are expected to keep a light-
sensitive stylus in contact with the target and the total
time of contact is electronically recorded. Subjects
typically developed the motor coordination skills necessary
to increase time on target through repeated trials (Eysenck
& Frith, 1977). Distractors affected the performance of
normal subjects on the pursuit rotor, with greater amounts
of distraction causing greater difficulties in performance
(Eysenck & Thompson, 1966). Nonetheless, after a rest
period, normal subjects demonstrated normal learning for the
task. The hypothesis developed that most learning on the
80


145
medication were to significantly improve motor skill
acquisition in these children, it would provide supporting
evidence for dysfunction in a cortical-subcortical motor
programming loop. Significantly better motor learning in
medicated children with ADHD would also support the use of
stimulants as an effective intervention for incoordination.
Although the ADHD group as a whole demonstrated
deficits in motor learning, there was some overlap in the
performances of individual children in the ADHD and control
groups. Traditionally, children with ADHD have been
subtyped based on symptoms of inattention, impulsivity, and
hyperactivity. However, these symptoms may be only part of
the picture for some children with ADHD. The wide
variability in individual motor abilities within the ADHD
group suggested that developmental motor problems may
overlay inattention and impulsivity in some children with
ADHD. It may be important to identify the subgroup of ADHD
children with these problems, as they may have additional
difficulties in academic and athletic situations.
Children with a formal diagnosis of learning disability
were excluded from this study, but comorbid learning
disabilities are common in children with AJDHD. Research


22
normal, and fine hair are all significantly more common in
children with ADHD than in normal controls.
Mixed evidence exists concerning the influence of
maternal health and pre- and perinatal factors on the
incidence of ADHD. Poor maternal health, toxemia or
eclampsia during pregnancy, and a maternal age younger than
twenty were found to differentiate mothers of ADHD children
from mothers of normal controls (Hartsough & Lambert, 1985).
Significantly longer labor and later gestational age were
also correlated with ADHD in the child. Another study
(Barkley, DuPaul, & McMurray, 1990) found evidence for none
of these factors. Low birth weight was found to be
correlated with ADHD by Szatmari, Offord, and Boyle (1989b)
and Mitchell, Aman, Turbott, and Manku (1987), but was not
found to be significant by Hartsough and Lambert (1985) or
Barkley, DuPaul, and McMurray (1990). Research on the
effect of fetal distress at birth has also produced
contradictory findings, with some research indicating a
significant correlation with ADHD (Hartsough & Lambert,
1985), while others do not (Barkley, DuPaul, & McMurray,
1990). The existence of difficulties in toilet training has
also been disputed by investigators. Nevertheless, it


56
1987), but academic performance was enhanced only by
medication (Carlson, Pelham, Milich, & Dixon, 1992).
Medication also positively influenced the self-ratings of
children with ADHD. The singular effect of medication
indicated deficient self-regulation (Douglas, 1984), and
medication appeared to augment the self-regulatory system.
Behavior therapy alone was found to be as effective as a low
dose of Ritalin in controlling disruptive behavior, but it
did not increase positive self-ratings (Carlson, Pelham,
Milich, & Dixon, 1992). Feedback on the children's
behavior, as applied in this condition, may have helped
control their behavior, but negatively impacted self-
ratings. A combination of behavior therapy and low-dose
medication was as effective in effecting behavior change as
high-dose medication alone, suggesting that combined
treatments can reduce medication use (Carlson, Pelham,
Milich, & Dixon, 1992). The authors noted that between-
subject differences played a significant role in the
effectiveness of either treatment and should be considered
when designing an intervention program.


120
between ADHD status and change in performance over blocks.
No significant change was found in the performance of the
ADHD group over blocks.
In contrast to the ADHD group, the control group
demonstrated a significant change in performance over
blocks, F (5, 160) = 36.17, p < .001. T-tests were then
used for pairwise comparisons between blocks to determine
when motor learning took place. For the control group,
Block 1 time on target was significantly lower than Block 2
and Block 2 was significantly lower than Block 3 (Table 5).
There were no other significant differences between
successive blocks (Table 5).
Comparison of Group Differences on Blocks
T-tests were used in pairwise comparisons to
investigate group differences on the six blocks of rotary
pursuit trials. The ADHD group had significantly less time
on target than the Control group on each of the six blocks
(Table 6).


