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Recognizing, Differentiating, and Referring Students with Absence Seizures

Permanent Link: http://ufdc.ufl.edu/UFE0024193/00001

Material Information

Title: Recognizing, Differentiating, and Referring Students with Absence Seizures What Factors Affect Preservice Teachers' Decision Making?
Physical Description: 1 online resource (181 p.)
Language: english
Creator: Nasewicz, Nicole
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: absence, adhd, epilepsy, inattention, preservice, psychology, school, seizures, teachers
Educational Psychology -- Dissertations, Academic -- UF
Genre: School Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) and epilepsy are common pediatric disorders that often occur co-morbidly. Both disorders predispose children to a wide range of school-related problems, some of which are the same and others vastly different. Fortunately, with early diagnosis and comprehensive disease management, the long-term sequelae of these disorders can be largely redirected. Diagnosing and differentiating between the disorders, however, can be remarkably complex. Diagnostic difficulties are particularly characteristic to the differentiation of absence seizures and ADHD - Primarily Inattentive Subtype (ADHD-PI), given that they present with subtle, overlapping symptomology. Teachers are among the most influential adults in the identification and management of ADHD and epilepsy in children. Unfortunately, teachers regularly fail to participate effectively in the diagnostic and evaluation process. Using a factorial survey design, 100 preservice teachers participated in this study to investigate (1) whether preservice teachers recognized absence seizures, (2) what characteristics predicted recognition ratings, (3) whether preservice teachers differentiated absence seizures from ADHD, (4) what characteristics predicted differentiation ratings, (5) whether preservice teachers anticipated initiating referrals for hypothetical children presenting with absence seizures, (6) what characteristics predicted referral ratings, and (7) whether preservice teachers anticipated making different referral decisions for hypothetical children presenting with absence seizures and hypothetical children presenting with ADHD? Overall, preservice teachers recognized absence seizures. Knowledge of ADHD, a respondent-level characteristic, and having received a previous diagnosis of ADHD-PI, a child-level characteristic, had negative effects on recognition ratings. Two child-level characteristics, having no recollection for what happened during the elapsed time and fluttering eyelids, had positive effects on recognition ratings. Preservice teachers differentiated reliably between unambiguous cases of absence seizures and ADHD. However, their proficiency declined when the disorders occurred co-morbidly. Only one respondent-level characteristic, referral efficacy, had a significant effect on differentiation ratings. Overall, preservice teachers anticipated initiating referrals for students presenting with absence seizures. Variance in referral ratings depended exclusively on respondent-level characteristics. Specifically, beliefs about the teacher?s role and mean recognition rating had positive effects on referral ratings. In general, preservice teachers anticipated being more likely to initiate referrals for students presenting with absence seizures than students presenting with ADHD.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Nicole Nasewicz.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Smith-Bonahue, Tina M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024193:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024193/00001

Material Information

Title: Recognizing, Differentiating, and Referring Students with Absence Seizures What Factors Affect Preservice Teachers' Decision Making?
Physical Description: 1 online resource (181 p.)
Language: english
Creator: Nasewicz, Nicole
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: absence, adhd, epilepsy, inattention, preservice, psychology, school, seizures, teachers
Educational Psychology -- Dissertations, Academic -- UF
Genre: School Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) and epilepsy are common pediatric disorders that often occur co-morbidly. Both disorders predispose children to a wide range of school-related problems, some of which are the same and others vastly different. Fortunately, with early diagnosis and comprehensive disease management, the long-term sequelae of these disorders can be largely redirected. Diagnosing and differentiating between the disorders, however, can be remarkably complex. Diagnostic difficulties are particularly characteristic to the differentiation of absence seizures and ADHD - Primarily Inattentive Subtype (ADHD-PI), given that they present with subtle, overlapping symptomology. Teachers are among the most influential adults in the identification and management of ADHD and epilepsy in children. Unfortunately, teachers regularly fail to participate effectively in the diagnostic and evaluation process. Using a factorial survey design, 100 preservice teachers participated in this study to investigate (1) whether preservice teachers recognized absence seizures, (2) what characteristics predicted recognition ratings, (3) whether preservice teachers differentiated absence seizures from ADHD, (4) what characteristics predicted differentiation ratings, (5) whether preservice teachers anticipated initiating referrals for hypothetical children presenting with absence seizures, (6) what characteristics predicted referral ratings, and (7) whether preservice teachers anticipated making different referral decisions for hypothetical children presenting with absence seizures and hypothetical children presenting with ADHD? Overall, preservice teachers recognized absence seizures. Knowledge of ADHD, a respondent-level characteristic, and having received a previous diagnosis of ADHD-PI, a child-level characteristic, had negative effects on recognition ratings. Two child-level characteristics, having no recollection for what happened during the elapsed time and fluttering eyelids, had positive effects on recognition ratings. Preservice teachers differentiated reliably between unambiguous cases of absence seizures and ADHD. However, their proficiency declined when the disorders occurred co-morbidly. Only one respondent-level characteristic, referral efficacy, had a significant effect on differentiation ratings. Overall, preservice teachers anticipated initiating referrals for students presenting with absence seizures. Variance in referral ratings depended exclusively on respondent-level characteristics. Specifically, beliefs about the teacher?s role and mean recognition rating had positive effects on referral ratings. In general, preservice teachers anticipated being more likely to initiate referrals for students presenting with absence seizures than students presenting with ADHD.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Nicole Nasewicz.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Smith-Bonahue, Tina M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024193:00001


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1 RECOGNIZING, DIFFERENTIATING, AND REFERRING STUDENTS WITH ABSENCE SEIZURES: WHAT FACTORS AFFECT PRES ERVICE TEACHERS DECISION MAKING? By NICOLE NASEWICZ A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Nicole Nasewicz

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3 To my patient husband, loving family, and the graduate faculty who provided me with endless support and counselI could not have achieved this milestone without you.

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4 ACKNOWLEDGMENTS I thank the m embers of my supervisory co mmittee for their ongoing support and counsel, with particular gratitude for my committee chair who encouraged me to investigate a topic I feel passionately about. I thank the Assistant Director/Elementary Coordinator of the Unified Elementary Proteach Program (UEP) at the Universi ty of Florida for helping to coordinate my research efforts, the preservice teachers who graciously participated in my research study, and the UEP course instructors who surrendered valu able class time so that I could pursue my scholarly interests. I th ank my loving family for providing me with endless encouragement, and for helping me maintain a positiv e perspective throughout the entirety of this process. Finally, I thank my husband for sacrificing countless night s and weekends, being a reassuring presence, and demonstrating a genuine interest in my st udy, which provided me with the validation and motivation I needed to proceed.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4LIST OF TABLES ...........................................................................................................................8ABSTRACT ...................................................................................................................... .............10 CHAP TER 1 REVIEW OF THE LITERATURE ........................................................................................12Attention-Deficit/Hyperactivity Disorder ...............................................................................12Clinical Definition of ADHD ..........................................................................................13Attention-Deficit/Hyperactivity Disord er-Primarily Inattentive Subtype .......................14Diagnosis .........................................................................................................................15Educational Problems ...................................................................................................... 17Health Outcomes ............................................................................................................. 17Treatment ..................................................................................................................... ....18Clinical Utility .................................................................................................................18Over-Diagnosis and Differential Diagnosis ....................................................................19Summary ....................................................................................................................... ...20Epilepsy ..................................................................................................................................21Absence Seizures .............................................................................................................22Diagnosis .........................................................................................................................23Educational Problems ...................................................................................................... 24Health Outcomes ............................................................................................................. 25Treatment ..................................................................................................................... ....26Summary ....................................................................................................................... ...27Overlapping and Distinguishing Symptoms ........................................................................... 27Overlapping Symptoms ...................................................................................................27Distinguishing Symptoms ............................................................................................... 30Summary ....................................................................................................................... ...33ADHD, Epilepsy, and School .................................................................................................33School-Based Assessment ............................................................................................... 36The School Psychologist .................................................................................................36The Integration of Medical and Educational Information ............................................... 38Pharmacotherapy ...................................................................................................... 38School-Based interventions ......................................................................................39Summary ....................................................................................................................... ...44The Instrumentality of Teachers .............................................................................................44Direct Influence .............................................................................................................. .45Indirect Influence ............................................................................................................ .46Knowledge and Beliefs ....................................................................................................49Teacher Efficacy ..............................................................................................................51

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6 Preservice Teacher Prep aration Prog rams ....................................................................... 54Summary ....................................................................................................................... ...56Assessing Professional Judgment ...........................................................................................57The Factorial Survey .......................................................................................................58Independent variables ...............................................................................................59Dependent variables .................................................................................................60Subgroup Variation .........................................................................................................61Level of Analysis .............................................................................................................62Criticisms ................................................................................................................. 63Rebuttal .................................................................................................................... 64Summary ....................................................................................................................... ...64Conclusion .................................................................................................................... ..........65Purpose of the Study .......................................................................................................... .....662 METHODS AND PROCEDURES ........................................................................................ 71Participants and Settings ..................................................................................................... ....71Measures ...................................................................................................................... ...........76Vignette Instrument ......................................................................................................... 76Independent variables ...............................................................................................77Dependent variables .................................................................................................78Proteach Demographic Information Survey (PDIS) ........................................................78Instrument Development ................................................................................................. 79Knowledge of Attention Deficit Disorders ...................................................................... 82Knowledge and Attitudes Toward Ep ilepsy and Persons with Epilepsy ........................ 83Procedure ..................................................................................................................... ...........84Child Vignettes ................................................................................................................84Demographic Information ............................................................................................... 88Knowledge and Beliefs About ADHD ............................................................................ 88Knowledge and Beliefs About Epilepsy .......................................................................... 903 RESULTS ....................................................................................................................... ........99Question 1 ...............................................................................................................................99Question 2 .............................................................................................................................100Question 3 .............................................................................................................................103Question 4 .............................................................................................................................105Question 5 .............................................................................................................................107Question 6 .............................................................................................................................108Question 7 .............................................................................................................................1104 DISCUSSION .................................................................................................................... ...117Introduction .................................................................................................................. .........117Question 1 ......................................................................................................................119Question 2 ......................................................................................................................123Respondent characteristics ..................................................................................... 123

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7 Child characteristics ...............................................................................................127Question 3 ......................................................................................................................128Question 4 ......................................................................................................................130Respondent characteristics ..................................................................................... 130Child characteristics ...............................................................................................132Question 5 ......................................................................................................................133Question 6 ......................................................................................................................134Question 7 ......................................................................................................................135Practical Implications ........................................................................................................ ...136Limitations ................................................................................................................... .........141Implications for Future Research .......................................................................................... 143APPENDIX A INSTRUCTOR INVI TATION LETTER .............................................................................148B INFORMED CONSENT ......................................................................................................149C SAMPLE VIGNETTE INSTRUMENT ...............................................................................151Research Vignettes ...............................................................................................................151Jennifer ...................................................................................................................... ...........152Katie ......................................................................................................................... .............153Anne .......................................................................................................................... ............154Julie ......................................................................................................................... ..............155Kelly ......................................................................................................................... ............156Tracy ......................................................................................................................... ............157D PROTEACH DEMOGRAPHIC INFORMATION SURVEY ............................................. 158E UNIFIED ELEMENTARY PROTEACH PROGRAM CORE REQUIREMENTS ............160F INSTRUCTION ON ADHD AND ABSE NCE SEIZURES ................................................161G COGNITIVE INTERVIEWS INFORMED CONSENT ......................................................162H PILOT STUDY CONSENT FORM ..................................................................................... 164I KADDS INSTRUMENT ......................................................................................................166J ATPE INSTRUMENT ..........................................................................................................169LIST OF REFERENCES .............................................................................................................171BIOGRAPHICAL SKETCH .......................................................................................................181

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8 LIST OF TABLES Table page 1-1 Criteria for Attention-Defi cit/Hyperactivity Disorder as outlined in the Diagnostic and Statistical Manual of Mental Disord ers Fourth Edition Text Revision ................. 681-2 Seizure classification .................................................................................................... .....691-3 Overlapping symptoms of AD HD-PI and absence seizures .............................................. 691-4 Distinguishing symptoms of ADHD-PI and absence seizures ..........................................701-5 Subgroup variation assumptions* ......................................................................................702-1 Preservice Teacher-Related Demographic Information as Reported on the Proteach Demographic Information Survey (PDIS) ......................................................................... 922-2 Preservice teachers knowledge, attitudes, and experiential information as reported on the Proteach Demographic Information Survey (PDIS) ...............................................932-3 Correlation matrix for selected preservice teacher characteristics as reported on the Proteach Demographic Information Survey (PDIS) ..........................................................942-4 Independent variables and leve ls assigned within the vignettes ........................................ 952-5 Mann-Whitney test statistics to assess for nonresponse error on the open-ended item across the vignettes .......................................................................................................... ..962-6 Preservice teachers explanations for th e hypothetical childrens presenting episodes of inattention ......................................................................................................................972-7 Correlations between preservice teac hers objective and subjective knowledge .............. 983-1 Summary of hierarchical linear modeling analysis for variables predicting preservice teachers ability to recognize absence seizures ................................................................ 1123-2 Crosstabulation results for preservice t eachers seizure disorder ratings across the ADHD and absence seizure vignettes. .............................................................................1133-3 Crosstabulation results for preservice teacher explanations for the hypothetical childrens presenting episodes of inattention ...................................................................1133-4 Summary of hierarchical linear modeling an alysis for variables predicting preservice teachers ability to differentiate absence seizures from ADHD ...................................... 1143-5 Summary of hierarchical linear modeling an alysis for variables predicting preservice teachers referral decision ................................................................................................ 115

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9 3-6 Crosstabulation results for preservice t each ers referral decisions on the vignettes ....... 116E-1 Unified Elementary Program (UEP) co re curriculum and field experiences .................. 160F-1 Instruction on ADHD and seizure disorder s provided in Unified Elementary Program 161

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10 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy RECOGNIZING, DIFFERENTIATING, AND REFERRING STUDENTS WITH ABSENCE SEIZURES: WHAT FACTORS AFFECT PRES ERVICE TEACHERS DECISION MAKING? By Nicole Nasewicz May 2009 Chair: Tina Smith-Bonahue Major: School Psychology Attention-Deficit/Hyperactivity Disorder (ADHD) and epilepsy are common pediatric disorders that often occur co-morbidly. Both di sorders predispose childre n to a wide range of school-related problems, some of which are the same and others vastly different. Fortunately, with early diagnosis and comprehensive diseas e management, the long-term sequelae of these disorders can be largely redirected. Diagnosing and differen tiating between the disorders, however, can be remarkably complex. Diagnostic diffi culties are particularly characteristic to the differentiation of absence seizures and ADHD Primarily Inattentive Subtype (ADHD-PI), given that they present with sub tle, overlapping symptomology. Teachers are among the most influential adults in the identification and management of ADHD and epilepsy in children. Unfortunately, teach ers regularly fail to participate effectively in the diagnostic and evaluation process. Using a factorial survey design, 100 preservice teachers participated in this study to investigate (1 ) whether preservice teachers recognized absence seizures, (2) what characteristics predicted reco gnition ratings, (3) whether preservice teachers differentiated absence seizures from ADHD, (4) what characteristics predicted differentiation ratings, (5) whether preservice te achers anticipated initiating referrals for hypothetical children presenting with absence seizures, (6) what char acteristics predicted referral ratings, and (7)

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11 whether preservice teachers anticipated maki ng different referral decisions for hypothetical children presenting with absence seizures and hypothetical children pr esenting with ADHD? Overall, preservice teachers recognized absence seizures. Knowledge of ADHD, a respondent-level characteristic, and having received a previous diagnosis of ADHD-PI, a childlevel characteristic, had negativ e effects on recognition ratings. Two child-level characteristics, having no recollection for what happened during the elapsed time and fluttering eyelids, had positive effects on recognition ratings. Preservice teachers differentiated reliably between unambiguous cases of absence seizures and ADHD. However, their proficiency declined when the disorders occurred co-morbidly. Only one re spondent-level characteris tic, referral efficacy, had a significant effect on differentiation ratin gs. Overall, preservice teachers anticipated initiating referrals for students presenting with absence seizures. Variance in referral ratings depended exclusively on respondent -level characteristics. Spec ifically, beliefs about the teachers role and mean recognition rating had po sitive effects on referral ratings. In general, preservice teachers anticipa ted being more likely to initiate referrals for students presenting with absence seizures than studen ts presenting with ADHD.

