Rotary pursuit performance in children with attention deficit hyperactivity disorder


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Rotary pursuit performance in children with attention deficit hyperactivity disorder
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viii, 169 leaves : ; 29 cm.
Colvin, Andrew
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Subjects / Keywords:
Research   ( mesh )
Attention Deficit Disorder with Hyperactivity -- Child   ( mesh )
Attention Deficit Disorder with Hyperactivity -- Infant   ( mesh )
Motor Skills   ( mesh )
Practice (Psychology)   ( mesh )
Motivation   ( mesh )
Attention   ( mesh )
Reward   ( 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 )
bibliography   ( marcgt )
non-fiction   ( marcgt )


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

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University of Florida
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All applicable rights reserved by the source institution and holding location.
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aleph - 002286965
oclc - 49346323
notis - ALP0116
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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


project. Without the love, understanding and patience of my

wife, Cheryl Colvin, this dissertation would not have been







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


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 . .


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


* ii



. 2
. 6





. 80


. 87

Neuroanatomy of Motor Systems


Summary . .
Specific Aims and Hypotheses



Subjects .
Measures .
Procedure . .

7. RESULTS . .

Initial Analyses .
Neuropsychological Measures .
Analyses of Pursuit Rotor Perf


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




REFERENCES ..........


. 89

. 93

.. 93
. . 95


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. 116
ormance 117

. 131

. 132
. 133
. 135
. 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



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


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


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





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.


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,


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

(3) is easily distracted by extraneous stimuli

(4) has difficulty awaiting turn in games or group

(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

(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

(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,


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

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:


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

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

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

(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

(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:


(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

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

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


(g) often blurts out answers before questions have been

(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

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

(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.,


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


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,


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


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


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


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,


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


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


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,


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


independent contribution, comorbid oppositional-defiant or

conduct disorders made a significant contribution to family

conflicts (Anastopoulos, Guevremont, Shelton, & DuPaul,


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


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


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


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).


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


by children with ADHD when they learn any novel skill

(Leavell, Ackerson, & Fischer, 1995).


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).



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


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.


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


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,


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).


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


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

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,


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


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,


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



The Pursuit Rotor


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


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


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


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


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


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).


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,


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


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).

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