53
as to its effectiveness on other aspects of their behavior
(DuPaul, Barkley, & McMurray, 1994). Although Ritalin
significantly reduced inattention and impulsivity in a group
of children with comorbid ADHD and internalizing symptoms,
it did not significantly improve the academic functioning of
these children {DuPaul, Barkley, & McMurray, 1994). In
fact, the academic functioning of children with ADHD and a
relatively greater number of internalizing symptoms may
actually decline, although further research is needed to
confirm this result (DuPaul, Barkley, & McMurray, 1994).
Medication Effects on Social Skills
Social behaviors in ADHD children are affected by
medication in several ways {Whalen et al., 1989; Buhrmeister
et al., 1992). Unmedicated children with ADHD were
significantly more socially engaged than controls,
suggesting that these children need social stimulation
(Buhrmeister et al., 1992). These children face
difficulties because their social interactions are generally
considered aversive by other children {Berry, Shaywitz, &
Shaywitz, 1985). Ritalin use resulted in improved peer
ratings of children with ADHD, but these ratings were still


12
Sluggish cognitive tempo in children with ADD/WO has
been a consistent finding in the research {Lahey et al.,
1988; Barkley, DuPaul, and McMurray, 1990). A factor-
analytic investigation of both the teacher-completed SNAP
checklist (Pelham, Atkins, & Murphy, 1981) and a set of
clinician-rated symptoms provided evidence for slowed
cognitive tempo, inattention, and disorganization in
children with ADD/WO (Lahey et al., 1988). The SNAP yielded
two factors, inattention-disorganization and motor
hyperactivity-impulsivity, suggesting that inattention can
be separated from hyperactivity, resulting in at least two
distinct behavioral syndromes involving attention. In
addition to inattention-disorganization and hyperactivity-
impulsivity, a factor identified as sluggish cognitive tempo
emerged from the clinician ratings of clinic-referred
children. Slowed cognitive tempo may not have been
identified on the SNAP because no items on the checklist are
related to this symptom cluster (Lahey et al., 1988).
Sluggish cognitive tempo was related to the drowsiness and
forgetfulness that had been previously identified (Lahey,
Schaughency, Frame, & Strauss, 1985) in teacher ratings of
children with ADD/WO. In addition, slowed tempo is


82
speed appeared necessary for younger children. Older
children showed greater improvement with practice, but never
achieved adult levels of performance (Davol, Hastings, &
Klein, 1965). Socioeconomic status may affect motor
learning at younger ages, but this difference disappears
among older children (Davoll & Breakell, 1968). Davoll,
Hastings, and Klein (1965) noted that young children may
find the rotary pursuit task fatiguing and repetitive. In
order to increase the motivation of these children,
reinforcement should be applied.
Children defined as "clumsy," who had significant motor
incoordination but were normal on neurological examination,
performed worse than normal controls on the rotary pursuit
task (Lord & Hulme, 1988). However, they did show a steady
increase in their ability to stay on target across trials,
suggesting a transfer from visual feedback control of motor
systems to the development of motor programs (Heindel,
Butters, & Salmon, 1988). Impairment in initial encoding,
through processing of visual feedback, may be a more
important factor in clumsiness than the inability of these
children to develop effective motor programs (Lord & Hulme,
1988). Nonetheless, these children did not approach normal


104
correlated with g, or general cognitive ability at r=.79 and
r=.74, respectively (Sattler, 1992).
The Continuous Performance Test (CPT) was used as a
measure of sustained attention and impulsivity. The CPT has
been shown to be a valid measure of attention problems,
especially through the number of correctly identified
targets, and errors of omission score (Barkley, Grodzinsky,
& DuPaul, 1992; Barkley & Grodzinsky, 1994). Impulsivity is
often measured through the errors of commission score
(Barkley & Grodzinsky, 1994). The version of the CPT used
in this study (Conners, 1994) was divided into two five-
minute subtests. During that time, a sequence of letters
was displayed on a computer screen. The first subtest was a
cancellation task that required a response when the target
letter "X" appeared, while the second subtest was a
conditional cancellation task, requiring responses to a
target letter sequence, "XA", The CPT was scored by
computer and errors of commission, errors of omission, hit
percentage (percentage correct), and reaction time scores
were produced. Errors of commission and reaction time
provided a baseline estimate of the child's impulsivity,