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12 CHAPTER 1 REVIEW OF THE LITERATURE Attention-Deficit/Hyperactivity Disorder Attention-Deficit/Hyperactivity Disorder (ADHD) is the m ost common neurobehavioral disorder of childhood (American Academy of Pediatrics, 2000). ADHD is characterized by a persistent pattern of inatte ntion, hyperactivity-impulsivity, or both (American Psychiatric Association [APA], 2000). Some degree of en ergy, exuberance, and impetuousness is normal, and even expected of school-aged children. However, in excess, these behaviors may be maladaptive. For example, children with ADHD often experience significant functional problems, such as school difficulties, academic underachievement, troublesome interpersonal relationships (e.g., with family and friend), and low self-esteem (A merican Academy of Pediatrics, 2000). The core symptoms of ADHD inattention and hyperac tivity-impulsivityare thought to arise in early chil dhood and persist across the devel opmental span (Mash & Barkley, 2003). Therefore, while a diagnos is of ADHD can be made at any age, diagnostic criteria includes that some of the beha viors are present before age se ven years (APA, 2000). Repeatedly, research and clinical practice de monstrates that with early rec ognition, accurate assessment, and comprehensive disease management, many of the undesirable educational and psychosocial outcomes associated with ADHD can be redirect ed (American Academy of Pediatrics, 2000). To be diagnosed with ADHD, a childs ina ttentive and hyperactive-impulsive behaviors must be of greater intensity, or occur with greater frequency, th an can be expected given the childs developmental level (APA 2000). The symptoms must cause clinical impairment in at least two settings (e.g., social, academic, or occ upational functioning) (Ball, Wooten, & Crowell, 1999). However, the degree of dysf unction that the behaviors cause can vary significantly across settings, depending on the nature of the envir onment. ADHD generally causes more impairment

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13 in environments that place gr eater demands on childrens atten tion and concentration abilities, such as school (APA, 2000). In fact, ADHD is so apparent and problematic in educational settings that researchers and prac titioners previously referred to it as a school-based disorder (Atkins & Pelham, 1991; Wright, 2002). The preval ence rate of ADHD is estimated to range from 3% in school-age children, occurring significantly more in males than in females (i.e., 3:1 ratio, respectively) (APA, 2000; Mash & Barkley, 2003). Notably, th e prevalence of ADHD has varied substantially across st udies and overtime. Many researcher s attribute this variability to changes in diagnostic criteria for the disord er (American Academy of Pediatrics, 2000). Clinical Definition of ADHD While syndro mal constructs similar to ADHD have existed for decades, the current definition differs markedly from its predece ssors (Mash & Barkley, 2003; Wright, 2002). For example, Hyperkinetic Behavior Syndrome, Hype r-excitability Syndrome, Attention Disorders, Minimal Brain Dysfunction, and Hyperkinetic R eaction of Childhood are all childhood disorders relating to inattention and hyperactivity (Wright, 2002). However, the diagnostic criteria for Attention Deficit Disord er (ADD), adopted by the Diagnostic and Statistical Manual of Mental Disorders Third Edition (DSM-III), was the first to recognize inattention as a unifying element (Wright, 2002). The DSM-III provided practitioners with lists of core symptoms and decision rules for differential diagnosis. On the basis of this criteria, practiti oners had to determine whether the individual was e xperiencing ADD with hyperactivity or without hyperactivity (Mash & Barkley, 2003). Researchers and pract itioners favored the new, exp licit criteria, believing that it improved both objectivity and relia bility of diagnosis (Wright, 2002). A prominent, and somewhat controversial, m odification to the definition of the disorder was the transition to a categorical di agnostic classification system in the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM-IV) (APA, 1994, 2000; Nigg,

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14 2006). Repeatedly, factor analy tic studies identified two dist inct dimensions underlying the cardinal symptoms of ADHD: (1 ) Inattention and (2 ) Hyperactivity-Impulsivity (APA, 2000; Mash & Barkley, 2003). In keeping with thes e findings, the DSM-IV augmented diagnostic criteria for ADHD to reflect two distinct dimensions, and provided practitioners with two separate lists of items one for inattention and one for hyperactivity-impulsivity. Both lists contained independent criteria with thresholds, resulting in three subtypes of the disorder: Attention-Deficit/Hyperactivity Disorder Primarily Hyperac tive-Impulsive Type (ADHD-PHI), Attention-Deficit/Hyperactivity Disorder Primarily Inattentive Type (ADHD-PI), and Attention-Deficit/Hyperactivity Disorder Combined Type (ADHD-C) (APA, 2000; Mash & Barkley, 2003). Attention-Deficit/Hyperactivity Di sorder-Primarily Inattentive Subtype Attention-Deficit/Hyperactivity Disorder Primarily Inattentive Subtype (ADHD-PI), often erroneously referred to as ADD, is esti m ated to occur in 3% of school-age children, suggesting that it is as prevalent as ADHDC (Mash & Barkley, 2003; Nigg, 2006). The disparity across gender is less pronounced for this subt ype (APA, 2000); some ep idemiological studies observed comparable rates across males and fe males (e.g., 1.4% vs. 1.3%, respectively) (Mash & Barkley, 2003). Cardinal symptoms of ADHD-PI include failure to gi ve close attention to details and difficulty sustaining attenti on (APA, 2000). Children with the disorder tend to move from one uncompleted activity to the next, whether it be chores, schoolwork, or play activities (APA, 2000). Their schoolwork tends to be messy, and is often riddled with care less errors. Typically, children with ADHD-PI avoid task s or activities that require sustained mental effort and demonstrate a marked aversion to homework (APA, 2000).

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15 Parents and teachers of children with ADHD-PI often describe them as daydreamers. More specifically, they report that children with ADHD-PI appear as though their mind is elsewhere and attend only intermittently during conversa tions (APA, 2000). As a result, they may miss details in conversations, or fail to comprehend the rules of a game. In general, individuals with ADHD-PI are described as disorganized; they fre quently lose or damage materials necessary to complete a task (APA, 2000). Children with the disorder are easily dist racted by irrelevant stimuli in the environment, which can interfere substantially with their ability to complete assignments and tasks. Imagine, for example, a typical classroom overflo wing with noises, such as the ticking of a clock, the ta pping of a pencil, or the whisperi ng of students. For most children these noises are readily ignore d. For a child with ADHD-PI, th ese noises may be conspicuous and may seem inescapable. Diagnosis Practition ers of varying types (e.g., primar y care physicians, subspecialties, and nonphysician mental health provide rs) may diagnose a child with ADHD, and the diagnostic practices they utilize may vary considerably (American Academy of Pediatrics, 2000). Despite advances in science, researchers have yet to disc over a laboratory test can accurately and reliably identify ADHD (Williams et al., 2002). Currentl y, the DSM-IV stands as the universally accepted criteria for the identifica tion of ADHD and is used by practitioners in most clinical settings (Wright, 2002). The DSM-IV, based on the medical model of human behavior, conceptualizes disorders as bei ng syndromal and inherent to th e person (Wright, 2002). Benefits of this type of classification system are that it facilitates a uniform code of communication, promotes a consensual understanding of disorders, and improves reliability in measuring behaviorally derived construc ts, such as ADHD (Wright, 2002). However, many practitioners remain unconvinced of the usefulness of the DSM -IV definitional standard, especially those who

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16 routinely link diagnostic information to interv entions. These practitione rs prefer to rely on dimensional classification schemes, which conc eptualize behavior as occurring on a continuum (i.e., they are concerned with the degree, or severity, of the behavior) (Mash & Barkley, 2003). Dimensional classification schemes, which rely on multivariate statistical techniques, are thought to enhance diagnostic power (Mash & Barkle y, 2003). As a result, the diagnosis of ADHD routinely involves clinical observations, interviews, and behavioral rating scales (Williams et al., 2002). To receive a diagnosis of ADHD-PI, children must exhibit at least six symptoms consistent with the inattention threshold out lined in the DSM-IV for a minimum of six months (Table 1-1) (APA, 2000). Like ADHD-C, the behavior must cau se impairment in at least two settings. However, the level of dysfunction may vary with respect to the demands of the environment (APA, 2000). Additionally, the child must display fewer than six symptoms consistent with the Hyperactivity-Impulsivity threshold (i.e., the child would meet cr iteria for ADHD-C) (APA, 2000). To best understand a childs behavior, th e DSM-IV advises practitioners to gather information from multiple informants who observe and interact with the child across disparate settings (APA, 2000). In addition to pare nts, guidelines identify teachers as natural raters (Tripp, Schaughency, & Clarke, 2006). Their input is preferred particularly fo r their ability to have close and continuing contact with studen ts (i.e., children spe nd 40% of their developing life in school), to observe students under demanding learning cond itions, and to compare the students behavior to his or her peers (i.e., whom are of the sa me developmental level and placed under similar conditions) (Bishop & Slevin, 2004; Tripp et al., 2006; Wright, 2002) With parental consent, practitioners may elect to review school records, including comprehensive evaluations and

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17 conference reports, and may consult with key school-based personnel, such as the school psychologist (American Acad emy of Pediatrics, 2000). Educational Problems Unfortunately, the literature clearly docu m ents that ADHD places children at-risk for a wide range of educational problems (American Academy of Pediatrics, 2000). For example, numerous studies have demonstrated that child ren with ADHD score lower on intelligence tests than normal controls. Notably, however, this difference becomes non-significant when hyperactive-impulsive behavior is partialed out (Barkley, Karlsson, & Po llard, 1985; Hinshaw et al., 1987; Lynham, Moffitt, & Stouthamer-Lober, 1993; Mash & Barkley, 2003). Children with ADHD-PI tend to have the most difficulty on execu tive functioning tasks, pa rticularly those that require selective or focused attention, rapid re trieval of verbal information from memory, and visual-spatial processi ng (Barkley, DuPaul, & McMurray, 1990; Garcia-Sanchez, EstevezGonzalez, Suarez-Romero, & Junque, 1997). ADHD-PI also places children at-risk for academic underachievement and learning disability (M ash & Barkley, 2003). Hynd et al. (Hynd et al., 1991; Morgan, Hynd, Riccio, & Hall, 1996) reported that, within a sample of children with ADHD-PI, 60% met criteria for learning disabili ty, most commonly in math. Unsurprisingly, then, children with ADHD-PI are significantly more likely to be retained and to receive special education services than children in th e general population (Mash & Barkley, 2003). Health Outcomes Researchers have conducted fe w studies exploring the rela tionship between ADHD-PI and adverse health outcom es (Mash & Barkley, 2003). They have, however, conducted considerable research with respect to ADHD-C. Since childre n with ADHD-C meet criteria for the inattention threshold, it may be reasonable to generalize ma ny of the findings to individuals with ADHD-PI. Accident proneness, injury, and motor vehicle accidents are among the most notable adverse

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18 health outcomes associated with ADHD-C. Acco rding to parents, as compared to normal controls, children with ADHD-C are up to four ti mes more accident prone; and are significantly more likely to sustain injuries in various spor ts, fracture bones, and ingest poisonous substances (Mash & Barkley, 2003). They are also more likely to experience sleep dist urbancesa negative and unfortunately common side-effect of stim ulant medication (Becker, Fennell, & Carney, 2004; Mash & Barkley, 2003). Adolescents with ADH D-C are more likely to be involved in motor vehicle accidents, and they are significantly more likely to be found at fault. Moreover, as compared to same-age peers, they receive si gnificantly more speeding citations, and they are significantly more likely to ha ve their drivers licenses su spended (Mash & Barkley, 2003). Treatment The m ost common form of treatment for a ll ADHD subtypes is stimulant medication. Consistent with the prevalence of the disorder, the use of stimulant medication has risen steadily among pediatric populations. In their study, Safer and Zito (as cited in Nigg, 2006) estimated that between 2 and 2.5 million children in the United Stat es (U.S.) were taking stimulant medication for ADHD in 1999, which was equivalent to 3% of all U.S. children. Another survey-based study found that rates among insured pati ents are even higher, estimati ng that approximately 4.3% of U.S. children were taking stimulant me dication (Nigg, 2006). Psychotherapy, and more specifically, behavioral manageme nt, is another effective treatment option (Nigg, 2006; Swanson et al., 1998). Extant research suggests that ps ychotherapy and medication in combination are associated with the best outcome s (Nigg, 2006; Swanson et al., 1998). Clinical Utility Researchers have established the clin ical ut ility of ADHD-PI by de monstrating that the subtype can be differentiated from ADHD-C with respect to its presentation and long-term outcomes (Nigg, 2006). In general, ADHD-PI te nds to emerge later than ADHD-C (e.g., 8

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19 years vs. 58 years, respectively) (Applegate et al., 1997; Mash & Barkley, 2003). Additionally, as compared to children with ADHD-C, child ren with ADHD-PI displa y fewer oppositional or aggressive symptoms, are less lik ely to be diagnosed with co-m orbid externalizing disorders (e.g., ODD and CD), and are more shy and with drawn (Mash & Barkley, 2003). They are less likely to have speech and language problems as well (Cantwell & Baker, 1992; Mash & Barkley, 2003). While both groups of children are at-risk fo r special education placement, children with ADHD-PI are more likely to receive special educa tion services for learning disabilities, whereas children with ADHD-C are more likely to be pl aced in classes intended for behaviorally disturbed children (Mash & Barkley, 2003). Studie s suggest that children with ADHD-PI require more remedial assistance; research ers attribute this need to thei r deficits in focused attention, verbal retrieval skills, and visual -spatial processing (B arkley et al., 1990; Ga rcia-Sanchez et al., 1997; Mash & Barkley, 2003). Over-Diagnosis and Differential Diagnosis In general, ADHD-PI has good clinical utilit y. T he associated symptoms hang together statistically like a syndrome, the disorder re sponds positively to trea tment, and it can be differentiated from ADHD-C and ADHD-PHI (Nigg, 2006). However, despite being an empirically based construct, ADHD-PI may still be misdiagnosed or over-diagnosed. Researchers allege that the shift to a categoric al diagnostic system (i.e., in the DSM-IV) caused the prevalence of the disorder to rise drastica lly. More specifically, by dividing inattention and hyperactivity-impulsivity into distinct dimensions with individual threshol ds, more children meet diagnostic criteria than in the past (APA, 2000; Mash & Barkley, 2003). Practitioners relying on previous editions of the DSM would have diagnosed these children wi th Attention Deficit Hyperactivity Disorder Not Otherwise Specified (ADHD-NOS) (APA, 2000). Additionally, while inter-evaluator reliability for ADHD-C a broad diagnostic cat egory is fairly high,

PAGE 20

20 some researchers caution that reliability tends to decline upon diagnosing narrower subtypes of the disorder, such as ADHD-PI (Mash & Barkley, 2003). In light of these criticisms, some researcher s and practitioners char ge current diagnostic ADHD criteria with being unable to differentiate between qualitatively different forms of inattention (i.e., inattention orig inating from heterogeneous etio logies). Children who initially present with ADHD are regularly found to have a range of pediatric disord ers, including but not limited to: learning disab ilities, movement disorders, fragile X syndrome, genetic disorders, pervasive developmental/autistic disorders, or epilepsy (Pearl, Weiss, & Stein, 2001). To guard against misdiagnosis and over-diagnosis, the DS M-IV-TR requires practitioners to perform differential diagnosis, which functions to rule out other psychiatric, medical, or neurological disorders that may account for the childs presen ting behavior (Pearl et al., 2001). Unfortunately, differential diagnosis is an imperfect practice, especially when disorders share subtle, overlapping symptomology. Summary ADHD, a common neurobehavioral disorder, is com prised of three subtypes: (1) ADHDPHI, (2) ADHD-PI, and (3) ADHD-C (APA, 2000; Barkley et al., 1990; Mash & Barkley, 2003). Characterized by inattention, ADHD-PI can inte rfere substantially with a childs daily functioning, especially at sc hool (Mash & Barkley, 2003; Nigg, 2006). If diagnosed early and accurately, children with ADHD-PI typically respond positively to treatment, which may involve stimulant medication, psychotherapy, or both (Nigg, 2006; Swanson et al., 1998). However, researchers and practitioners ar e growing increasingly concerned that children with ADHD-PI are being misdiagnosed and, more specifically, over-diagnosed (Nigg, 2006) Critics of the current ADHD definitional standard caution that, due to the broa d and unspecific nature of DSMIV-TR diagnostic criteria, children with inattentio n stemming from heteroge neous etiologies are

PAGE 21

21 routinely diagnosed with ADH D-PI (APA, 2000; Mash & Barkley, 2003). To ensure that childrens inattention is not st emming from another source, pract itioners rely on differential diagnosis (Pearl et al., 2001). Un fortunately, however, differentia l diagnosis is an imperfect precaution and regularly fails to dete ct alternative explanations for childrens inattention (Pearl et al., 2001). Epilepsy Epilepsy, a chronic and often serious health condition, is characterized by recurrent seizures (Cull & Goldstein, 1997; Gastaut, 1973). A seizure is a sudden, involuntary, tim elimited alteration in behavior that is accompan ied by an abnormal electrical discharge in the brain. Seizures are caused by a va riety of factors, including bu t not limited to (1) diseases affecting the central nervous sy stem, (2) genetic syndromes, and (3) birth trauma. However, the cause of seizures is unknown in approximately two-thirds of cases (Cull & Goldstein, 1997). Thus, regarding its relationship w ith epilepsy, a seizure may be conceptualized as a nonspecific symptom of a disorder that must be further diagnosed (Lishman, 1987). Epilepsy is one of the most common neurological diseas es in the general population (Dan tas, Carirr, Carirr, & Filho, 2001). Depending on the populations st udied and the definitions us ed, the prevalence rate for epilepsy ranges from .4-1% (Center for Dis ease Control [CDC], 1994). While the disease transcends all demographic boundaries, epilepsy is especially prevalent during the school years, affecting approximately 0.5% of school-age children (Bishop & Slevin, 2004; Dantas et al., 2001; Kaleyias, Tzoufi, Kotsalis, Papavasiliou, & Diamantopoulos, 2005; Ojinnaka, 2002). When evaluating a child for epilepsy, neurologis ts classify the childs seizures as either generalized or partial, depending on the origin of the abnormal activ ity in the brain (Table 1-2) (Cull & Goldstein, 1997; Leppik, 2000). Genera lized seizures invol ve abnormal activity throughout the brain, whereas partia l seizures involve abnormal activ ity that is isolated to a

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22 discrete, or focused, part of the brain (Agnew, Nystul, & Conner, 1998; Leppik, 2000). Generalized seizures are more co mmon. The Tonic-clonic seizure, pr eviously referred to as the grand mal seizure, is the most notable type of generalized seizure. However, absence seizures, which are characterized by subtle behavior ch anges, are the most common type of childhood epilepsy (Agnew et al., 1998). Freque ntly, absence seizures are cons idered benign, since they are not believed to (1) be caused by injuries to the brain, (2) cause in jury to the brain, and (3) have a significant impact on psychological and social well-being (Wirrell, 2003). The finding that many individuals outgrow absence seizur es was used as further evidence that they are not a threat to life or long-term health. However, today, many researchers and practit ioners dispute these assumptions, pointing to evidence that absence se izures do have negative effects on well-being, and to the fact that a significant number of individuals never outgrow them (Wirrell, 2003). Absence Seizures Absence seizures, pr eviously referred to as petit mal epilepsy, are characterized by impaired consciousness that is unaccompanied by large convulsive movements. The most common type of childhood epilepsy, absence seizur es occur in approximately 2-10% of children with epilepsy (Agnew et al., 1998). Typically, ab sence seizures emerge between ages 5 and 15 years, with a higher prevalence among females (Agnew et al., 1998; Leppik, 2000). The typical course of absence seizures is that they become less frequent in adolescence and often remit entirely in adulthood (Agnew et al., 1998). Absence seizures are characteri stic for their brevity (Agnew et al., 1998; Leppik, 2000). They typically last for 5 to 10 seconds; however, deviations of up to 60 seconds are not uncommon. The term pyknolespy (pyknos refers to overcrowding) is associated with absence seizures as it descri bes their tendency to occur in rapid succession (Leppik, 2000). Children may experience several hundr ed-absence seizures per day with little to no normal mental activity between them (Ada ms & Victor, 1993; Agnew et al., 1998).