154
Biederman, J., Faraone, S.V., Spencer, T., Wilens, T.,
Norman, D., Lapey, K.A., Mick, E,, Lehman, B.K., &
Doyle, A. (1993) Patterns of psychiatric comorbidity,
cognition, and psychosocial functioning in adults with
attention deficit hyperactivity disorder. American
Journal of Psychiatry. 150, 1792-1798.
Biederman, J., Wilens, T. Mick, E., Milberger, S., Spencer,
T.J., & Faraone, S.V. (1995). Psychoactive substance
use disorders in adults with Attention Deficit
Hyperactivity Disorder (ADHD): Effects of ADHD and
psychiatric comorbidity. American Journal of
Psychiatry. 152, 1652-1658.
Blouin, A.G., Conners, C.K., Seidel, W.T., 5c Blouin, J.
(1989). The independence of hyperactivity from conduct
disorder: Methodological considerations. Canadian
Journal of Psychiatry. 21/ 279-282.
Breen, M.J. (1989). Cognitive and behavioral differences in
ADHD boys and girls. Journal of Child Psychology and
Psychiatry/ 2Q., m-iie.
Buhrmester, D., Whalen, C.K., Henker, B., MacDonald, V., 5c
Hinshaw, S.P. (1992). Prosocial Behavior in hyperactive
boys: Effects of stimulant medication and comparison
with normal boys. jQurnal of Abnormal child Psychology,
20./ 103-121.
Cantwell, D.P. 6c Baker, L. (1991). Association between
Attention Deficit Hyperactivity Disorder and learning
disorders. Journal-Pf Learning Disabilities/ 24, 88-95.
Cantwell, D.P. 5c Baker, L. (1992). Attention deficit
disorder with and without hyperactivity: A review and
comparison of matched groups. Journal of the American
Academy of Child and Adolescent Psychiatry. 21, 432-
438 .


115
index of social status, was significantly higher than that
of the group of children with ADHD (X2 (4) = 10.59, p =
.05). There were significantly more girls in the control
group than in the ADHD group (X2 (1) = 6.89, p = .01).
Significantly more children in the ADHD group than in the
control group were receiving tutoring or other academic
assistance (X2 (1) = 12.62, p < .01) and there was a trend
towards more comorbid diagnoses in the ADHD group compared
to the control group (X2 (2) = 5.77, p = .06).
Parent Report Measures
Parents of children in the ADHD group reported
significantly more disruptive behaviors on the CPRS-R than
parents of children in the control group (p (62) = 7.57, p <
.001; Table 2). Children in the ADHD group were reported to
meet significantly more of the DSM-IV diagnostic criteria
for ADHD than children in the control group (p (62) = 12.84,
P< .001; Table 2).


65
also been implicated in the control of attention (Luria,
1973).
Cerebral blood flow changes in the sensory and
sensorimotor regions of cortex have been demonstrated in
children with ADHD (Lou et al., 1989). Increases in blood
flow to the occipital lobe have been linked to an inability
to screen out irrelevant visual information (Lou,
Henrickson, & Bruhn, 1990). As other sensory cortices
demonstrated similar changes, it appears that there is a
lack of inhibitory control of sensory input, perhaps a
result of disrupted striatal connections to the thalamus
(Lou, Henrickson, & Bruhn, 1990). Consistent with the
hypothesis of deficient self-regulation (Douglas, 1983),
this may create difficulties for children with ADHD in
screening sensory input (Lou, Henrikson, & Bruhn, 1990).
Brain Metabolism in Children with ADHD
Glucose metabolism is the main source of energy for the
brain, so measurement of this process is another indicator
of the functional activity of brain structures (Chugani,
Phelps, & Mazziotta, 1987). During performance of a simple
attention task, the left prefrontal area was significantly


15
Recent changes in methodology have resulted in more
consistent findings of cognitive differences between the
attention deficit subtypes, differences that are consistent
with the behavior pattern of each group (Goodyear & Hynd,
1992). A review of the literature indicated that there were
differences in information processing styles between the
subtypes (Goodyear & Hynd, 1992). Children with ADD/H were
hypothesized to have input difficulties related to their
attention deficits, while ADD/WO children were believed to
have output problems related to their slower rate of
cognition, and deficits in automatized information
processing similar to those of children with learning
disabilities. Support for this view came from findings that
children with ADD/H were impaired on tests of sustained
attention and behavioral inhibition, while children with
ADD/WO had deficits in focused attention and slowed
cognition (Barkley, DuPaul, & McMurray, 1990) These
authors reported differences between the two subtypes in the
performance of several tasks. ADD/WO children were found to
have significantly more difficulty than ADD/H children on
the WISC-R Coding subtest and on tests of long-term verbal
memory. Children with ADD/WO demonstrated lower levels of


70
are believed to be frontal lobe functions (Luria, 1973).
Impulsivity leads to errors of commission, while
inattentiveness leads to errors of omission (Grodzinsky &
Diamond, 1992). The deficient performances of children with
ADHD on vigilance tasks make these tests effective in
measuring the intensity of ADHD symptoms (Barkley &
Grodzinsky, 1994). Children with ADHD made errors of
commission significantly more often than children with
learning disabilities or normal controls and this measure
separated the performance of children with ADHD from normal
children (Barkley, & Grodzinsky, 1994; Seidman et al. ,
1994). Adolescents with ADHD continued to have difficulty
with vigilance tasks, but were not more distractible than
normal controls, suggesting maturational effects (Fischer,
Barkley, Edelbrock, & Smallish, 1990).
Aside from the results of vigilance tasks, which were
fairly consistent across studies, tests of frontal lobe
functioning have produced mixed results in children with
ADHD. The Stroop Interference Task, which requires subjects
to name a stimulus while inhibiting a conflicting response,
differentiated children with ADHD from normal controls in
some studies (Grodzinsky & Diamond, 1992; Barkley,


166
Shue, K.L. & Douglas, V.I. (1992). Attention deficit
hyperactivity disorder and the frontal lobe syndrome.
Brain and Cognition, 22, 104-124.
Simenson, R.J. (1973). Acquisition and retention of a motor
skill by normal and retarded students. Perceptual and
Motor Skills. 22, 791-799.
Simeon, J.G. & Wiggins, D.M. (1993). Pharmacotherapy of
attention deficit hyperactivity disorder. Canadian
Journal_of Psychiatry. 22, 443-448.
Smith, M.L. (1988). Recall of spatial location by the
amnesic patient H.M. Brain and Cognition. 2, 178-183.
Spreen, O., Tupper, D., Risser, A., Tuokko, H., & Edgell, D.
(1984). Human Developmental Neuropsychology. New York:
Oxford Press.
Still, G.F. (1902). Some abnormal psychical conditions in
children. Lancet. i, 1008-1012, 1077-1082, 1163-1168.
Swanson, J.M., Cantwell, D., Lerner, M., McBurnett, K., &
Hanna, G. (1991). Effects of stimulant medication on
learning in children with ADHD. Journal of Learning
Disabilities. 21, 219-230.
Szatmari, P., Offord, D.R., & Boyle, M.H. (1989a). Ontario
Child Health Study: Prevalence of attention deficit
disorder with hyperactivity. Journal of Child
Psychology and Psychiatry. 22, 219-230.
Szatmari, P., Offord, D.R., & Boyle, M.H. (1989b).
Correlates, associated impairments, and patterns of
service utilization of children with attention deficit
disorder: Findings from the Ontario Child Health Study.
Journal of Child Psychology and Psychiatry. 22, 205-
217.
Trites, R.L., Blouin, A.G.A., & Laprade, K. (1982). Factor
analysis of the Conners Teacher Rating Scale based on a
large normative sample. Journal of Consulting and
Clinical Psychology, 22,(5), 615-623.


CHAPTER 7
RESULTS
Initial Analyses
Experimenter Effects
T-tests were performed to compare the protocols
completed by the primary investigator and the graduate
research assistant most involved in the study. The second
graduate assistant completed too few protocols (n = 4) for
analysis. No significant differences between the two raters
were found on IQ estimates, measures of attention, fine
motor coordination, and judgement of spatial orientation, or
pursuit rotor performance.
Demographic Analyses
No significant differences were found between the ADHD
group and the control group for age (£. (62) = -.19, ns) or
ethnicity (X2 (4) = 8.32, ns). Socioeconomic status of the
control group, based on Hollingshead's (1975) four-factor
114


23
seemed that these problems are present in some ADHD children
and may be significantly more common than in children
without ADHD (Hartsough & Lambert, 1985).
Comorbid Psychiatric Diagnoses
in Children with adhp
Hyperactivity is closely related to other disruptive
behavior disorders, as research has found that 40% to 60% of
children with ADHD have been found to have a comorbid
conduct disorder (Szatmari, Offord, & Boyle, 1989a; Barkley,
Fischer, Edelbrock, & Smallish, 1990). The Conduct Disorder
and Attention Problem subscales of the Revised Behavior
Problem Checklist (RBPC) had a shared variance of between 20
and 31 percent (Quay & Peterson, 1983). In addition there
were high correlations between attention-deficit and
antisocial behavior factors on both the Conners Teacher
Rating Scale (TRS) and the original Behavior Problem
Checklist (BPC; Arnold, Barneby, & Smeltzer, 1981). These
correlations emerged when these authors factor-analyzed
items from these scales, treating all 93 items as if they
constituted a single measure. The hyperkinetic factor on
the two scales correlated at i = .86, supporting the


119
Pursuit Rotor Analyses of Group Performances
A repeated measures ANOVA was used to analyze the
effect of ADHD status and reward condition on pursuit rotor
performance. Initially, socioeconomic status, gender,
comorbid diagnoses, and tutoring/other academic help were
used as covariates, as preliminary analyses found
significant differences between the ADHD and control groups
on these variables. However, no significant effect was
found for any covariate and these variables were removed
from the model. The reward condition was also not found to
be significant as a main effect or in any interaction.
Therefore, this variable was removed from the model and the
four conditions were collapsed into ADHD and Control groups.
Further analyses were performed on this reduced model.
The reduced-model repeated measures ANOVA found
significant effects for ADHD status, F (1,62) = 28.20, p <
.001, and learning over blocks, F (5,310) = 21.17, p < .001.
A significant interaction was found between ADHD status and
learning, F (5,310) = 9.52, p < .001.
Separate repeated measures ANOVAs were performed for
the ADHD and control groups to investigate the interaction