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23 Neurologists distinguish between typical and atypical absen ce seizures. Commonly, typical absence seizures are idiopathic or the etiology of the seizures is unknown. Fortunately, studies suggest that they remit entir ely in approximately 40% of patients, most commonly during adolescence (Leppik, 2000). Atypical absence seiz ures, in contrast, are more complex. During atypical absence seizures, children can retain some ability for purposive movement and speech, which complicates their presentation and makes them difficult to iden tify (Leppik, 2000). Like typical absence seizures, atypical absence seizures occur more in females and emerge prior to adolescence. Unlike typical absence seizures, atypi cal absence seizures tend to occur with greater frequency, to be more prolonged, and to co-occur with other seizure t ypes (Leppik, 2000). For example, absence seizures associated with Juve nile Absence Epilepsy can last for several hours (Pearl et al., 2001). Children with atypical absence seizures demonstrate significantly higher rates of mental retardation, and tend to have a higher incidence of global cognitive deficits. This seizure type tends to be expre ssed as a nonspecific symptom of brain injury during development (Leppik, 2000). Diagnosis Diagnosis of absence seizures depends heavily on behavioral descrip tions during clinical events (W illiams et al., 1996). Current clinical practice dictates that electroencephalogram (EEG) recordings only assist in the diagnosis of absence seizures and that abnormal epileptiform activity (i.e., on an EEG) only be treated if it is accompanied by clinical seizures (Schubert, 2005; Williams et al., 2002). This recommendation is based on the assumption that subclinical epileptiform activity does not affect attention or cognitive functioning (Schubert, 2005). The finding that many children with ADHD (i.e., 6-30%) demonstrate abnormal epileptiform activity bolsters the recommendation that EEG recordings be supplemented by behavioral descriptions (Tan & Appleton, 2005). Notably, many researcher s and practitioners challenge the assumption

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24 that subclinical epileptiform activity does not impa ir cognitive func tioning, insisting that it does impair attention to a degree (Schubert, 2005). Persons with absence seizures describe them as brief flashes of blackouts, like in a daze, or getting into a trance (Panayiotopoulos et al., 1992). They report a lack of aura prior to the onset of an absence seizure (i.e., a sensation that it is about to occur), as well as an absence of a postictal period following the seizures term ination (i.e., post seizur e confusion) (Leppik, 2000). For pediatric populations, dia gnosis relies almost exclusivel y on parental descriptions and reports (Williams et al., 1996). Parents of children with typical absence seizures describe the episodes as being discrete, in th at the onset and offset of the episode are obvious (Pearl et al., 2001). While absence seizures are considered non-convulsive, some minor movements may be present during the event. Parents commonly report body limpness a nd the arrest of activity (e.g., the child may suddenly drop whatever item he or she was holding). Williams et al. documented a very clear pattern of behaviors associated wi th absence seizures. Every parent in the study endorsed staring behavior, cessati on of speech, failure to respond, and the need for information to be repeated (Williams et al., 1996). Identi fying atypical absence seizures may be more difficult, given that the episodes tend to be more sporadic, more unpredicta ble, less discrete, last for protracted periods of time, and are associat ed with mental retard ation, all of which may complicate the presentation of the behavior (Pearl et al., 2001). Educational Problems Cognitive a bility varies significantly across individuals with epilepsy, and given the transitory nature of seizures (i.e., they are time-limited events and can be outgrown), can vary markedly over time (Svoboda, 2004). Much of the tim e, epilepsy is associat ed with deficits in narrower cognitive domains, such as visual-spatial processing, attention, and memory. However, again, given the transitory nature of seizures, deficits may only be temporary (Binnie, Channon,

PAGE 25

25 & Marston, 1990). The results of studies suggest that age of onset, seizure frequency, and seizure type all affect cognitive functioning. More specifically, earlier onset, increased frequency of seizures, longer duration of seizures, and partial seizures are associated with a worse prognosis (Cull & Goldstein, 1997). Regardi ng absence seizures, atypical absence seizures are associated with impaired cognitive functioning, and, more specifically, functioning in the mentally retarded range. Typical absence seizures, in contrast, have only been linked to transitory deficits due to impaired consciousness (Cull & Goldstein, 1997). Prolonged periods of impaired consciousness due to consecutive absence seizures can lead to considerable dysfunction at school. For exampl e, if they occur during instruction, or during exposure to novel material, a child may have gaps in his or her learning and fail to master important skills (e.g., during math instruction) (L eppik, 2000). Unsurprisingly, academic deficits are common among children who experience absence seizures. As a group, children with epilepsy are at-risk for academic underachievement and learning disability (LD). Fastenau, Shen, Dunn, and Austin (2008) found that approximately half (48.2%) of children with epilepsy met discrepancy criteria for learni ng disability; discrepancies were most common in writing (38%), followed by math (20%) and reading (13%) (Fastena u et al., 2008). Additionally, as compared to children in the general population, children with epilepsy ar e significantly more likely to be retained and to receive special education services (Svoboda, 2004). Earlie r onset and increased frequency of seizures are associated with mo re cognitive difficulties and greater academic dysfunction (Cull & Goldstein, 1997). Health Outcomes Unfortunately, the literature suggests that ab sence seizures place children at-risk for experiencing a num ber of adverse health outcomes. Specifically, ab sence seizures are associated with accident proneness a nd injury. In one study 27% of children with absence seizures reported

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26 having sustained an injury as a result of loosing consciousness during an absence seizure (Wirrel, 2003; Camfield, Camfield, Dooley, & Gordon, 1996). School-age children are at increased risk for being involved in bicycling accidents, being struck by a car, and for acquiring mild head injury. Adolescents with absence seizures are involved in motor vehicle accidents at elevated rates, which, unfortunately, may lead to deat h (Salinsky, Wegener, & Sinnema, 1992). Much of the time, children with absence seizures are invo lved in accidents and sustain injuries after beginning treatment with Anti-Epil eptic Drugs (AED). In respons e, neurologists often advise children and their caregivers to take special precau tions both at home and at school (Wirrel et al., 1996). For example, children may be mandated to wear a helmet during activities that pose a special risk, such as bicyc ling (Wirril et al., 1996). Treatment Treatm ent for epilepsy may include medicati on, special diet, and less commonly surgery. The most common form of treatment for epileps y is Anti-Epileptic Drugs (AEDs). Valproate (Depakene) and Ethosuximide are the most comm only prescribed drugs for absence seizures (Leppik, 2000). Given that absence seizures ar e often considered benign, Ethosuximide is usually recommended first; Valproat e is reserved for when Ethosuxi mide is ineffective or when the child also experiences Tonic-clonic seiz ures (Leppik, 2000). Neurologists formerly considered Lamotragine to be a second line drug; however, its use has increased significantly over time (Posner, Mohamed, & Marson, 2005). Treatment with AEDs has been linked with improvements in neurocognitive functioning, esp ecially on visual memory and fine-motor fluency tasks (Siren et al., 2007). Surprisingly, however, seizure va riables and cognitive functioning often play a minimal role in acad emic underachievement among children with epilepsy (Fastenau et al., 2008). Family enviro nment (e.g., emotional climate, stimulation, and parental involvement), in contrast, has been found to have a positive, significant impact on

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27 achievement, especially in writing (Fastenau et al., 2008). Therefore, treatment often extends beyond medical intervention, and may involve the br oader familial system and cross-disciplinary collaboration. Summary Epilepsy, characterized by abnorm a l electrical activity in the brain, is an umbrella term covering many different seizure disorders. Abse nce seizures are the most common type of childhood epilepsy, and are characterized by impa ired consciousness that is unaccompanied by convulsive movements (Leppik, 2000) Subtle and brief, absence se izures are often considered benign (Wirrel, 2003). However, increasingly, res earch documents that impaired consciousness due to absence seizures is associated with significant dysfunction, particularly at school (Svoboda, 2004). Optimistically, most children with absence seizures respond positively to treatment, which usually involves AEDs (Le ppik, 2000). Proper treatment, however, depends on accurate diagnosis. Currently, diagnosis depends heavily on behavioral descriptors during clinical events (Williams et al., 1996). Parents ar e almost exclusively responsible for describing childrens behavior and for relaying important information to practitioners (Williams et al., 1996). Unfortunately, recognizing abse nce seizures can be complex, es pecially given the subtlety of their associated symptoms (Williams et al., 1996; Williams et al., 2002). Overlapping and Distinguishing Symptoms Overlapping Symptoms Overlapping behavioral sym ptomology can complicate the differential diagnosis of seizure disorders and ADHD. Absence seizures and ADHD-PI are particularly difficult to differentiate. Both disorders are characterized by subtle be haviors (e.g., staring), share similar cognitive profiles, and are associated with many of the same undesirable educational outcomes. For example, in general, children with both disord ers have general cognitive ability within normal

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28 limits. However, they commonly experience defici ts within narrower cognitive domains, such as attention, memory, and executive functioning (Barkley et al., 1990; Binnie et al., 1990; GarciaSanchez et al., 1997; Williams et al., 1996). Moreover, both epilepsy and ADHD predispose children to academic underachievement, learni ng disability, grade-re tention, and special education placement (Table 1-3) (Hynd et al., 19 91; Mash & Barkley, 2003; Morgan et al., 1996, Svoboda, 2004). Regarding their conduct and behavior, childr en with ADHD-PI and absence seizures are described similarly. For example, children with absence seizures are often described as being absentminded or day-dreamy, and often lose items that are necessary to co mplete a task (Adams & Victor, 1993; Agnew et al., 1998). They are also describe d as having difficulty listening, responding when spoken to, sustaining attention on tasks, remembering daily activities, following through on instructions, and organizing tasks (Adams & Victor, 1993; Agnew et al., 1998). These descriptors mirror many of those us ed to describe children with ADHD-PI (e.g., day-dreamy, hypoactive, passive, apathetic, lethar gic, confused, and sluggish) (Mash & Barkley, 2003). However, what some researchers and practi tioners find most troub ling is that many of these descriptors parallel diagnos tic criteria for ADHD-PI as ou tlined in the DSM-IV (Agnew et al., 1998). As a result, children with absence seiz ures may meet diagnostic criteria for ADHD-PI, despite exhibiting inattenti on that is originating fr om a disparate etiology. A last factor complicating the differentiation of ADHD-PI and abse nce seizures is that they often occur co-morbidly (Schubert, 2005). For ex ample, in a study involving children with epilepsy, Hesdorffer et al. (2004) found that 28-39% had problems with hyperactivityimpulsivity, 42% had problems with inatten tion, and 14% met diagnostic criteria for ADHD. Results across studies converge to suggest that, as compared to children with focal epilepsies,

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29 children with generalized epilepsies, such as absence seizures, are more likely to exhibit problems with inattention (Schubert, 2005). Absence seizures, in particul ar, predispose children to problems with inattention, even when seizur es are controlled with AEDs (Schubert, 2005). Researchers have proposed several hypothese s to clarify the relationship between ADHD and epilepsy. One hypothesis is that epilepsy, or its treatment, causes ADHD (Hesdorffer et al., 2004). Another leading hypothesis is that both disorders arise from central nervous system damage, or from a tertiary condition (Schubert, 2005). For example, in a study conducted by Becker, Fennel, and Carney (2004), parents desc ribed their children with epilepsy as having significant problems with inattention and hyperac tivity. However, neither the severity of the epilepsy nor the frequency of the seizures predic ted problems with inatte ntion and hyperactivity. Instead, sleep disturbances pr edicted seizure activ ity, inattention, and hyperactivity. Findings suggest that a significant nu mber of individuals presenting with ADHD, epilepsy, or both disorders may be experiencing sleep distur bances as well (Becker et al., 2004). More importantly, the findings may suggest that improvi ng quality of sleep may indirectly lead to a reduction or elimination of seiz ure activity, problems with ina ttention and hyperactivity, or both (Becker et al., 2004). Finally, considered a third a nd increasingly viable hypothesis, researchers propose that epilepsy is often preceded by the development of ADHD (H esdorffer et al., 2004). ADHD, then, may be considered a risk fact or for developing epilepsy. That ADHD precedes epilepsy is particularly true of the ADHD-PI subt ype (Hesdorffer et al., 2004). While researchers have yet to substantiate the exact mechan isms underlying the relationship between ADHD and epilepsy, clearly, when a child presents with ADHD-PI, the possibility that they are experiencing co-morbid absence seizures should be explored (Schubert, 2005).

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30 Distinguishing Symptoms Persons familiar with ADHD-PI and absen ce seizures can differentiate between the disorders by attending to the natu re o f their associated symptoms (Table 1-4). Specifically, while both disorders are characterized by episodes of inattenti on, they differ with re spect to their onset, pervasiveness, and stability. For example, while both disorders tend to emerge during the school years, ADHD-PI is often predicated by increased demands on attention and concentration. As a result, children are not generally diagnosed with ADHD-PI prior to upper-elementary school (e.g., grades three through five). Girls with inattention prob lems tend to go more unnoticed, given that they are less likely to exhibit overt or disruptive be havior in the classroom (Wright, 2002). Once ADHD-PI emerges, it tends to be stable (i.e., the behavior generalizes to most situations that require sustained attention and persists across th e persons lifespan). Inattention stemming from ADHD-PI tends to arise graduall y, occurring after the person grows uninterested in a task or activity. The episodes usually last until something interesting happens, or until an outside agent (e.g., a teacher or caregiver) verbally or physica lly interrupts the episode. Absence seizures, in contrast, begin abruptly irrespective of environmental demands. They may occur in all situations, ev en during enjoyable activities, such as play. Hyperventilation provokes absence seizures, and they may occur during physical activity as a result (e.g., during physical education or during re cess) (Pearl et al., 2001). Inatte ntion stemming from absence seizures is discrete; the onset and offset of th e episodes are clearly demarcated. In general, the episodes last 10-15 seconds during which the chil d may be unresponsive to verbal or physical redirection. Absence seizures may occur frequen tly (occurring hundred of times a day), or they may be sporadic. In either case, the inattention is unpredictable, which differentiates it from the predictable episodes of inatten tion characteristic of ADHD-PI. Differentiating atypical absence seizures from ADHD-PI may prove to be more difficult, given that ch ildren with atypical

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31 absence seizures can retain some purposive move ment, and the onset and offset of the episodes tend to be less disc rete (Leppik, 2000). Concerns regarding accuracy of seizure dia gnosis prompted researchers to investigate whether specific behaviors can be used to differentiate reliably between ADHD-PI and absence seizures. Williams et al. (1996) launched an initial research effort to identify behaviors that are unique to seizure activity. First, they provided parents of children with epilepsy and parents of children without epilepsy with a set of 40 behavioral descript ors (i.e., the Seizure Behavior Checklist). Next, they analyzed pa rents responses and identified descriptors that were endorsed differently across the groups. Overall, parents of children with epileps y endorsed 12 descriptors more often: does not remember what happened, moves mouth funny, drools, jerking/twitching, becomes stiff, changes in breathing, stares off, bites or chews tongue, eyes look glassy, will not respond, murmurs or slurs words, and eyes or head turn to one side (Williams et al., 1996). Parents of children without seizures endorsed one be havior most often: fidgets in seat. Descriptors particularly characte ristic to generalized seizures were those that were highly physiologic and visible (e.g., eyes roll up, cries out, drooling, tw itching/jerking, and changes in breathing) (Williams et al., 1996). The hallmark distinction between absence seizures and nonseizure events was lack of responsiveness. That is, parents of children with absence seizures perceived them as not only experiencing an alte red state of consciousne ss, but, also, as being unable to make a response (Williams et al., 1996). While replication of this study should be conducted to determine the robustness of the results preliminary findings s uggest that behavioral descriptors can be used to screen children for seizure events. Williams et al. (2002a) conducted a follo w-up study to assess whether the 13 aforementioned behavioral descri ptors could distinguish between patients with new-onset seizure

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32 disorders and ADHD. The groups differed signifi cantly on all items, except one: mumbles/slurs words. Additionally, with the exception of fidgets in seat, parents of children with seizures endorsed all descriptors more of ten than parents of children w ith ADHD. Upon further analysis, the investigators determined that four items were able to distinguish between the diagnoses with a high degree of specificity (i .e., the correct overall classifica tion rate was 89%). The most important behavioral indicators included : eyes look glassy, changes in breathing, jerking/twitching, and fidgeting. Ch ildren whose parents endorsed th at they had glassy eyes but did not fidget were correctly classified as ha ving epilepsy 96% of the time. Conversely, children whose parents endorsed that their eyes were not glassy, that they did not experience changes in breathing, but that they did fidget were correc tly classified as having ADHD 96% of the time. The results of this study suggest that specific descriptors can be used to differentiate between seizure events and ADHD. Williams et al. (2002b) conducted a third study to determine whether a parent-completed structured instrument could facilitate the diagno stic process for seizures and, ultimately, improve diagnostic accuracy. The Attention Deficit Disorders Evaluation Scale-Home Version (ADDESHV), a scale that is used regularly in clinical and educational se ttings, was used to measure the intensity of the childrens inattention. Parents completed the instrument prior to their child receiving a diagnosis of ADHDPI or absence seizures. Star ing behavior was common to children with ADHD-PI and absence seizures (i.e ., it was endorsed by 80% and 95% of parents, respectively), suggesting that the behavior is not useful for di fferential diagnosis. While both groups of children demonstrated elevated levels of inattention, the level of intensity was significantly higher for children with ADHD-PI. Specifically, children with absence seizures mean standard scores on the inattentive s cale of the ADDES-HV fell in the normal range,