157
Dupaul, G.J. & Barkley, R.A. (1990). Medication treatment.
In Barkley, R.A. (Ed.)# Attention Deficit Hyperactivity
Disorder: A Handbook for Diagnosis and Treatment. New
York: Guilford Press.
DuPaul, G.J.# Barkley, R.A., & McMurray, M.B. (1991).
Therapeutic effects of medication on ADHD: Implications
for school psychologists. School_Psychology Review. 2Q,
203-219.
DuPaul, G.J., Barkley, R.A., & McMurray, M.B. (1994).
Response of children with ADHD to methylphenidate:
Interaction with internalizing symptoms. Journal of the
Amer.i.can.Ac-3demy of child and Adolescent Pgyohiatry,
H, 894-903.
Eysenck, H.J. & Frith, C.D. (1977). Reminiscence,
Motivation, and Personality; A case study in
experimental psychology. New York: Plenum.
Eysenck, H.J. & Thompson, W. (1966). The effects of
distraction on pursuit rotor learning, performance, and
reminiscence. British Journal of Psychology. 57. 99-
106.
Faraone, S.V., Biederman, J., Lehman, B.K., Spencer, T.,
Norman, D., Seidman, L.J., Kraus, I, Perrin, J., Chen,
W.J., & Tsuang, M.T. (1993). Intellectual performance
and school failure in children with attention deficit
hyperactivity disorder and in their siblings. Journal
of Abnormal Psychology. 102, 616-623.
Farmer, J.E. & Peterson, L. (1995). Injury risk factors in
children with Attention Deficit Hyperactivity Disorder.
Health Psychology. 14., 325-332.
Fischer, M., Barkley, R.A., Edelbrock, C.S., & Smallish, L.
(1990). The adolescent outcome of hyperactive children
diagnosed by research criteria, II: Academic,
attentional, and neuropsychological status. Journal of
Consulting and Clinical Psychology, 580-588.


24
criteria used for measuring hyperactivity (Arnold, Barneby,
& Smeltzer, 1981). The hyperkinetic factor on the TRS and
RBPC had correlations of between .69 and .77 with the
rebellious unsocialized and antisocial immature factors on
the TRS, indicating significant overlap between disruptive
behavior disorders (Arnold, Barneby, and Smeltzer, 1981).
Despite the high correlations between ADHD and other
disruptive behavior disorders, evidence supported ADHD as a
distinct diagnosis (Blouin, Conners, Seidel, & Blouin,
1989). Comparisons between groups of clinically referred
children have shown that inattention and impulsivity
separate ADHD children from conduct disordered or anxious
children (Halperin et al, 1993). The codiagnosis of
oppositional or conduct disorder is often given to children
with ADHD when they respond to conflicts in structured
situations with violations of major rules and laws (Barkley,
1990; Wells & Forehand, 1985). Comorbid conduct disorder
was associated with increased cigarette, alcohol, and
marijuana use in children with ADHD compared to controls
(Barkley, Fischer, Edelbrock, & Smallish, 1990).
Children with ADHD are also frequently diagnosed with a
comorbid mood disorder, such as depression or bipolar


Offord, & Boyle, 1989a), making research with this group of
children difficult. The scarcity of data on children with
4
ADD/WO led the developers of the DSM-III-R (American
Psychiatric Association, 1987) to recognize only Attention
Deficit Disorder with hyperactivity as a diagnostic category
(Goodyear & Hynd, 1992). The diagnostic criteria for ADHD
in the DSM-III-R were as follows:
Attention Deficit Hyperactivity Disorder
Note: Consider a criterion met only if the behavior is
considerably more frequent than that of most people of
the same mental age.
A. A disturbance of at least six months during which
at least eight of the following are present:
(1) often fidgets with hands or feet or squirms in seat
(in adolescents may be limited to subjective feelings
of restlessness)
(2) has difficulty remaining seated when required to do
so
(3) is easily distracted by extraneous stimuli
(4) has difficulty awaiting turn in games or group
situations
(5) often blurts out answers to questions before they
have been completed
(6) has difficulty following through on instructions
from others (not due to oppositional behavior or
failure of comprehension), e.g., fails to finish chores