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33 whereas standard scores for children with ADHD-PI fell in the moderate to severe range. These results suggest that the inatte ntive scale on the ADDESHV may be assistive in distinguishing between the diagnoses. Finally, two specific beha viors on the ADDES-HV reli ably differentiated between the diagnoses: failing to complete homework assignment s and being unable to stay on task. Whereas these behaviors were characteris tic to children with ADHD, they were not characteristics to children with absence seizures. Summary Clearly, ADHD-PI and absence seizures share m any overlapping symptoms. Both disorders are characterized by relatively subtle behaviors (e.g., staring), share similar cognitive profiles (i.e., average cognitive abilities with de ficits in narrower domains), and, unfortunately, predispose children to many of the same undesira ble educational outcomes (e.g., grade retention) (Barkley et al., 1990; Bi nnie et al., 1990; Garcia-Sanchez et al., 1997; Hynd et al., 1991; Mash & Barkley, 2003; Morgan et al., 1996; Svoboda, 2004). Pa rents and teachers describe children with both disorders similarly (e.g., abse nt-minded and day-dreamy), and despite that their inattention stems from disparate etiologies, children with both disorders may meet criteria for ADHD-PI (i.e., as outlined in the DSM-IV) (Agnew et al., 1998). That absence seizures and ADHD-PI often occur co-morbidly further complicates ac curate differentiation between the disorders (Schubert, 2005). Researchers have begun to identif y specific behavioral de scriptors that can be used to differentiate reliably between the diso rders (Williams et al., 2002). Being familiar with ADHD and epilepsy may also allow a person to differentiate between the disorders according to the nature of their associated inattentive episodes (Williams et al., 2002). ADHD, Epilepsy, and School Today, the assessm ent and treatment of ADHD and epilepsy routinely involves a multidisciplinary team of professionals drawing from medical, health, and educational

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34 communities (Attention Deficit, 1994; Wr ight, 2002). However, historically, these responsibilities were reserved for the medi cal community (Atkins & Pelham, 1991; Hakola, 1992). The schools, in contrast, sought to iden tify and help students with high frequency problems that are largely unrelated to health (e .g., specific learning disa bility [SLD]) (Wodrich, Kaplan, & Deering, 2006). Thus, students with ADHD and epilepsy were only eligible for special education services if they qualified unde r customary designations, such as SLD, mental retardation (MR), or emotional dist urbance (ED) (Wodrich et al., 2006). Recent research, documenting a high prevalence of chronic health conditions among school-age children (15%) and a he alth-classroom learni ng link, prompted educators to establish more avenues for acquiring special education servi ces for children with chronic health conditions (Wodrich et al., 2006). Today, school-based professionals have more options for assisting students with ADHD and epilepsy than they did in th e past, even if the child is only experiencing relatively minor academic, developmental, or ad justment problems (Wodrich et al., 2006). Of greatest influence was the addition of the special education category Other Health Impaired (OHI) (IDEA, 1990). A memorandum issued by the U. S. Department of Education (USDOE) in 1991 augmented the list of medical disorders for which a student is eligible to receive special services under the category OHI to include ADHD (Wright, 2002). Currently, both ADHD and epilepsy are listed explicitly in the category definition: Other health impairment means having limited st rength, vitality, or alertness, including a heightened alertness to environmental stimuli th at results in limited alertness with respect to the educational environment, that(i) Is due to a chronic or acute health problem such as asthma, attention deficit or attention defi cit hyperactivity disord er, diabetes, epilepsy, a heart condition, hemophilia, lead poisoning, leuke mia, nephritis, rheumatic fever, sickle cell anemia,; and (ii) Adversely affects a child s educational performance (Individuals with Disabilities Act, 1991, P.L. 102-119, 20 U.S.C. 140[a][1]). The inception of Section 504 of the Vocational Re habilitation Act, later incorporated into the Americans with Disabilities Ac t (1990), assumed the schools gr eater responsibility in meeting

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35 the needs of children with ADHD and epilepsy as well (Wodrich et al., 2006). Section 504 guarantees more students with chronic health cond itions accommodations by broadly defining a person with a disability as one who has a physical or mental impairment that substantially limits a major life activity such as learning (Section 12102). The aforementioned changes in special edu cation criteria drove up the administrative prevalence of ADHD dramatically (i.e., th e rate at which ADHD is recognized and accommodated in the schools); specifically, th e administrative prevalence doubled shortly thereafter (Nigg, 2006; Swanson et al., 1998). For example, in general, children with ADHD are eligible for three special education categories: LD, ED, and OHI. Rates of children with ADHD being served in programs for LD and ED have remained consistent since the official school recognition of ADHD, accounting for approximately 25% and 40% of child ren in the programs, respectively (Forness & Kavale, 2001). In contrast, the number of students being served in programs for OHI tripled since the official school recognition of ADHD (Forness & Kavale, 2001). Forness and Kavale (2001) estimate th at children with ADHD account for 68.7% of children entering special educat ion under the OHI category. Children with epilepsy are also remarkably frequent users of special services (Wodrich et al., 2006). Wodrich et al. (2006) conducted a study to examine special education usage and related assessment procedures, and found that approximately 56% of ch ildren with epilepsy receive special education services Most students were assigned to the traditional developmental category MR (30%). Approximately one in fi ve (16%) students had an OHI designation; however, only 10% of the sample was receiving services based on OHI alone (Wodrich et al., 2006). Stated differently, the remainder of the pa rticipants had at leas t one other non-health designation (e.g., language impaired or SLD) (Wodr ich et al., 2006). No studies to date have

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36 examined special education usage or placement d ecisions for children with absence seizures in particular. School-Based Assessment Under the mandates of IDEA and Se ction 504, if a child is referred for a school-based assessment, schools are required to evaluate ch ildren with any disorder that may have a detrimental impact on school performance (W right, 2002). The goal of the school-based assessment is to determine the presence and severity of an educationally-rel ated disability, and to determine the assignment of services (W right, 2002). Since ADHD and epilepsy are not traditional special education categories, educator s often have to adopt diagnostic procedures developed in clinic settings and adapt them to the school setting (Forness & Kavale, 2001). The school-based evaluation involves a multidisciplinary team of professionals who jointly decide on the nature and extent of servic es that are necessary to meet the childs individual needs. One member, the school psychologist, is expected to understand the impact of health on learning, and to work to ameliorate the impact of chronic illness on functioning at school (Wodrich et al., 2006). The School Psychologist Teachers regularly refer child ren to the sc hool psychologist for concerns regarding inattention, given that inatten tion can substantially impair f unctioning at school (Wright, 2002). In fact, in a study conducted by Lloyd et al. (1991), teachers third most common reason for initiating a referral was concerns about inatten tion, accounting for nearly one-fourth of all of referrals made. Within the school system, school psychologists are rega rded as experts in assessment, and they may be expected to have specialized knowledge ab out pediatric disorders (Atkins & Pelham, 1991; DuPaul, 1992; DuPaul & Stoner, 1994; Montague, McKinny, & Hocutt, 1994; Wright, 2002). This assumption may be reasonably close to the truth with respect

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37 to ADHD. For example, Herbert et al. (2004) de monstrated that schoo l psychologists scored significantly higher than teachers on the Knowle dge of Attention Deficit Disorders Scale (KADDS), which measures knowledge and misconceptions about ADHD. School psychology programs, however, spend re latively little time on the recognition of neurological disorders, such as epilepsy (Sbordone & Rudd, 1986, Wright, 2002). No studies to date have explored whether school psychologists recognize neur ological disorders (Sbordone & Rudd, 1986). However, it may be reasonable to hypothesize that, li ke teachers, school psychologists may mistake various medical a nd neurological problems for ADHD-PI (Ball, Wooten, Crowell, 1999). Licensed ps ychologists may have greater expe rtise in the areas of child psychopathology and pediatric disorders. Although, only a small minority of school psychologists employed by the schools are licensed as psychologists. For example, in their study, McGrath and Yalof (2008, February) found that 2 2.1% of school psychologists in their sample were licensed as psychologists. However, c onsidering that the sa mple included college professors and private practitioners (i.e., whom are significantly more likely to hold a Ph.D. and, thus, be licensed as a psychologist ), this figure could be expected to be much lower in practice. Historically, when a school psychologist conducted a school-ba sed assessment, the primary purpose of the assessment was to dete rmine whether the child presented with an educationally-related disability, and whether a change in placem ent was necessary for the child to receive an appropriate education (Mace y, 2005). However, in recent times, school psychologists are being involved earlier in the education proc ess to complete less formal assessments and, more importantly, to implement interventions. Typically, pre-referral interventions involve providing the teacher with support and resources so that he or she can implement effective interventions in the classroom (Macey, 2005). State agencies are

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38 increasingly in support of pre-referral interv entions, since they may decrease the number of students requiring formal assessment a nd special education placement (Macey, 2005). The Integration of Medical and Educational Information It is critical to note that although school-based assessm ents generate im portant educational-related information, they do not yiel d a medical diagnosis. Therefore, if a teacher suspects that a child has an underlying medical di sorder and initiates a re ferral for a school-based evaluation, the child may or may not go on to rece ive an accurate medical diagnosis (i.e., it will depend largely on the school psychologists prowe ss). An accurate medical diagnosis is critical to effective, comprehensive treatment. For example, an early and accurate medical diagnosis can prevent a child from struggling at school by qualifying the child for special services before his or her problems become severe (Wodrich et al., 2006). Diagnostic labels are also helpful for their ability to allow a child to receive pharmacother apy. Finally, by assigning a label to the behavior, practitioners can implement research-based in terventions, proven to be effective (SemrudClikeman, 2005). Pharmacotherapy Pharm acotherapy, an effective treatment for ADHD and epilepsy, requires a formal medical diagnosis. If a child is misdiagnosed as having ADHD-PI when, in reality, they are experiencing absence seizures, the child will fail to receive appropriate treatment, which typically involves AEDs. Moreover, some resear chers and practitioners purport that stimulant medications, which is considered a first-line treatment for ADHD-PI, may actually lower seizure threshold. That is, if a child with absence se izures is incorrectly diagnosed with ADHD and prescribed stimulant medicati on, they may experience a wors ening of symptoms, or may experience an greater frequency of seizures (Williams, 2002; Schubert, 2005). Notably, no controlled studies conducted to date support this contention (Schubert, 2005; Tan & Appleton,

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39 2005). Therefore, if a child exhibits symptoms consistent with a medical disorder, or if the child exhibits symptoms that are inc onsistent with an existing diagnosis (e.g., the child is diagnosed with ADHD-PI, however his or her symptoms seem irregular), teachers should be encouraged to initiate a referral. School-Based interventions Children with epilepsy and ADHD-PI are guarant eed a free public education appropriate to their specific needs as m andated by P.L. 94-142 (Dreisbach, Ballard, Russo, & Schain, 1982). A free and appropriate public educat ion often includes school-based interventions. Children with ADHD-PI and epilepsy are largel y heterogeneous groups or, stat ed differently, there are no specific educational deficits that are common to all children with th e disorders (DuPaul & Stoner, 2002; Dreisbach et al., 1982 ). Therefore, when designi ng interventions, consideration must be given to both the characteristics of the child and the environment, so that services may be tailored to meet each childs individual need s. Specific care must be taken to unsure that services are provided in the l east restrictive environment possi ble (Dreisbach et al., 1982). Since inattention stemming from ADHD-PI and absence seizures manifest similarly, they predispose students to many of the same school related problems (e.g., learning disability, memory deficits, and difficulty with sustained attention) (Forness & Kavale, 2001). As a result, interventions for either disorder may have a num ber of elements in common. For example, well designed interventions targeting inattention may ta ke into account the child s (a) current level of functioning, (b) current presenting problem behavi ors, (c) the possible en vironmental functions of the presenting inattentive behavior, (d) the targ et behaviors of greatest concern to the teacher and student, and (e) elements of the classroom environment and teaching approach that may limit the effectiveness of the interven tions (DuPaul & Stoner, 2002).

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40 Increasingly, the educational community is in favor of providing students with assistance, regardless of the cause of the problem (Gresham, 2004). That is, when students present with inattention, interventions should be implemented immediately, regardle ss of the students disability status (Hale, Kaufman, Naglieri, & Kavale, 2006). By implementing services early, it may reduce unnecessary student failure, labeling, and placement in special education (Gresham, 2004; Hale et al., 2006). Response to intervention (RTI) may be used as a basis for decisionmaking, particularly regarding the modification of interventi ons (Gresham, 2004). RTI relies on a consultative model of service delivery in wh ich specialists, such as school psychologists, design and evaluate interventions. Teachers ar e typically responsible for implementing the interventions directly to students (Gresham, 2004). Fuchs, Mock, Morgan, & Young (2003) descri bed the general RtI model in vague and nonspecific terms as (1) Student s are provided with generally effective instruction by their classroom teacher (Tier1); (2) Their progress is monitored; (3) Thos e who do not respond get something else (Tier 2); (4) Again, their prog ress is monitored; and (5) Those who do not respond either qualify for special education or for special education evaluation (Tier 3). Many researchers and practitioners di verge over how much problem-sol ving should occur at Tier 2, reflecting two, competing RtI paradigms, the st andard protocol vers us the problem-solving model (Hale, Kaufman, Naglieri, & Kavale, 2006). The standard protocol emphasizes scientifically-based classroom instruction and experimental group designs, whereas the problemsolving model emphasizes increasingly individua lized interventions and measurement practices for nonresponsive students as th ey ascend the tiers (Hale et al., 2006). The implicit assumption underlying both paradigms is that insufficient gr owth must signify an inherent deficit or disability (Hale et al., 2006). Implementation and decision-making under the competing models,

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41 however, will differ, and the trade-off will be one of external validity (i.e., the standardized approach) versus internal validity (i.e., the pr oblem-solving approach) (Hale et al., 2006). Given that both models possess clear merits, some res earchers and practitioners advocate the use of a blended approach, which calls for implementation of a standard treatment protocol with some, limited problem-solving starting as ea rly in the process as Tier 2. According to the Office of Special Education Programs (OSEP), Tier 2 services include programs, strategies, and procedures designed and employed to supplement, enhance, and support Tier 1 instruction to all students. Reca ll that, at Tier 2, the level of problem analysis that occurs will depend largely on the paradigm adhered to (i.e., the standard protocol or problem solving approach). Students at Tier 2, particular ly adhering to the standard protocol paradigm, are grouped according to presenting, arguably superf icial, characteristics. For example, students presenting with decoding problems may constitute a group and receive the same research-based reading intervention, regardless of why they are exhibiting difficu lties with decoding. Similarly, students exhibiting inattention ma y receive the same research-bas ed interventions to enhance independent functioning, regardless why they are experiencing difficulties sustaining their attention. If a student responds positively to an intervention, then, argua bly, the cause of the problem is inconsequential. However, if a school-related problem is a symptom of an underlying organic condition, such as a medi cal or neurological disorder, identifying the source of the problem is critical, even when the student appear s to be responding positiv ely to an intervention. Given that children with ADHD and children with absence seizures present similarly, they may be assigned to the same group (i.e., at Ti er 2) and receive the same research-based interventions. While some com ponents of interventions for children with ADHD and absence seizures may be similar, other aspects may diff er considerably. The most notable distinction

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42 pertains to whether the childs behavior is perceived as being controllable, or volitional. Many parents, teachers, and practiti oners perceive inattention stem ming from ADHD and epilepsy as being, at least somewhat, uncontrollable. They believe that the efficacy of pharmacotherapy working at the neurotransmitter level bolst ers this contention (DuPaul & Stoner, 2002). However, research suggests that behavioral modification strategies, such as contingency management programming (e.g., token reinforcemen t), are also effective for children with ADHD, suggesting that they have some contro l over their behavior (DuPaul & Stoner, 2002). With age, children with ADHD-PI can be taught self-management strategies, which require them to recognize and record whether they have demo nstrated a specific beha vior (e.g., inattention) (DuPaul & Stoner, 2002). Conversely, practitioners rare ly recommend that inattent ion stemming from absence seizures be controlled through environmental interventions. Ab sence seizures occur without warning and are usually unprovoked. Individuals experiencing the se izures are often unaware of their occurrence. Therefore, in most cases, beha vioral management would be an inappropriate and ineffective intervention st rategy. Some researchers have demonstrated that highly demanding and stressful situations, such as taking tests, may produce increased absence activity in children (Dreisbach, Ballard, Russo, & Schain, 1982). Others advise that, at times, seizure activity is reinforced inadvertently, since it allows children to avoid noxious environmental events (Dreisbach et al., 1982; Cataldo, Russ o, & Freeman, 1979). When designing interventions for inattention, then, it may be best practice to conduct a functional be havior assessment (FBA) to ascertain the function of the behavior, even when the behavior appears to stem from an underlying neurological problem (Dreisbach et al., 1982).

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43 However, waiting to assess the effectivene ss of school-based inte rventions for students with pediatric disorders, such as absence seizures and ADHD may not onl y be ineffectual, but may actually be harmful, given that untreated medical and neurologically-based problems may portend a myriad of health and safety concerns, such as traumatic brain injury and death. Like academic and behavior problems, pediatric disorder s respond best to early and accurate diagnosis and treatment. Failure to recognize medical and neurologically-based in dicators denies children access to appropriate medical treatment (e.g., ph armacalogical regimens). In the absence of appropriate medical treatment, academic and beha vior problems at school will likely persist, given that even interventions implemented with exceptional intensity and integrity will fail to address the source of the problem With time, childrens academ ic and behavior problems may intensify or grow more pervasiv e, which, eventually, may negatively affect their self-concept and self-esteem. Absence seizures, a subtle yet potentially debi litating type of pediat ric epilepsy, perfectly illustrate how waiting to assess the effectiveness of standard, predetermined interventions may be inappropriate in certai n, limited circumstances. It may be best practice to bypass/discontinue/postpone the Tier process when students present with specific medical and neurological indicators, such as (a) paroxysmal changes in consciousness, (b) acute changes in functioning, (c) progressive loss of previously ma stered developmental milestones or skills, (d) behavioral or attention problems with possible or ganic bases, and (e) th e presence of physical stigmata or dysmorphic features (Wodrich, 2005). Perhaps commonly occurring medical and neurological indicators should be reflected on classand school-wide screening instruments, and personnel responsible for screeni ng students (i.e., likely teachers under the standard protocol

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44 paradigm and specialists, such as school psychologists, under the problem-solving paradigm) should be familiarized with them. Summary All students, including those with ADHD and ep ilepsy, are guaranteed FAPE (Dreisbach et al., 1982). T oday, children with either disorder can receive special services under traditional special education categories, su ch as LD, ED, or MR, or they may qualify under OHI (Forness & Kavale, 2001; Wodrich et al., 2006). They may also receive school-based accommodations according to Section 504 (Forness & Kavale, 200 1; Wodrich et al., 2006). The school-based assessment is designed to determine the presence and severity of an educationally related disability, and to establish the assignment of services (Wright, 2002). The school psychologist is often responsible for conducti ng the school-based assessment, which does not yield a medical diagnosis (Ball et al., 1999; Mill er, 2006; Wodrich et al., 2006). Accurate medical diagnoses can be critical, given that they inform effective tr eatment. For example, despite presenting similarly, children with ADHD and epilepsy benefit from di fferent treatments (Dreisbach et al., 1982; DuPaul & Stoner, 2002 ). Implementing school-based interventi ons, with disregard for the cause of the presenting problem, can be harmful in certa in limited circumstances, given that untreated medical and neurological probl ems may portend a myriad of h ealth and safety concerns. The Instrumentality of Teachers Teachers sp end more time with students than a ny other school personnel and interact with students across a variety of structured and unstr uctured activities and se ttings (Gresham, 2004). They are in an ideal position to pl ay a direct and indirect role in diagnosis and treatment, and, as a result, are regarded as key members in the liv es of children with ch ronic health conditions (Sciutto, Terjesen, & Bender-Frank, 2000). Teachers are responsible for implementing schoolbased interventions, making appropriate referra ls, and are regularly relied upon to provide

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45 accurate information to those responsible for making a diagnosis. They are often regarded as carryover agents, responsible fo r collaborating with diverse pr ofessionals and incorporating findings into their practice (Has lam & Valletutti, 2004). Unfort unately, teachers often have limited knowledge and hold inaccurate beliefs about these disorders, which negatively influences their classroom behaviors and the decisi ons they make (Dunn & Kuntos, 1997). Direct Influence Teachers are responsib le for implementing sc hool-based interventions and for employing developmentally appropriate classroom practices for all students, including those with ADHD and epilepsy (Gresham, 2004). Unfo rtunately, teachers regularly fail to implement interventions as intended, and rarely abide by intervention scripts they are provided with (Gresham, 2004). Researchers have identified several factors that predict teachers will ingness to abide by an intervention script for prolonged periods of time, including (1) whether they condone the use of the intervention strategy, (2) wh ether they view the problem be havior as mutable, and (3) whether they hold negative attit udes toward the child or the child s disorder (Ysseldyke, Pianta, Christenson, Wang, & Algozzine, 1983). Some t eachers, for example, consider behavioral management strategies to be inappropriate, e quating reinforcement to bribery (Schloss & Smith, 1988). Moreover, many teachers attribute problem be haviors, such as inattention, to causes within the child, or to sources out of their control (e.g., the childs home situation) (Ysseldyke et al., 1983). They do not consider it the schools responsibility, the n, to address these behaviors (Gresham, 2004). Teachers rarely attribute devi ations in student performance to a medical condition (Haslam & Valletutti, 2004, p. 5). Given that approximately 85% of children do not have a chronic medical condition that affects th eir performance at school, this assumption is reasonable (Haslam & Valletutti, 2004, p. 5).

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46 Studies suggest that, in general, regular and special education teachers differ with respect to the classroom practices they engage in. For example, as compared to regular education teachers, special education teachers are more w illing to and implement behavioral interventions more often (Forness & Kavale, 2001). They also consult with specialists (e.g., school psychologists, behavior specialists, and other special education teachers) for purposes of intervention planning and development more re gularly than regular education teachers do (Forness & Kavale, 2001). Finally, they are much more likely to use one-on-one instruction, which may be an effective strategy for children who experience lapses in attention (Forness & Kavale, 2001). Regular education teachers, in contrast, are described as desiring little assistance with classroom strategies. Instead, they make refe rrals for the purposes of testing and special education placement (Forness & Kavale, 2001). Regul ar education teachers, then, are thought to operate from a medical model of diagnos is (i.e., they initiate referrals for within child problems) (Leone, 1989). Undoubtedly, these differences reflect, at least to a degree, differences in training and beliefs about behavior and di sorders. For example, historica lly, special education preparation programs have relied much more heavily on beha vioral theory (Forness & Kavale, 2001). With the current shift toward inclusion and unified pr ograms (i.e., those that emphasize elementary education and mild disab ilities), differences in classroom pr actices and beliefs about behavior among regular and special education teachers may become less pronounced. Indirect Influence Teachers can play an im portant indirect role as well through the referrals they make and by providing reliable information to practitioners (Sciutto et al., 2000). Typically, the referral process involves three steps (1) referral, (2) assessment, and (3) placement (Bocian, Beebe, MacMillan, & Gresham, 1999). Given school initiatives to move away from labeling children

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47 and placing them in special education, teachers ma y be reluctant to initiate referrals. Instead, they may be more inclined to request pre-refe rral interventions (i.e., to remediate the problem and, hopefully, avoid special education placemen t) (Gresham, 2004). Therefore, specialists participating in pre-referral interventions, such as school psychologi sts, also have an opportunity to recognize a medical problem and initiate an ap propriate referral. Other factors that, reportedly, discourage teachers from making referrals are (1) having received inadequate training on behaviors that warrant a referral, (2) the hassle of making a referral, and (3) that the referral process can be unclear and confusing (Christe nson et al., 1982; Haslam & Valletutti, 2004). Making a referral to an outside agency or professional is even more convoluted, since structured procedures for initiating a referral ar e not always in place (H aslam & Valletutti, 2004). As a result, teachers must often make decisions on an ad hoc basis (Haslam & Valletutti, 2004). Macey (2005) asked teachers whether they had ever referred a parent to a physician, psychologist, or psychiatrist to obtain an ADHD evaluation. Many teachers responded that they had not, indicating that for a teacher to suggest a diagnosis is against the law. Other teachers, however, indicated that they had (Macey, 2005). Cl early, there is significa nt variation between school district policies and procedures. Given the gravity of receiving an accurate medical diagnosis, teachers should be encouraged to i nvestigate and to become familiar with their particular school districts policie s and procedures for initiating a re ferral to an outside agency or professional (Haslam & Valletutti, 2004). With respect to ADHD, teachers are often th e first to make referrals for assessment (Sciutto et al., 2000). Unfortunate ly, teacher accuracy for ADHD diagnosis tends to be low. For example, Cotugno (1993) found that only 22% of children referred to a clinic specializing in ADHD by teachers received a primary diagnos is of ADHD (Cotugno, 1993). In another study,

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48 only 38% of students suspected of having ADHD by their teachers received a confirmatory diagnosis of ADHD. There are no studies to date describing the accuracy of teacher referrals for children with epilepsy; diagnosis of epilepsy re lies almost exclusivel y on parental reports (Williams et al., 1996). However, teachers can be instrumental to th e early and accurate diagnosis of epilepsy for the same reasons they are valuable to the a ssessment of ADHD: they have close and continuing contact with students, they observe students dire ctly at various times and in multiple settings, and they have the ability to compare the students behavior to peers whom are of the same developmental level and are placed under similar learning conditions. While exact prevalence rates are unavailable, researchers contend that a significant percentage of children are misdiagnosed as havi ng ADHD-PI, when in fact they have epilepsy, or both disorders. It logically follows that teachers, too, may mistake absence seizures for ADHD, a more common pediatric di sorder. This contention is bolst ered by teachers tendency to over-identify ADHD, and by their tendency to overgen eralize other proble matic behaviors to ADHD (Cotugno, 1993; Macey, 2005). That teachers ar e familiar with epil epsy is critical. However, that teachers understand the relationship between ADHD and epilepsy is equally important. Recall that researchers consider ADHD-PI a risk-factor for developing absence seizures (Hersdorffer et al., 2004). That is, when a child receives a diagnosis of ADHD-PI, they are at increased risk for going on to develop epilepsy (Hersdorffe r et al., 2004). Therefore, if a student has received a diagnosis of ADHD-PI, teachers should not automatically assume that their presenting behavior is attributable to ADHD-PI. Instea d, they should explore numerous causes and reasons for attention difficulties, since the child may be experiencing co-morbid seizures (Macey, 2005).

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49 To facilitate the accuracy and us efulness of teacher referrals, practitioners recommend that they compile anecdotal information about the child and his or her behavior into a written report (Haslam & Valletutti, 2004). The written report describes the stude nts behavior in sufficient detail and in behavioral terms. For example, the report should describe the conditions under which the behavior occurs, record the frequency and duration of th e behaviors, and attest to the consistency of the behavior over time (Haslam & Valletutti, 2004). The te acher should rely less on labels that are ambiguous and involve a leve l of interpretation (e.g., lazy or inattentive). Finally, teachers can provide extr emely valuable information about the ways the behavior affects the childs daily functioning (Haslam & Valletutti, 2004). Knowledge and Beliefs Som e researchers hypothesize th at teachers unwillingness to work with students with difficulties, inability to implement interventions effectively in the classroom, and tendency to misidentify students (i.e., over-identify in the case of ADHD and under-identify in the case of epilepsy) all stem from limited knowledge and in accurate beliefs about the disorders. Studies investigating teachers knowledge of ADHD corr oborate that they have a poor understanding of the disorders nature, causes, c ourse, and outcomes (Sciutto et al., 2000). For example, in a study conducted by Ghanizadeh, Bahredar, and Moei ni (2006), only 46.9% of elementary school teachers knew that ADHD is caused by biological or genetic vulnerabil ities. Moreover, the majority of teachers (53.1%) attr ibuted the disorder to parent al spoiling (Ghanizadeh et al., 2006). Another study conducted by Sciutto, Terjese n, and Bender-Frank (2000) revealed that a majority of teachers held th e startling misconception that ADHD symptoms are caused by, and can be controlled by, dietary restrictions. Teach ers were most knowledgeable about symptoms, or the diagnosis of ADHD as outlined in the DSM-IV; they answered more than 80% of items correctly (Sciutto et al., 2000). In one study, teachers who received information on ADHD were

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50 more likely to use positive teaching techniques (e.g., reduction in amount of coursework, use of praise, preferential seating, and allowing for movement) (Ghanizadeh et al., 2006; Glass, 2000). This finding implies that teachers rely on knowledge to inform their practices. Perhaps the most encouraging trend noted across th e disparate research studies wa s that, by and large, teachers desire additional ADHD-related knowl edge and training (Macey, 2005). Studies concerning teachers knowledge and beliefs about epilepsy in the United States (U.S.) are scant in the lite rature (Bishop & Slevin, 2004). Th e results of international investigations converge to re veal several trends (Bishop & Boag, 2006; Bishop & Slevin, 2004). Almost universally in these studies teachers had insufficient knowledge about epilepsy, held erroneous and potentially dangerous beliefs about the disorder (i.e ., first-aide management), and reported receiving little or inad equate training and preparation in disease management (Bishop & Boag, 2006; Bishop & Slevin, 2004; Prpic et al., 2003). For example, in one study, more than 30% of teachers associated epilepsy w ith insanity (Bishop & Boag, 2006). A positive relationship between teacher know ledge and attitudes appears to exist; the more knowledge teachers posses about epilepsy the more willingly they accept a child with epilepsy in their classroom (Bannon, Wilding, & Jones, 1992; Dantas et al., 2001). Additi onally, studies suggest that better-educated individuals, su ch as U.S. teachers, tend to be more knowledgeable and hold more positive attitudes to ward individuals with the disorder (Bannon et al., 1992; Dantas et al., 2001). Finally, while the majority of teachers participating in these studies had not received formal instruction on epilepsy, encouragingly, the vast majority desired additional information and training (Bishop & Slevin, 2004). Numerous studies have sought to identify wh ether teacher characteristics (e.g., teaching regular or special education, age, and experience) predict knowledge of ADHD and epilepsy.

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51 The results have been inconsistent across studies and across disorders. For example, Sciutto et al. (2000) found that knowledge of ADHD was unrelated to age, education level, and number of special education classes taken. Knowledge of epilepsy, in contrast, was positively related to teacher confidence (i.e., the ability to effectively teach a child with epilep sy) and experience (i.e., the number of children with epilepsy they ha d taught) (Sciutto, 2000). Another large-scale study investigating teachers knowledge of epilepsy suggested that level of education, teaching experience, currently teaching a student with epilepsy, self-r eported knowledge of epilepsy, frequency of contact with persons with epileps y, and ethnicity all pred ict knowledge of epilepsy (Bishop & Boag, 2006). Teacher Efficacy Countless studies have dem onstrated that effi cacy expectations aff ect teachers decisionmaking and behavior in the classr oom, such as their decision to initiate a referral (Macey, 2005). An efficacy expectation refers to having confiden ce that one can successfully execute a behavior to produce a desired outcome (Bandura, 1977, p. 193). When forming efficacy expectations, teachers must analyze the task or assess what will be required of them (Tschannen-Moran, Hoy, & Hoy, 1998). For example, to initiate an appropria te referral a teacher must be aware of the problems and behaviors that warrant a referr al, be able to recognize those problems and behaviors, be familiar with the steps for initiating a referral, and be able to carry out those steps effectively. After determining what will be requir ed of them, teachers make inferences regarding the difficulty of the task (Tschannen-Moran et al., 1998). Typically, efficacy is divided into two dime nsions: teaching efficacy and personal efficacy (Ashton & Webb, 1986; Gibson & De mbo, 1984). Teaching efficacy pe rtains to the belief that ones teaching can affect certa in educational outcomes (Macey, 2005). Personal efficacy pertains to the belief that one possesses the skills neces sary to teach students successfully (Macey, 2005).

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52 Woolfolk, Rosoff, and Hoy (1990) found that personal efficacy (i.e., confidence in ones instructional abilities) is related to more humanistic attitudes a bout classroom control, such as the attitude that all humans can be taught. Unsurpri singly, studies suggest that teachers with higher self-efficacy are more likely to agree with regu lar education placement and are less likely to initiate referrals for special education evaluation (Macey, 2005; Podell & Soodak, 1993). Social-cognitive theory proposes another type of expectation: outcome expectancy (Tschannen-Moran et al., 1998). Whereas an effi cacy expectation relates to an individuals conviction that he or she can orchestrate the n ecessary actions to perfor m a given task, outcome expectancy relates to the individuals estimate of the likely consequences of performing the task at the expected level of competence (Tscha nnen-Moran et al., 1998) For example, when considering whether he or she should initiate a referral for a student, a teacher may take into account the outcomes of previous referrals and special education evaluations. Outcome expectancies are thought to add l ittle to the predictive power of efficacy measures, and, as a result, have received little research attention (Tschannen-Mo ran et al., 1998). Researchers do concede, however, that outcome expectancies pr ovide incentives or disincentives for behavior, especially in the form of physical or social rewards, recognition, punish ments, or criticisms (Tschannen-Moran et al., 1998). For example, if a teacher perceives that teachers who initiate high rates of referrals are critic ized and teachers who manage child ren with problem behaviors in the classroom are lauded, he or she may be less inclined to initiate a referral. In general, expectations of personal efficacy come from four sources: (1) performance accomplishments, (2) vicarious experience, (3) verbal persuasion, and (4) emotional arousal (Bandura, 1977). Performance accomplishments refers to personal mastery experiences or, stated differently, depends on whether a person has experienced success in the past. Vicarious

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53 experience suggests that expect ations can be learned from observing others perform tasks without negative consequences (B andura, 1977). Verbal persuasion refers to the use of verbal suggestion in order to convince an individual th at he or she can successfully handle a task. Finally, arousal refers to the f act that individuals often become emotionally and physiologically aroused in the face of difficult situations, and th is information can be indicative about level of skill or ability (Bandura, 1977). Teacher efficacy is conceptualized as being both context and subject-matter specific. That is, a teacher may feel very competent in one si tuation or working with one kind of student and less competent in other situations or working wi th other kinds of students (Tschannen-Moran et al., 1998). Teachers efficacy, or confidence, in a situation depends largely on their subjective knowledge (i.e., perceived competence) (Liljedahl n.d.; Tschannen-Moran et al., 1998). For example, Reid et al. (1994) found that teachers who had read more about ADHD and who had more experience working with individuals with ADHD were more confident that they could meet the needs of students with ADHD. Simila rly, Bishop and Boag (2006) found that teachers who were currently teaching a child with epilep sy and teachers with more years of experience were more confident that they could meet the needs of children with epilepsy. In general, teachers report being more familiar with ADHD th an epilepsy, which is not surprising, since ADHD is significantly more prevalent and has received considerable attention in popular literature and the media (Bishop & Slevi n, 2004; Tschannen-Mora n et al., 1998). However, the distinction between objective a nd subjective knowledge is important, given that teachers regularly overesti mate or underestimate their abilities (Tschannen-Moran et al., 1998). Whereas objective knowledge pertains to the acquisition of facts and accurate information, subjective knowledge is anchored in beliefs (Liljedahl, n.d.). The phrase subjective