77
attention and concluded that underarousal in this area
causes disinhibition of irrelevant input. However, this
conclusion was based on disorders, such as depression, that
cause secondary problems in vigilance and they did not
directly investigate vigilance in ADHD (Weinberg & Harper,
1993). Competing explanations for sustained attention
deficits in ADHD, such as the difficulties in self
regulation proposed by Douglas (1983), suggest that it is
not only the posterior attention system that is involved in
ADHD. Other impairments, such as impaired active shifting
of attention, are controlled by different neural structures,
discussed below (Voeller & Heilman, 1988a).
The brain region most involved with attention and
cognitive regulation appears to be the prefrontal cortex
(Posner, 1992), thought to be responsible for active
shifting of attention (Mirsky et al., 1991). Planning and
organization of behavioral responses to environmental
stimulation is also an important component of frontal lobe
activity (Cohen, 1993). These skills have been found to be
deficient in children with ADHD (Shue & Douglas, 1992).
Unmedicated children with ADHD had normal recognition for
the spatial location of pictures presented to them in a


159
Haxby, J.V., Grady C.L., Ungerlieder, L.G., & Horwitz, B.
(1991). Mapping the functional neuroanatomy of the
intact human brain with brain work imaging.
Neuropgychologia, 22, 539-555.
Heiligenstein, E. & Keeling, R.P. (1995). Presentation of
unrecognized Attention Deficit Hyperactivity Disorder
in college students. Journal of American College
Health. 41, 226-228.
Heindel, W.C., Butters, N., & Salmon, D.P. (1988). Impaired
learning of a motor skill in patients with Huntington's
disease. Behavioral Neuroscience. 102. 141-147.
Heitman, R.J. & Gilley, W.F. (1989), Effects of blocked
versus random practice by mentally retarded subjects
learning a novel skill. Perceptual and Motor Skills.
£2., 443-447.
Hinshaw, S.P. (1992). Academic underachievement, attention
deficits, and aggression: Comorbidity and implications
for intervention. Journal of Consulting and Clinical
Psychology. £2, 893-903.
Horgan, J.S. (1982). Comparison of mildly mentally retarded
and nonretarded children on a rotary pursuit task under
optimal task conditions. American Journal of Mental
Deficiency, £7, 316-324.
Horn, P.W. (1975). Pursuit rotor speed, sex differences, and
reminiscence in young children. The Journal of
Psychology. 11, 81-85.
Hynd, G.W., Hern, K.L., Novey, E.S., Eliopulos, D.,
Marshall, R., Gonzalez, J.J., & Voeller, K.K. (1993).
Attention deficit disorder and asymmetry of the caudate
nucleus. Journal pf Child Neurology, 1, 339-347.


96
acquisition in children with ADHD and attempted to explain
any differences that were found when these children were
compared to normal controls. Deficits in performance were
believed to be primarily due to deficits in the formation of
motor programs, with impulsivity and inattention resulting
in additional deficits. The inattention and impulsivity
characteristic of children with ADHD was modulated in a
reward for performance condition.
Specific hypotheses were as follows:
(1) Children with ADHD in the reward for performance
condition were expected to have deficits in motor learning
compared to normal controls. The reward situation attempted
to control for attention without the use of medication that
might have also enhanced motor skill acquisition (Douglas,
1984) .
(2) Children with ADHD in the no reward learning situation
were expected to have added deficits resulting from
impulsive responding and inattention to the task (Douglas,
1984) .
(3) Significant group differences were expected between
children with ADHD and normal controls on measures of fine
motor coordination (Barkley & Grodzinsky, 1994) and


16
off-task behaviors and less impulsivity during a vigilance
task, but their overall performance was similar to that of
children with ADD/H (Barkley, DuPaul, & McMurray, 1990).
Neuropsychological tests of fine motor speed, planning,
sequencing, and problem solving did not distinguish ADHD
subgroups in a study by Barkley, Grodzinsky, and DuPaul
(1992) or more recently in research by Barkley and
Grodzinsky (1994).
Overall, research has indicated that of the DSM-IV
subtypes, ADHD-Combined and ADHD-Primarily Inattentive have
sufficient empirical support. The evidence for the third
subtype, ADHD-Primarily Hyperactive/Impulsive, was not as
strong and the basis for this diagnosis was not clear. It
is the combination of motor hyperactivity and attentional
components that makes the children with ADHD-Combined type
of interest to the current study. Further references to
children with ADHD will include only this group of children.
The different cognitive style of children with ADD/WO may
introduce confounds into a study of motor learning and they
will be excluded from the current study.


TABLE 7
REGRESSION MODEL
Beta t
ATTENTION
Omission errors (Cancellation) ,004 .03
Omission errors (Conditional) -.138
IMPULSIVITY
Commission errors (Cancellation) -.070 -.44
Commission errors (Conditional) -.359 -3.03
FINE MOTOR COORDINATION
Grooved Pegboard (non-dominant) -.192 -1.28
SPATIAL JUDGEMENT
JLO (# correct) .075 .58
129
U
ns
ns
<.01
ns
ns


66
less active in adolescents with ADHD than in normal
controls, (Zametkin et al., 1993). Metabolism in this area
had a significant negative correlation with the severity of
ADHD symptoms (Zametkin et al., 1993). Adolescents with
ADHD had significantly higher metabolic rates in a portion
of the left parietal lobe, a finding that may be consistent
with their sensory processing deficits (Lou, Henrickson, &
Bruhn, 1990). Although these findings contradicted evidence
of right frontal lobe involvement in ADHD, they
differentiated between adolescents with ADHD and controls in
the absence of overall differences in brain metabolism
(Zametkin et al., 1993).
Adults with a childhood history of ADHD did have a
lower rate of total brain metabolism than normal controls,
perhaps as a result of the disorder's effects on maturation
(Zametkin et al., 1990). Adults with ADHD also had lower
metabolic rates in the somatosensory cortex (Zametkin et
al., 1990). Consistent with the findings in adolescents,
the greatest reduction in metabolic activity was found in
the left prefrontal regions of the adults with ADHD
(Zametkin et al., 1990).


TABLE 1
DEMOGRAPHICS
113
TOTAL
ADHD
CONTROL
SAMPLE
GROUP
GROUP
(N=64)
(N=31)
(N=33)
CHILD'S SEX
Male
46
27
19
Female
18
4
14
CHILD'S AGE
7
9
6
3
8
19
9
10
9
11
3
8
10
15
7
8
11
10
6
4
SOCIOECONOMIC STATUS (Hollingshead)
1 1
1
0
2
8
6
2
3
10
8
2
4
25
8
17
5
20
8
12
RACE
White
51
27
24
Minority
13
4
9
African-American
5
2
3
Hispanic
6
0
6
Native American
1
1
0
Biracial
1
1
0
PSYCHIATRIC MEDICATION
None
36
3
33
Stimulants
27
27
0
Other
1
1
0
COMORBID DIAGNOSES
None
59
26
33
Oppositional/Defiant
3
3
0
Other/Combined
2
2
0


28
behaviors, they are not necessarily causative of ADHD. For
example, the ADHD/LD children in the Pennington, Groisser,
and Welsh (1993) study displayed significant conduct
problems in addition to attention deficits. The children
with ADHD/LD also had significantly higher rates of family
instability and this combined with academic failure, rather
than a primary ADHD, may have led to disruptive behavior in
some of these children (Pennington, Groisser, & Welsh,
1993) .
Further evidence against the causative link between
learning disabilities and ADHD was provided by findings that
preschoolers with ADHD have difficulties with independent
work and following rules in a structured setting
(Alessandri, 1992). Developmental problems related to ADHD
may cause cognitive impairments that lead to academic
difficulties, even when there is no co-occurring learning
disability diagnosis (Szatmari, Offord, & Boyle, 1989b).
Symptoms of ADHD are often present before 4 years of age
(Barkley, Fischer, Edelbrock, & Smallish, 1990) and academic
problems were linked to pre-existing impulsivity and
inattention in children with ADHD (Barkley,1990). Prior to
enrollment in school, or even if enrolled in preschool, a


CHAPTER 2
CENTRAL NERVOUS SYSTEM DYSFUNCTION IN ADHD
The Impa-C-t of Right Hemisphere Dysfunction on ADHD
Research on the etiology of ADHD has focused on the
neurological basis for this disorder and on the possible
reasons for any brain dysfunction, as important differences
have been found in the neurology of children with ADHD
compared to control children (Barkley, 1990). Right
hemisphere abnormalities were found on CAT scans of nine of
fifteen children referred for behavioral and learning
problems, and all of these children met criteria for
attention deficit disorder (Voeller, 1986). These children
also had difficulties reading social cues and modulating the
cues they projected (Voeller, 1986). As a group, they were
withdrawn and isolated and did not respond well to
psychotherapy. Although the symptoms of these children are
similar in many ways to those of ADHD children, the
interpersonal problems of these children could not be
entirely attributed to attention deficits (Voeller, 1986),
59


55
Behavioral and Combined Treatment Strategies
Treatment of ADHD often involves combining
psychostimulant medication with a behavioral modification
program and parent training (Simeon & Wiggins, 1993;
Barkley, 1983). Training for parents of children with ADHD
generally consists of teaching behavioral principles such as
positive reinforcement and time-out, and having parents
recognize their own contributions to the child's behavior
(Barkley, 1983). Behavioral methods are often directly
related to parent training and involve the application of
contingency management strategies both at home and in
school. The goal of behavior modification programs is to
help the child control his own behavior, but they may be
difficult to implement without concomitant medication
intervention and may be more costly in terms of time and
money (Barkley, 1983; Murray, 1987). Despite these
constraints, behavioral approaches may be useful for
children with ADHD who are not responsive to medication
(Murray, 1987).
The combination of stimulant medication and behavior
therapy improved the behavior of children with ADHD (Murray,