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54 knowledge, then, is a misnomer. However, objective and subjectiv e knowledge are not necessarily opposing constructs and, instead, may be viewed as co mplementary subsets of things we believe (Liljedahl, n.d.). For example, whereas the former refers to things we more than believe the latter refers to things we just believe (Liljedahl, n.d.). Although teachers beliefs may be shaped by education and teaching experiences, they are often resistant to change, especially those that are formulated early on in life. Many researchers agree that it is teachers subjective knowledge that determines for the most part what happens in the classroom, given that subjective knowledge influences teachers sense of self-efficacy (Liljedahl, n.d.). Teachers sense of self-efficacy has received considerable research attention as a result. In general, studies suggest that slightly overestimating ones actual capability is associated with the best outco mes (Tschannen-Moran et al., 1998). Although researchers and theorists agree that efficacy is context-and subject-matter specific, consensus regarding the appropriate level of specificity fo r measuring the construct has not been reached. Most current measures of efficacy are considered too general. Single item measures, in contrast, are often found to be unreliable, have limited generalizability, and cannot capture multi-faceted dimensions of the construct (Tschannen-Moran et al., 1998). Therefore, researchers wishing to assess efficacy of a given population should st rive to balance specificity and generality. Preservice Teacher Preparation Programs Knowledge of ADHD a nd epilepsy, experience w ith individuals with the disorders (i.e., frequency of contact), and self-efficacy appear to be among the most important variables for predicting whether a teacher will initiate a referral. An impor tant question, then, is where teachers can acquire this knowledge and experience, and where they can develop a sense of selfefficacy? Preservice teacher preparation programs are ideal for transmitting accurate knowledge to teachers, and for providing them with valuab le training experiences; they are particularly

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55 effective for overcoming public health problem s such as ADHD and epilepsy (Bertolote, 1994; Bishop & Boag, 2006; Ojinnaka, 2002). Increasi ngly, preservice teacher preparation programs include instruction on disabilities in their curricula (Haslam & Valletutti, 2004). For example, preservice teachers preparation programs may incl ude formal instruction on ADHD in courses pertaining to inclusion and clas sroom management, whereas they may include information about epilepsy and seizure management in health science courses (S. Halsall, personal communication, December 3, 2007). To improve preservice teachers sense of self -efficacy, or their confidence that they can accurately recognize pediatric diso rders and initiate appropriate referrals, preparation programs should include field-based experiences, allo wing preservice teachers to experience personal mastery. The opportunity to work successfully with these students while under the guidance of an experienced teacher should increase pers onal mastery (Macey, 2005). The opportunity to observe experienced teachers working successfully with students with disabilities would increase self-efficacy through vicarious experience (M acey, 2005). Clearly, experienced teachers can build preservice teachers confidence verbally, and through gaining experience with students and working through situations their physiological arousal should diminish. Finally, preservice teacher preparation programs could address issu es of teacher confiden ce and involvement in their professional roles (e.g., whethe r it is their responsib ility to initiate a referral when they suspect that a student has an underlying medical problem) (Fritz et al., 1995, p. 207). Efficacy depends largely on teachers subjective knowledge, which may or may not correspond to their objective knowle dge. Studies suggest that teachers regularly overestimate their level of knowledge, and that slightly overestimating ones ab ilities can result in optimal outcomes (Tschannen-Moran et al., 1998). However, clearly, overestimating ones skill level or

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56 abilities can have negative consequences as well For example, a teacher may incorrectly assume that he or she is managing a problem behavior eff ectively and, as a result, fail to investigate and acquire a more effective skill set. Preservice teacher preparation programs can help preservice teachers form more accurate appraisals by assess ing their knowledge formally with tests and providing them with direct feedback. Unfort unately, traditional tests can lack important contextual details, and, as a result, may not nece ssarily predict how a teacher will behave in the classroom. More valid ways of assessment should be developed to measure if, and to what extent, preservice teachers incorporate knowledge of ADHD and epilepsy into daily practice, and to what extent frequency of contact and personal efficacy affects their decision making. Summary Teachers can be extremely infl uen tial to the accurate diagnosis and treatment of ADHD and epilepsy (Gresham, 2004; Sciutto et al., 2000). Unfortunately, teachers often fail to implement interventions as intended, and provide inaccurate or inconsequential information to practitioners (Bishop & Boag, 2006; Cotugno, 1993; Sciutto et al., 2000). These shortcomings are believed to be due, at least in part, to inadequate knowledge and ill-conceived beliefs about the disorders (Bishop & Slevin, 2004; Ghanizadeh et al., 2006). Although findings have been inconsistent across studies, expe riential variables appear to affect knowledge the most. More importantly, knowledge, frequency of contact, and efficacy appear to influence preservice and practicing teachers behavior and decision-making (Macey, 2005). Preservice teacher preparation programs are ideal for transmitting knowledge to preservice teachers. Moreover, well-designed field experiences can provide preservice teachers w ith exposure to individuals with disabilities, which should help to improve thei r sense of self-efficacy (Macey, 2005).

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57 Assessing Professional Judgment Helping professionals, such as teachers, m ake decisions daily and must exercise professional judgment across diverse domains (Tay lor, 2006). Clearly, some decisions are more important than others (i.e., their consequences ar e serious), making the fact ors that affect those decisions of interest to res earchers. Information and incr eased understanding of decision processes may be used to improve training, ev idence-based practices, and policy development (Taylor, 2006). A failure to recognize ADHD-PI or absence seizures can delay appropriate treatment (i.e., both disorders respond positively to pharmocotherapy). Moreover, the misdiagnosis of absence seizures for ADHD ma y actually worsen the childs condition, since stimulant medications may lower seizure thresh old (i.e., raise seizure frequency) (Williams, 2002; Schubert, 2005). Thus, recognizing a seizure a nd making an appropriate referral may be considered an extremely important decision that a teacher must make. When presented with the aforementioned scenario, teachers are ethically e xpected to exercise professional judgment (e.g., make an appropriate referral) and collaborate with professionals (e.g., the school psychologist). However, assessing how teachers react in these s cenarios and what decisions they make can be can be remarkably complex. Traditional methods used to investigate de cision-making issues, such as classical experiments and qualitative techniques (e.g., diar y methods and interviews), are constrained by practical and ethical limitations; they are also criticized for having inadequate validity and limited generalizability (Taylor, 2006; Zeller, 2003). Traditional surveys and questionnaires also, arguably, are not suited for the study of human attitudes and behavior, since they can elicit unreliable and biased se lf-reports (Alexander & B ecker, 1978). Furthermore, they do not allow for strong causal inferences (Zeller, 2003). Vignettes, a me thod popularized by Star in 1950, have been used extensively over the last 50 y ears. However, researchers often pass up this

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58 approach for its inability to provide insight into which factors contribute most to decision-making (Thurman, Lam, & Rossi, 1988). Finally, for resear ching mental illness, Coie, Costanzo, and Cox (1975) came up with a list approach to studying decision-making. The list approach involves providing participants with lists of descriptions of personal attributes and behaviors, and having the participants rate them in order of importance. Unfo rtunately, the list approach is unable to consider contextual factors that influe nce decision-making in real -life situations (Coie et al., 1975). The Factorial Survey The factorial survey, which m ay be consider ed a blend of laboratory experiments and social surveys, addresses many of the afor ementioned methodological limitations (Ludwick & Zeller, 2001). Some clear merits of the research design include high internal validity (i.e., due to the randomization of the factors the vignettes), hi gh external validity (i.e., the decisions closely resemble those in daily life), r obustness (i.e., due to large number s and the unit of analysis), and the ability to relate the findings to other f actors and demographic in formation (Taylor, 2006). The factorial survey research desi gn utilizes true-to-life vignettes that are designed to simulate an event or situation that woul d otherwise be prohibited from investigation (e.g., practical, logistical, or ethical reasons). The factorial survey ha s already proven to be a method for rigorous study in the social sciences and, more recently, in the fields of social work and school psychology (e.g., traumaspecific assessment skills) (Butkereit, 2004; Ta ylor, 2006). The method can be used to elicit participants knowledge, attitudes, and judgments in a situation of interest (Zeller, 2003). Ludwick (2004) provided an important contribution to the literature by demonstrating that, as a measure, the factorial survey design is valid and reliable for assessing judgments and decisionmaking. The factorial survey, then, may an idea l method for investigating whether teachers

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59 recognize absence seizures, diffe rentiate them from ADHD, and exercise good professional judgment by anticipating that they would initiate an appropriate referral (Barter & Renold, 1999; Finch, 1987). Peter H. Rossi pioneered the factorial survey approach (Byers & Zeller, 1995). The factorial survey uses vignettes to assess the e ffects of important independent variables on an outcome decision of interest (Zeller, 2003). A vi gnette is a short story that contains factors relevant to the decision to be ma de. Each vignette is comprised of a series of sentences that are fixed in a certain order (Taylor, 2006). Howe ver, the characteristic s of the story (i.e., independent variables) are varied and manipulated so that they are randomly assigned to subjects (Zeller, 2003). It is this randomization that gives the factorial survey the robustness of an experimental method, yet the complexity of the factors is what upholds the external validity (Ashton, 1999; Taylor, 2006). The information incl uded in the vignettes may be drawn from the available literature, practice know ledge, or a preliminary qualitativ e study (Taylor, 2006). The construction of the vignettes may be facilitated with computer programs, such as VIGWRITE, which randomly selects characteristics to include (i.e., every level of each IV has an equal chance of being selected). Minor adjustments of the vignettes may be necessary as they must be coherent, logical, and internally consistent (Zeller, 2003). Independent variables The indepen dent variables are called dimensions. Each dimension consists of multiple levels (Taylor, 2006; Zeller, 2003). The dimensions are usually categorical but may be ordinal or interval as well (i.e., they can be converted into categorical vari ables) (Zeller, 2003). There is no limit on the number of dimensions and levels that can be used, with some researchers including up to 20 of each (Thurman, Lam, & Rossi., 1988). However, it is important to consider the respondents ability to assimilate large amounts of information, subject willingness, and subject

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60 fatigue (Thurman et al., 1988; Zeller, 2003). With re spect to mental illness, previous research has revealed that longer vignettes w ith more problematic behaviors ar e more likely to elicit more severe judgments from participants. This tendenc y has been coined snow-balling (Thurman et al., 1988). Thus, when designing the factorial surve y, the researcher should balance brevity with complexity, and, ultimately, should match the degree of descriptiveness to the real-life situation he or she is attempting to simulate. Finally, th e researcher should consider the way the vignette levels are weighted. More specifically, if some levels are presented as positive and others negative, it will lead to an inconsistent vi gnette (e.g., a child who is described as being inattentive, alert, and always on-task) (Thurman et al., 1988). The more dimensions and levels a researcher includes, the larger the factorial object universe (Byers & Zeller, 2003). Th e factorial object universe re fers to the set of all unique objects formed by all possible combinations of on e level from each of the dimensions. It is the product of the number of levels for each dimens ion multiplied across all dimensions (Byers & Zeller, 2003). The factoria l object sample refers to the sample of vignettes the researcher elects to use. The factorial object sample should possess the same characterist ics of orthogonality and rectangularity as the universe a nd, thus, is considered an unbiased sample. Researchers have used Monte Carlo studies to demonstrate that, for all intents and purposes all of the dimensions in the sample are uncorrelated with one another (Zelle r, 2003). As a result, every respondents sample is considered to be statistically equivalent (Thurman et al., 1988). Dependent variables The dependent variable is of prim ary im portance. Anywhere between one and three dependent variables can be specifi ed using a factorial survey res earch designs (i.e., above three things get jumbled) (Zeller, 2003). Given that th e purpose of the study is to measure variance in the dependent variable(s), each DV must be capable of showing significant variance. As a result,

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61 researchers often elect to measure the DVs with Likert scales. When utilizing Likert scales for dependent variables, there is a potential that so me respondents will exhibit a tendency to provide high or low ratings (Zeller, 2003) Many researchers conc eptualize this tendency as a subject characteristic (i.e., it may expre ss the subjects particular inte rpretation of the rating scale) (Thurman et al., 1988). To deal w ith rater tendency, a subjects mean rating can me formed by averaging their ratings across the vignettes, and may be included in the OLS regression analysis as a control variable or cova riate (Thurman et al., 1988). Rossi and Anderson (1982) described another method of dealing with rater tendency, which entails including give-away vignettes that precede the actual test vignettes. The give-away vignettes include ambiguous indicators of the variable of interest. For example, in the curr ent case, they may include some, but all not all indicators of ADHD-PI or absence seizures. Afte rward, analyses may be conducted on the actual test vignettes (a) as deviations from their mean, or (b) as residuals from the scores predicted from the give away vignettes (Zeller, 2003). These an alyses have, on occasion, resulted in different substantive results, bolstering the in clusion of give-away vignettes. Subgroup Variation The factorial survey is a power ful research m ethod for detec ting and describing differences across structural conditions. Wh ile not its original purpose, re searchers have found that the factorial survey can sufficien tly detect subgroup variation (Byers & Zeller, 1998). Thus, variability in factorial surveys, as determin ed by the coefficient of determination, can be interpreted in two general ways: due to changes in the independent variables, and due to sample characteristics (Byers & Zeller, 1998). Samples of subjects may be delineated or described based on a range of social or demographic characte ristics (Thurman et al., 1988). However, when modeling subgroup variation, there are several assumptions to consider (Table 1-5).

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62 Attempts to measure subgroup variation in fact orial survey research have generated mixed findings (i.e., it has been detected in some studies and not in othe rs) (Byers & Zell er, 1998). In a study examining perceptions of me ntal illness, demographic fact ors, such as age and gender, influenced decision-making. More specifically, fe males were more likely to rate persons as mentally ill and were more likely to be clas sified as mentally ill by raters. A study concerning teacher reporting of child abuse, in contrast, re vealed that males provided higher ratings (i.e., they were less tolerant of child abuse and more likely to report it to the appropriate authorities) (OToole et al., 1999). Preservice teac hers ratings, then, may be expect ed to vary with respect to these and other educational and experiential variables (e .g., knowledge, experience, and efficacy). Level of Analysis Most researchers utilizing the factorial survey methodol ogy agree that, f or practical purposes, the appropriate level of an alysis is the vignette. As a resu lt, factorial survey data can be analyzed using ordinary least squares (OLS) regr ession, which allows the unique contribution of each level and the total contribution of the levels to be ascertained (R2) (Byers & Zeller, 1995). OLS, in effect, conceptualizes the ratings as linear functions of the person described in the vignette and the characteristics of the rater (Thurma n et al., 1988). This type of analysis is aided by the asymptotic orthogonality of the factor ial survey and the fact that the respondent characteristics are also uncorrela ted with the levels (Thurman et al., 1988). While linearity is an assumption of the model, some dimensions may not be linear. In these cases, binary dummy coding can be used to carry out the regressi on analysis. The unstandardized regression coefficients, then, indicate the relative contribution of each dummy variable to scores on the dependent variable (i.e., compared to the net of th e effects of the other va riables in the equation) (Thurman et al., 1975).

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63 Criticisms While the factorial design is a powerful re search tool, the m et hodology is not without flaws. For example, some researchers have re servations about the va lidity of the methodology and, more specifically, the gene ralizability of the findings. They claim that, because the decisions and judgments are hypothetical, the resu lts cannot be interpreted to suggest what a participant would do if f aced with the situation that the vignette is attempting to simulate (Ludwick & Zeller, 2001). Another pot ential problem relates to the extent to which the vignettes represent the rea lities of the real life events they ar e portraying. While impo ssible to simulate real life events precisely, both of the aforementioned cr iticisms can be addressed by ensuring that the vignettes are sufficiently complex and inco rporate a sufficient num ber of IVs (Ludwick & Zeller, 2001). Some debate exists regarding the level of analysis with factorial su rvey data. Specifically, some researchers claim that treating the vignette as the level of analysis is inappropriate, since treating participant responses as independent causes the sample sizes to be artificially inflated. They contend that the more appropriate level of analysis is the re spondent, suggesting that hierarchical models (i.e ., logit) are better suited for analyz ing factorial survey data. Degenholtz, Kane, Kane, and Finch (1999) enumerate four distinct advantages to hierarchical models. First, they allow the researcher to take the nested stru cture of the data into account, which allows for the accurate specification of effect s of variables at different leve ls of aggregation (Hox & Kreft, 1994). Second, there may be substantial intra-class correlation (ICC), which may lead to inaccurate estimates of standard errors (Degenholtz et al., 1999). This is not unusual of factorial survey data, since the method is often conducted with intact social units, su ch as teachers. Third, hierarchical models allow the anal yst to test the hypothesis that a va riable has a different effect in different cross sectional units (i.e., a random coefficients mode l) (Degenholtz et al., 1999).

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64 Finally, hierarchical models specify fixed-effects, in which dummy variables are included for each higher-level unit (Degenholtz et al., 1999). Hier archical models, then, may be more suitable for analyzing factorial survey data when the dependence between observa tions is substantial. Rebuttal In response to claim s that hierarchical modeling is more appropriate for factorial survey data, researchers in support of OLS concede that strictly speaking, the systematic probability samples do not meet the independent sample selection assumption (Zeller, 2003). Moreover, they grant that major deviations from independent m easures are not robust. That is why, whenever possible, researchers attempt to use independent measures (Zeller, 2003). However, when researching practical problems, it may be impossi ble to obtain purely independent measures. In response, researchers may choose to use measures in which the departure from independence is so slight that it is still reasona ble to assume that the measures are independent (Zeller, 2003). Most factorial survey research operates on this reasonable and robust assumption (Zeller, 2003); researchers tolerate minor devia tions inherent to the factorial survey as robust. Zeller (2003) conducted an analysis plus simulation to answ er the question how much dependency can we have in the data without arti ficially inflating sample sizes ? Zeller (2003) concluded: There can be substantial dependency among obs ervations without seriously altering the pattern of the findings. As much as half of the variance in the dependent variable can be driven by the subject, not the vignette, with only a minor alteration in the nature of the relationship between the independent va riables and the dependent variable. Summary Recognizing a m edical disorder and initiati ng an appropriate refe rral is an important decision that many teachers must make (Taylor, 2006). Investigating judgment and decisionmaking can be remarkably complex for a variety of reasons. The factorial survey research design addresses many of the methodological limitations associated with tr aditional methods of

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65 assessing judgment and decision-making (Tay lor, 2006; Zeller, 2003). Although an imperfect methodology, researchers have found the factorial survey suitable for rigorous research (Butkereit, 2004; Taylor, 2006). Merits of the me thodology are that it can be used to make causal inferences and detect subgroup va riation (Byers & Zell er, 1998). However, some debate exists regarding the appropriate level of analysis for analyzing factor ial survey data (Zeller, 2003). Until the debate is resolved, it may be best practice to estimate the dependence between observations to determine which type of regressi on analysis is most a ppropriate (i.e., OLS or HLM). Conclusion Absence seizures and ADHD-PI are relatively common pediatric disorders that predispose children to a wide-range of problem s, especi ally at school (Schube rt, 2005). With early recognition and treatment, many of the undesira ble educational and psychosocial outcomes associated with the disorders can be redire cted (American Academy of Pediatrics, 2000). However, differentiating between the disorders ca n be remarkably complex, given that they share subtle and overlapping symptomology (Williams et al., 2002). Teacherswho have close and continuing contact with their studentsare in an ideal position to recognize pediatric disorders and initiate appropriate referrals (Bishop & Boag, 2006; Cotugno, 1993; Sciutto et al., 2000). Unfortunately, research suggests that teacher s tend to over-identify children with ADHD, implying that they under-identify children with absence seizures (i.e., they mistake absence seizures for ADHD) (Cotugno, 1993; Sciutto et al., 2000). Teacher characteristics such as efficacy, knowledge, and frequency of contact with persons with pediatric disorders are known to affect professional judgment and decision-making, such as the decision to initiate a referral (Bandura, 1977, p. 193; Bishop & Slevin, 2004; Sc iutto et al., 2000). Teachers difficulty recognizing pediatric disorders and initiating appropriate refe rrals, then, likely stems from

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66 having limited knowledge, inaccurate beliefs, and a poor sense of self-efficacy (Bishop & Slevin, 2004; Macey, 2005; Sciutto et al., 2000). Preservice teacher preparation programs are ideal for transmitting accurate knowledge to preservice teachers and for exposing them to pediatric populations, which, theoretically, should enha nce their self-efficacy (Bishop & Boag, 2006). Therefore, assessing ifand to what extentthese attributes are being transmitted to preservice teachers in preservice teacher preparation progra ms is of significant practical importance. Purpose of the Study The purpose of this stud y was to explore wh ether preservice teachers recognized absence seizures, differentiated them from ADHD, and antic ipated that they would initiate referrals for hypothetical children presenting with absence seizur es; and to identify th e childand respondentlevel characteristics that aff ected their decision-making. More specifically, this study answered the following seven research questions: 1. Do preservice teachers r ecognize absence seizures? 2. What is the unique contribution of each child characteristic (i.e., levels included in the vignettes) and selected respondent characte ristic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice te achers recognition ratings? 3. Do preservice teachers differentia te absence seizures from ADHD? 4. What is the unique contribution of each child characteristic (i.e., levels included in the vignettes) and selected respondent characte ristic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teac hers differentiation ratings? 5. What referral decision do preservice teachers make for hypothetical children presenting with absence seizures? 6. What is the unique contribution of each child characteristic (i.e., levels included in the vignettes) and selected respondent characte ristic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers referral ratings? 7. Do preservice teachers provide different referral ratings for hypothetical children presenting with absence seizures and hypothetica l children presenting with ADHD?

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67 This study will contribute to the existing li terature on preservice teachers knowledge, beliefs, and referral decisions with re spect to ADHD and epilepsy. Additionally, by understanding which childand respondent-level characteri stics affect decision-making, results can be used to make recommendations for programmatic changes to preservice teacher preparation programs (e.g., regarding formal instruction or hands-on experiences).

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68 Table 1-1. Criteria for AttentionDeficit/Hyperactivity Disorder as outlined in the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition Text Revision A. Either (1) or (2) (1) Frequent demonstration of six or more of the following symptoms of inattention. Inattention a. Fails to give close attention to details or makes careless mistakes in schoolwork, work, or other activities b. Has difficulty sustaining attenti on in tasks or play activities c. Does not seem to listen when spoken to directly d. Does not follow through on instructions, and fails to complete homework and chores e. Has difficulty organizing tasks and activities f. Avoids, dislikes, or is reluctant to enga ge in activities that require sustained mental effort (such as schoolwork or homework) g. Loses things necessary for tasks or activities h. Is easily distracted by extraneous stimuli i. Is forgetful in daily activities (2) Frequent demonstration of six or more of the following symptoms of hyperactivityimpulsivity Hyperactivity a. Fidgets with hands or feet or squirms in seat b. Leaves seat in classroom or in other s ituations in which remaining in seat is expected c. Runs about or climbs in situati ons in which it is inappropriate d. Has difficulty playing or engagi ng in leisure activities quietly e. Is on the go or often acts as if driven by a motor f. Talks excessively Impulsivity a. Blurts out answers before questions have been completed b. Has difficulty awaiting turn c. Interrupts or intrudes on others B. Some hyperactive-impulsive or inattentive symptoms that caused impairment were present before age 7 years. C. Some impairment from symptoms is present in 2 or more settings. D. There must be clear evidence of clinically si gnificant impairment in social, academic, or occupational functioning. ______________________________________________________________________________ Note. Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Copyright 2000. American Psychiatric Association.

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69 Table 1-2. Seizure classification Generalized Partial Caused by general biochemical Arise from specific parts of the brain dysfunction (localization related) Examples: tonic-clonic seizures, Ex amples: temporal lobe epilepsy, absence seizures, myoclonic frontal lobe epilepsy. Table 1-3. Overlapping symptoms of ADHD-PI and absence seizures Domain Symptom Physiological Staring Cognitive Average general cognitive ability (typical absence seizures) Inattention Impaired executive functioning and memory Educational Learning disability Underachievement Grade-retention Special education placement Behavioral descri ptors Day-dreamy Absent-minded, or forgetful

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70 Table 1-4. Distinguishing symptoms of ADHD-PI and absence seizures ADHD-PI Absence seizures Fidgeting in seat Cha nges in breathing, drooling, eyes become glassy, becomes stiff High frequency of problems with Low frequency of problems with sustained attention sustained attention Behavior intensity in the clinical, Behavior intensity in the normal, or or severe range average range Onset in school years (with increased Onset during sc hool years or adolescence demands for attention and concentr ation (juvenile ab sence epilepsy) Behavior stable and predicta ble Behavior frequent a nd discreet (i.e., clear onset) (i.e., occurs most situations that require in typical absence seizures sustained attention Behavior sp oradic lasting for protracted periods in atypical seizures. Episodes occur in boring situ ations Episodes occur any time; often during physical activity with hyperventilation. Do not begin abruptly Do begin abruptly Last until something intere sting happens Usually last between 15 and 20 seconds Episodes occur infrequently May occur many times a day Table 1-5. Subgroup variation assumptions* Assumption 1: Subgroups may vary in the average levels of judgments rendered (i.e., judgment thresholds) Assumption 2: Subgroups may vary in the variability of their judgments (i.e., judgment variance) Assumption 3: Subgroups may vary in the extent of norma l stochastic error in the model (i.e., judgment error) (can just compar e coefficients of determination) Assumption 4: Subgroups may vary in the weight s given to different dimensions. *Adapted from Byers and Zeller, 1998.

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71 CHAPTER 2 METHODS AND PROCEDURES Participants and Settings The particip ants included 100 preservice teacher s from the Unified Elementary Proteach Program (UEP) at the University of Florida. Permission to conduct research was received from the Elementary Coordinator/Assistant Director of the UEP prior to data collection. A letter describing the study (Appendix A) a nd inviting participation was se nt to nine instructors who taught a required course during th e semester in which data were collected. All nine agreed to recruit their students du ring a regularly scheduled class period. However, since two instructors co-taught one class, they granted the researcher permission to collect data from students in eight different classes. The research er distributed the research packets, including consent forms (Appendix B) and measurement instruments (Appendix C for a sample instrument), to preservice teachers and discussed the study with participants in person. All preservice teachers were treated fairly as prescribed by the American Psycholog ical Associations ethical guidelines (American Educational Research As sociation et al., 1999). One hundred research packets were distributed to preservice teacher s in eight different seminar classes across a three-week time sp an (i.e., 3/19/2008 through 4/2/2008). Of the 100 preservice teachers recruited, all 100 elected to participate, resu lting in a sample size of N = 100. Table 2-1 provides a summary of the demographic information provided by participants on the Proteach Demographic Information Survey (PDIS) (Appendix D). Participants were primarily female (95%), and ranged in age from 19 to 49 ( M = 22.40, SD = 3.19). Most participants were Non-Hispanic, white (83%). The UEP is designed to prepare teachers with a dual emphasis in elementary education and mild disabilities. The purpose of the program is to prepare teachers who are capable of: (1)

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72 creating and maintaining supportive and productive classrooms for divers e student populations and (2) working collaboratively with school pers onnel, families, and members of the community to develop alternative ways of educating all children, including those who present with unique instructional challenges, be havioral challenges, or both (as cited in the UEP handbook ) UEP students who complete a department approved undergraduate degree in the College of Education are awarded the Bachelor of Arts in Education (B.A.E.). However, to be recommended for certification, UEP students are required to complete an additional year in the UEP Masters program. During their masters year in the pr ogram, students may choose to specialize in elementary education (K-6), which would make th em eligible for a single certification, or they may chose to specialize in exceptional studen t education (K-12), wh ich would make them eligible for dual certif ications. Although the UEP admonishes students against withdrawing from the program after their eighth semest er to enter the work force with their B.A.E. (i.e., a student is not eligible for certification), on average, up to on e-third of pre-service te achers (30%) make this decision (S. Halsall, personal communication, December 3, 2007). For the purposes of this study, participants we re recruited toward th e end of their eighth semester. The majority of participants indicated that they plan to teach in a regular education setting (83.80%). Approximately one-fourth of the participants (23%) indi cated that they were not working toward certification. Of those part icipants working toward becoming certified, 75% planned to earn a single-cer tification, while the remain ing 25% planned to earn dual certifications. Approximately half of participan ts (50.5%) reported having received formal instruction on ADHD, while only 10% of participants indicated th at they had received formal instruction on seizure disorders. Ten percent of partic ipants indicated that they had received formal instruction on the process of initiating a referral (Table 2-1).

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73 The UEP is a standardized program of study, requiring both the completion of formal coursework and field experiences. During their first two years in the program, or for their first four semesters, UEP students are required to complete 60 general ed ucation credit hours. Semester five marks the beginning of their core requirements, and they are awarded their B.A.E. at the completion of semester eight. Beginning semester five, and every semester thereafter, students are required to complete a field component. With each semester, preservice teachers spend more time and are granted more responsibil ity in the classroom. For example, beginning in semester five, they are mentored by a classroom teacher. However, by semester eight, they are spending 20 hours a week in the classroom, co-l eading lessons. See Appendix E for a summary of UEP core curriculum and field requirements. A summary of the instruction preservice teach ers received on ADHD and seizure disorders in each of their core courses is provided in Appendix F. To obtain this information, the researcher began by reviewing the syllabi on file (i.e., in the office of the Department of Teaching and Learning) for each of their core co urses. The researcher browsed the syllabi for anything pertaining to ADHD or se izure disorders. When relevant information was identified the researcher contacted the course instructor via email and asked the inst ructor to answer the following questions: (1) Was ADHD covered in th is course, and (2) Were seizure disorders covered in this course. If the instructor answered yes to either of the aforementioned questions, they were asked to specify to what extent they covered the disord ers with respect to (1) symptom recognition, (2) symptom management, and (3) maki ng a referral. Finally, they were asked to indicate the number of questions they included on tests pertaini ng to each of the disorders. Overall, instructors responses suggest that ADHD was discussed modestly, while seizure disorders were not di scussed at any length.

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74 With respect to ADHD, students received the mo st instruction in their special education courses. However the instruction was limited in scope, relating mostly to legal obligations, classroom accommodations, and behavioral management. For example, classroom accommodations for students with ADHD were discussed in EDF 3115 ( Child Development for Inclusive Education ) and students understanding of the ma terial was assessed with a case study on a course examination (constitutin g 25% of the test). In EEX 3070 ( Teachers and Learners in Inclusive Schools ) special education law was covered and ADHD was included in the discussion. However, no test questions rela ted directly to ADHD. ADHD was not discussed specifically in EEX 3616 ( Core Classroom Management Strategies); however, classroom management strategies for behaviors consistent with ADHD (e.g., inattention, impulsivity, and hyperactivity) were discussed. Notably, no instructors endor sed that they discussed recognition of ADHD symptoms or the process of initiating a referr al for a student suspected of having ADHD. No instructors indicated that they discusse d seizure disorders at any length. In EEX 3070 ( Teachers and Learners in Inclusive Schools ) the health conditions that qualify a student for special education services under the category OHI were discussed. Epilepsy was among those conditions. However, seizure disorders were on ly mentioned and were not discussed in any detail. While not considered to be a core course the researcher contacted the instructor of HSC 3301 ( Health Science in Elementary Education ), since seizure manageme nt is often taught in health science courses. The inst ructor indicated that neither di sorder was discussed specifically. Participants subjective knowledge (i.e., perceived knowledge) of, beliefs about, and experience with ADHD and seizure disorders we re assessed (Table 2-2). Comparisons of participants responses were made using the Wilcoxon Signed Rank Test, a nonparametric test that does not require assumptions about the form of the distribution of the measurements. As a

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75 group, participants perceived themselves as possessing more ADHD-related knowledge than seizure disorder related knowledge ( z = -6.16, p = .000). Participants al so reported having had more contact with persons with ADHD th an persons with seizure disorders (z = -7.52, p = .000). Finally, participants recognition e fficacy, or their confidence that they can identify the disorders accurately, was higher for ADHD than for seizure disorders ( z = -5.51, p = .000). Frequency of contact with persons with ADHD was significantly correlated with efficacy for recognizing ADHD ( r = .54, p = .000). Likewise, frequency of contact with persons with seizure disorders was significantly correlated with effi cacy for recognizing seizure disorders ( r = .48, p = .000). Interestingly, frequency of contact with persons with seizure disorders was also significantly correlated with efficacy for recognizing ADHD ( r = .26, p = .011). The vast majority of participants expressed the belief that referring a student suspected of having an underling medical disorder is part of the teachers role or responsibility ( M = 4.96, SD = 0.97); 92% of participants provided ratings on th e top half of the scale. Having received formal instruction on ADHD was significa ntly and positively associated with preservice teachers subjective knowledge of ADHD, and, likewise, having received fo rmal instruction on epilepsy was significantly and positively associated w ith preservice teachers subjective knowledge of epilepsy (Table 2-3). Surprisingly, having receiv ed formal instruction on seizure disorders was also significantly and positively correlated w ith preservice teachers subjective knowledge of ADHD (Table 2-3). As expected, having received fo rmal instruction on the process of initiating a referral was significantly correla ted with referral efficacy (r = .24, p = .000). Referral efficacy, or preservice teachers confidence that they can initiate a referral effectively, was low (M = 2.02, SD = .94); 96% of participants provided ra tings on the bottom ha lf of the scale.