60
Nevertheless, the finding that ADHD is closely correlated to
right hemisphere deficits is consistent with data concerning
symptoms of inattention and motor impersistence in adults
and children with right-sided brain injuries (Voeller &
Heilman, 1988a).
Consistent with other evidence of right hemisphere
dysfunction in children with ADHD, these children made
significantly more left-sided errors than normal controls on
a letter cancellation task (Voeller & Heilman, 1988a). The
authors carefully selected only subjects who met all DSM-III
criteria for attention deficit disorder and were not
children with a conduct disorder mislabeled as ADHD. The
children with ADHD also had subtle left-sided neurologic
signs and had problems sustaining voluntary movements, a
difficulty often seen in adults with right hemisphere injury
(Voeller & Heilman, 1988b).
Attentional functions such as focusing on a target and
then disengaging to refocus on the next target are believed
to reside in the right hemisphere (Voeller & Heilman,
1988a). Children with ADHD demonstrated deficits on tasks
requiring them to fixate on a stimulus, both with and
without distractions (Voeller & Heilman, 1988b). On a


123
no significant relationship between socioeconomic status and
the learning index (r = .27).
To identify the factors underlying the range of motor
learning abilities, the relationship between fine motor
coordination (Grooved Pegboard) and the learning index was
examined using t-tests to compare children in the top and
bottom quartiles of the learning index. No significant
differences were found between these groups on either the
dominant (£ (3 0) = 1.04, ns) or nondominant hands (£. (30) =
1.88, ns). ADHD group children in the upper and lower
quartiles of the learning index were not significantly
different on the dominant (£ (14) = 1.92, ns) or nondominant
(L (14) = 1.14, ns) hands. No significant differences in
fine motor coordination were found in control group children
in the upper and lower quartiles of the learning index
(Dominant hand, t, (14) = .00, ns; Nondominant hand, £. (14) =
.26, ns).


14
Neuropsychological Studies of ADD/H
and-ADD/WO Children
Differences between ADD/H and ADD/WO children have been
found to exist on neuropsychological measures, but the exact
nature of these differences was not always clear.
Methodological difficulties, especially the relative rarity
of children with ADD/WO made it difficult to carry out these
studies (Goodyear & Hynd, 1992). Some authors suggested
that behavioral, rather than neuropsychological, criteria
should be used to differentiate between the subtypes (Hynd,
et al., 1989). These researchers found that children with
attention deficits and clinic-referred controls had similar
performances on simple reaction time tasks. A task
requiring speeded matching of letter strings, the most
difficult task in the study, did discriminate between
children with attention deficits and clinic-referred
controls, with the ADD children performing worse than the
control children. However, there was no significant
difference in the performance of ADD/H and ADD/WO children
on these tasks, suggesting little difference in the
neuropsychology of the subtypes (Hynd et al., 1989).


160
Hynd, G.W. Nieves, N., Conner, R.T., Stone, P., Town, P.,
Becker, M.G., Lahey, B.B., & Lorys, A. R. (1989).
Attention deficit disorder with and without
hyperactivity: Reaction time and speed of cognitive
processing. Journal of Learning Disabilities, 22, 573-
580 .
Hynd, G.W., Semrud-Clikeman, M., Lorys, A.R., Novey, E.S., &
Eliopulos, D. (1990). Brain morphology in developmental
dyslexia and attention deficit disorder/hyperactivity.
Archives of Neurology; 12, 919-926.
Hynd, G.W., Semrud-Clikeman, M., Lorys, A.R., Novey, E.S.,
Eliopulos, D., & Lyytinen, H. (1991) Corpus callosum
morphology in attention deficit hyperactivity disorder:
Morphometric analysis of MRI. Journal of Learning
Disabilities. 21, 141-146.
Hynd, G.W., Voeller, K.K., Hern, K. J., & Marshall, R.M.
(1991). Neurobiological basis of attention deficit
hyperactivity disorder (ADHD). School Psychology
Review, 20, 174-186.
Kataria, S., Wong, M.M., Hall, C.W., & Keys, G.F. (1992).
Learning styles of LD and NLD ADHD children. Journal of
Clinical Psychology. 48. 371-378.
Klonoff, H. 8t Low, M. (1974) Disordered brain function in
young children and early adolescents:
Neuropsychological and electroencephalographic
correlates. In Reitan, R.M. & Davison, L.A., Clinical
neuropsychology: Current status and applications, pp.
121-178. Washington, D.C.; V.H. Winston & Sons.
Kolb, B. & Milner, B. (1981). Performance of complex arm and
facial movements after focal brain lesions.
Neuropsycholoaia. 12, 491-503.
Koziol, L.F. & Stout, C.E. (1992). Use of a verbal fluency
measure in understanding and evaluating ADHD as an
executive function disorder. Perceptual and Motor
Skills. 71, 1187-1192.