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76 Measures Vignette Instrument Inform ation on preservice teachers ability to recognize absence seizures and differentiate them from ADHD, and the referral decisions they anticipated that they would make was obtained through ratings on six vignettes a bout hypothetical children (Appendi x C). Three of the vignettes were computer generated using a factorial survey research design (R ossi & Anderson, 1982). Each computer-generated vignette was comprise d of 10 sentences fixed in a certain order; however, one important variable in each sentence was varied. Th e 10 factors that were varied described characteristics of an absence seizure and, according to the literature, were relevant to the decision to be made (Taylor, 2006). Using a random numbers procedure, the vignettes were generated randomly so that all levels of each in dependent variable had an equal probability of being included (Ludwick, 2004). The randomized vignettes were produced in SPSS. The file that was produced was transferred into Microsoft Exce l for data transformation, and then transferred into Microsoft Word where minor editing was completed prior to the vignettes being printed and distributed. Fourteen variables were held constant acr oss the vignettes since they are common to absence seizures and ADHD and, as a result, coul d not be used to differentiate between the disorders: race, gender, grade placement, academic underachievement, learning disability, difficulty paying attention, difficulty concentr ating, difficulty remembering daily activities, difficulty listening when spoken to, difficulty following through on instructions in class, and, behaviorally, being absent-minded, sluggish, daydreamy, and staring blankly. More specifically, the cover page on the vignette inst rument that indicated that each of the six hypothetical children had the following characteristics in common:

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77 They are all Caucasian females in the third grade. Academically, th ey are struggling and are described as absent-minded, sluggish, and day-dreamy. Specifically, each of the children has difficulty, to some extent, paying attention, concentrating, remembering daily activities, listening when spoken to, and fo llowing through on instru ctions in class. Recently, each of the children were referred to and evaluated by th e child-study team at your school. None of them met educational criteria for Specifi c Learning Disability (SLD); both their general cognitive ability and academ ic achievement fell within age and grade level expectations. Independent variables The independent variables (IV), on the other hand, were varied system atically. Ten IVs were used in this study: (1) be havior during episode, (2) respon se to redirection, (3) problems with sustained attention, (4) intensity of inatten tion, (5) onset of episodes, (6) situations episodes occur, (7) duration of episodes, (8) frequency of episodes, (9) post-epis ode behavior, and (10) history of episodes. The IVs were selected for their ability to di fferentiate between the disorders (Ludwick, 2004; Taylor, 2006). Each IV was comprised of two or more levels that were either categorical or ordinal in nature The levels were randomly assi gned within each vignette, giving the factorial survey the essent ial elements of an experiment al design (Taylor, 2006; Ashton, 1999). For the present study, the factoria l object universe in formula form is: 3 x 2 x 4 x 2 x 3 x 2 x 2 x 2 x 3 x 2 = 6, 912. The value of 6,912 represents the entire population of dimension and level combinations possible to create the vi gnettes (Byers & Zellers 2003). Three unique absence seizure vignettes were created for each respondent, resulting in the creation of three hundred unique vignettes. The participants also completed three more vignettes: one fixed vignette depicting ADHD (Table 2-3) and two fixed, give-away vignettes depicting ambiguous indicators of ADHD and absence seizures. The participants responses on the fixed, give-away vignettes were used to derive a mean rating scor e, which allowed the researcher to account for participants rater tendency. The ADHD vignette was used to assess whether the preservice

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78 teachers provided different ratings for the hypothetical children pres enting with ADHD and the hypothetical children presenting with absence se izures (i.e., regardi ng their recognition and referral decisions). See Table 2-4 for a summar y of the IVs and levels assigned within the absence seizure test vignettes and to see th e levels included in the fixed, ADHD vignette. Dependent variables Participan ts were asked to respond to four questions following each vignette. Three of the items were Likert-type, and were used as depend ent variables in the regression analyses. Likert items were utilized for their capability to demonstrate significant variance. The first question asked participants to rate on a Likert-type scale the extent to which the childs behavior was consistent with ADHD, with 1 representing Definitely Not ADHD and 9 representing Definitely ADHD The second question was similar in format to th e first, and asked participants to rate to what extent they thought the chil ds behavior was consistent w ith a seizure disorder, with 1 representing Definitely Not a Seizure Disorder and 9 representing Definitely a Seizure Disorder The third question was open ended and asked partic ipants to specify the best explanation for the childs presenting behavior. Item three allowed pa rticipants the freedom to provide a tertiary, unnamed explanation. Responses to question three were coded qualitatively according to theme. Finally, participants were asked to rate on a Li kert-type scale how likely they were to make a referral for the hypothetical child, with 1 representing Not At All Likely and 9 representing Very Likely Proteach Demographic Information Survey (PDIS) Im portant demographic and experiential inform ation about the participants was obtained through the Proteach Demographic Informati on Survey (PDIS) (Appendix D), a survey developed by the researcher. Completion of the scale involved responding to 16 items. Participants provided informati on about their background (i.e., thei r age, gender, and ethnicity),

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79 their education (i.e., the type of certification they are seeking; th e type of population they intend to teach; and whether they have received fo rmal instruction on ADHD, epilepsy, or on the process of initiating a re ferral), their experience (i.e., their frequency of contact with persons with ADHD and seizure disorders), their knowle dge (i.e., their subjective or self-assessed knowledge of ADHD and seizure disorders), their e fficacy (i.e., their confidence that they can accurately identify ADHD and a seizure disorder, and their confidence th ey know the correct procedure to take when they would like to initiate a referral), a nd their beliefs (i.e., their beliefs regarding whether it is the teachers role or resp onsibility to initiate a referral when he or she suspects that a student has an underlying medical problem). Instrument Development Cognitive in terviews were conducted as part of instrument development to assess possible sources of response error, both on the vignette instrument and on the PDIS (Willis, 1999). To complete the cognitive interviews, five preservice teachers were asked to sign the informed consent form (Appendix G), to read the vignettes, to answer the corresponding questions, and to complete the PDIS. Afterward, the researcher le d a structured session via probing techniques to assess participants comprehe nsion of the questions and to ensure that they were familiar with all of the vocabulary. The researcher also assessed whether there was anything structurally or aesthetically wrong with th e instruments (Willis, 1999). Several changes were made to the instruments based on the participants feedback. For example, a question on the PDIS, asking participants to calculate how many credit hours they had completed, was removed (i.e., it was judged to be too difficult and likely to elicit unreliable responses). Response categories were added to several questions on the PDIS, while response categories were removed from others (e.g., the op tion allowing preservice teachers to indicate that they plan to teach in an inclusive sett ing was removed, since, today, regular education

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80 classrooms are inclusive settings). These changes were made prior to conducting the reliability study. A pilot study was also conducted as part of in strument development to assess the reliability of the vignette instrument. More specifically, the researcher assessed the internal consistency (Cronbachs alpha) and alternate forms reliability of the vignette instru ment. The participants were 45 preservice teachers enrolled in the UEP at the University of Florida: 25 masters level interns and 20 undergraduate level pre-interns. The researcher obtained permission from course instructors to recruit preservice teachers from th eir classes. The researcher met with preservice teachers in five classes to discuss the study and to distribute the consent forms (Appendix H) and study materials (i.e., a cover sheet with general instructions and the child vignette packets) (Appendix B). Of the 45 preservice teachers recruited, all 45 elected to participate in the pilot study and returned their completed materials to the researcher. The participants were asked to read the child vignettes and to complete the questions corresponding to each vignette. The give-away vi gnettes were presented randomly in the first and second positions. The actual test vignettes were presented randomly in positions three through six. Participant responses on the three abse nce seizure vignettes were used to establish the reliability of the instrument. However, sin ce the three static questions on the instrument pertained to three separate cons tructs (i.e., differentiating, recogni zing, and referring), they were conceptualized as subscales. The internal cons istency of participants responses to item one across the three vignettes, to item two across th e three vignettes, and to item three across the three vignettes was calculated. Since items one and three were Likert-type items, Cronbachs alpha analyses were conducted to calculate internal consistency. Based on 45 cases, item one yielded an = .83. Again, 45 cases were analyzed for item three, yielding an = .88. The

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81 Kuder-Richardson Formula 20 (K-R 20) is most appr opriate for assessing internal consistency of dichotomous data, and, as a result, was utilized for item two. Three of the 45 data sets (i.e., respondents) were excluded from analysis due to missing data (i.e., participants did not rate all three items). Based on 42 cases, item two yielde d K-R 20 = .87. Alternate forms, or parallel forms, reliability is calculated with the Pearson Product Moment Correlation Coefficient. That the three absence seizure vignettes were concep tualized as an instrument for the internal consistency procedure resulted in an estimate of alternate forms re liability. That is, for questions one, two, and three, the alternate forms reliability was equivalent to the in ternal consistency (.83, .88, and .87, respectively). Test scores that yield a reliability coefficient of at least .80 are considered sufficiently reliable for most re search purposes (Gall, Borg, & Gall, 1996). Although the open-ended item on the vignette instrument was sufficiently reliable, participants limited variability in responding was judged to be problematic for a regression analysis; only six participants were able to provide an acceptable response, such as seizures, absence seizures, or epilepsy. In general, partic ipants tended to provide more general responses, such as a medical disorder, despite that they were encouraged to provide as specific a response as possible. Therefore, the questi on was retained on the instrume nt for qualitative purposes, but would no longer be used as a DV in the regression analysis. When debriefing the participants, several suggested that the relationship between ADHD and ADHD-PI was unclear to them. Therefore, upon subsequent administration of the instrument, ADHD-PI was replaced with ADHD to avoid confusion. Finally, af ter debriefing the participants four Likert-type items were added to the PDIS. The new items pertained to pres ervice teachers beliefs a bout whether it is the teachers role or responsibility to initiate a referral when they suspect that a student has an underlying medical disorder, whether they feel confident that they know the correct procedure to

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82 take when they would like to initiate a referr al, and how confident th ey are that they can accurately identify the disorders (i .e., recognition efficacy). Knowledge of Attention Deficit Disorders Participan ts were asked to complete the K nowledge of Attention Deficit Disorders Scale (KADDS), a scale designed to measure knowle dge and beliefs about ADHD (Appendix I). The KADDS scale includes 36 items that are presented in a true (T), false (F), or dont know (DK) format (Sciutto & Feldhamer, 2007). By including the response option dont know the KADDS can be used to differentiate what preservice teachers do not know from what they believe incorrectly (i.e., misconceptions) (Sciutto & Feldhamer, 2007). The KADDS measures knowledge and misconceptions in the areas of (1) symptoms/diagnosis of ADHD, (2) the treatment of ADHD, and (3) the associated feat ures of ADHD (Sciutto & Feldhamer, 2007). The KADDS also includes negative indicators of ADHD or stated differently, be haviors that are not characteristic of ADHD. This provided preservice teachers the opportunity to demonstrate that they know what ADHD is, and what it is not (Sciutto & Feldhamer, 2007). Sciutto and Feldhamer (2007) reported estima tes of the KADDS reliability and validity. Internal consistency was estimated with a Coefficient alpha procedure. Coefficient alpha for the 36-item instrument was good ( = .81). The three subscales, symp toms/diagnosis, treatment, and associated features, had moderate levels of internal consistency ( = .50, = .61, and = .60, respectively). The stability of the scale was assess ed with a test-retest pr ocedure with two weeks between the administrations. The test-retest correl ation for the overall in strument was high (.76), whereas the stability of the subscales ranged from moderate to high (.59, .72, .70, respectively). Individuals who had previous exposure to ADHD (e.g., having taught a student with ADHD, or having a family member with th e disorder) performed significantly better on the scale than

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83 individuals who had no experien ce with the disorder. The finding that previous exposure enhanced performance on the KADDS supports that the KADDS is a valid measure of ADHD knowledge. Individuals with more training and greater exposure to information about the disorder also received higher scores on the measure. Knowledge and Attitudes Toward Ep ilepsy and Persons with Epilepsy Participan ts were asked to complete The Scale of Knowledge and Attitudes Toward Epilepsy and Persons with Epilepsy (ATPE -F orm S) (Appendix J). The ATPE-Form S is a psychometrically sound instrument designed to measure preservice teachers knowledge and attitudes toward epilepsy a nd persons with the disorder (Antonak & Rankin, 1982). Clear advantages of the instrument ar e that it is easy to administer and score. The ATPE, a 28-item Likert-type scale, is comprise d of 17 attitude items, 7 knowledge items, and 4 combined knowledge and attitude items. Each item is presen ted as a statement. Respondents indicate their agreement with each statement on a 6-point scale, with -3 representing I disagree very much and +3 representing I agree very much The responses are weighted and summed to generate a global knowledge and attitude score (Antonak & Rankin, 1982). The higher an individuals score on the knowledge scale (i.e., the 7 knowledge items and the 4 knowledge and attitude items), the more epilepsy-related knowledge they possess. Likewise, higher scores on the attitudes scale (i.e., the 17 attitude items and the 4 combined knowledge and attitude items) indicate more favorable attitudes towards indivi duals with epilepsy. Antonak and Rankin (1982) reported estimates of the ATPEs reliability and validity. The corrected Spearman-Brown reliability coefficient was .81, whereas the Coefficient alpha internal consistency homogeneity index based upon ite m variances was .87 (Antonak & Rankin, 1982). With regard to the validity of the ATPE, Antona k and Rankin (1982) report ed that an iterative principal-factors analysis of th e attitudes items yielde d three non-trivia l factors (i.e., prejudicial

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84 stereotypes, behavioral miscon ceptions, and behavioral optimism), which accounted for 68% of the variance in attitudes scores. Factor analysis of the knowledge item correlation matrix yielded five non-trivial factors; however, only one f actor (i.e., optimistic vi ews of the personal competence of persons with epilepsy) was interpretable. The findings that age (r = 0.13, p < .05), educational level ( r = 0.14, p < .05), and being a special service provider (i.e., special educators) ( r = 0.15, p = < .05) were positively correlated with a ttitude and knowledge scores on the ATPE supports that it is a valid measure of epilepsy related knowledge and attitudes. Procedure Child Vignettes Participating preservice teachers were asked to read and respond to questions pertaining to six vignettes (Appendix C). The part icipants received a packet c ontaining a cover sheet and the vignettes presented in random order, with th e exception of the give-away vignettes, which always preceded the test vignettes, but were ra ndomly presented in the first or second position. The preservice teachers were instructed to a ssume that they are elementary teachers in a medium-sized school district. The school is lo cated in a lower-middl e class neighborhood and has approximately 500 students in Kindergarten through grade five. The preservice teachers were told to assume that they are the childrens teach er and that it is the end of the third nine-week grading period. Based on the information presented in each vignette, participants were asked to respond to corresponding questions. They were informed that, although each vignette would have the same basic structure, the details of th e vignettes would vary. Th ey were also asked to consider each child separately. Specific instruc tions for completing the questions were included on each vignette. The preservice teachers were info rmed that each of the six children has certain characteristics in common:

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85 They are all Caucasian females in the third grade. Academically, th ey are struggling and are described as absent-minded, sluggish, and day-dreamy. Specifically, each of the children has difficulty, to some extent, paying attention, concentrating, remembering daily activities, listening when spoken to, and fo llowing through on instru ctions in class. Recently, each of the children were referred to and evaluated by th e child-study team at your school. None of them met educational criteria for Specifi c Learning Disability (SLD); both their general cognitive ability and academ ic achievement fell within age and grade level expectations. Preservice teachers were asked to rate on a Likert-type scale to what extent the childs behavior was consistent with Attention Defic it Hyperactivity Disorder from 1 ( definitely not ADHD) to 9 ( definitely ADHD ), to what extent the childs behavior was consistent with a seizure disorder from 1 ( definitely not a seizure disorder ) to 9 ( definitely a seizure disorder ), and how likely they were to initiate a referral from 1 (not at all likely ) to 9 ( extremely likely ). They were also asked to specify the best explanation for the childs presenting behavior on an open-ended item. Participants responses to item two on the vignette instrument, which asked them to indicate to what extent the childs presenting be havior was consistent with a seizure disorder, were used to represent their recognition of absence seizures. Part icipants recognition ratings were used as the DV in the recognition regression analysis. However, first, the ratings had to be transformed to account for rater tendency. Resi duals were calculated by subtracting each participants rating on question two on the give-away vignette, Anne which contained ambiguous indicators of an absence seizure, from their ratings on the actual test vignettes. Using this procedure, ratings could range from -8 to 8. Transformed recognition ratings ranged from -6 to 8 ( M = 1.89, SD = 2.39). Ratings transformed into positiv e integers (72.7%) when participants rated the hypothetical childs beha vior depicted in the absence seizure vignette as being more consistent with a seizure disorder than the hypot hetical childs behavior depicted in the giveaway vignette. Conversely, ratings transformed into negative integers (5.3%) when participants rated the hypothetical childs be havior depicted in the give -away vignette as being more

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86 consistent with a seizure disorder than the hypothe tical childs behavior de picted in the absence seizure vignette. Participants responses to items one and two, wh ich asked them to indicate to what extent the childs presenting behavior was consistent with ADHD and to what extent the childs presenting behavior was consistent with a se izure disorder, were used to derive their differentiation scores to be used in the in the differentiation regression analysis. For each absence seizure vignette, the respondents rating on item one was subtract ed from their rating on item two. By transforming the scores in this fashion, participants differentiation ratings could range from -8 (indicating the smallest, most inaccurate degree of differentiation) to 8 (indicating the largest, most accurate degree of differentiation) Transformed differentiation ratings ranged from -6 to 8 ( M = 5.20, SD = 2.73). Ratings transformed into positive integers (91.6%) when participants differentiate d between the disorders correctly (i.e ., they rated the hypothetical childs behavior as being more consiste nt with a seizure disorder than ADHD). Ratings transformed into negative integers (3.2%) when participants diffe rentiated between the disorders incorrectly (i.e., they rated that hypothetical childs behavior depicted in the absence seizure vignette as being more consistent with ADHD than a seizure disorder). Participants ratings on question four, which as ked them to indicate how likely they were to initiate a referral fo r the hypothetical children depicted in the vignettes, were used as the DV in the referral regression analysis. Like recognition ratings, referral ratings had to be transformed to account for rater te ndency. Residuals were calculat ed by subtracting participants ratings on question four on the gi ve-away vignette, Anne, which contained ambiguous indicators of an absence seizure, from their ratings on question four on the actual absence seizure test vignettes. Using this procedure, referral ratings could range from -8 to 8. Transformed referral

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87 ratings ranged from -5 to 8 ( M = 1.15, SD = 1.97). Ratings transforme d into positive integers (87%) when participants anticipated that they would be more likely to initiate a referral for the child depicted in the absence seizure vignette than the child depicted in the give-away vignette. Ratings transformed into negative integers (5%) when participants anticipated that they would be more likely to initiate a referral for the child de picted in the give-away vignette than the child depicted in the absence seizure vignette. Participants responses on item three on the vi gnettes, which was the open-ended item that allowed participants to specify the best expl anation for the childs presenting episodes of inattention, were entered into a database verbatim. A significant number of preservice teachers failed to respond to the open-ended item on th e absence seizure and ADHD vignettes (14.7% and 12%, respectively). Nonresponse error occurs when a significant number of participants in a survey sample fail to respond to a question (or questionnaire) and have different characteristics from those who did respond, when these charac teristics are important to the study (Dillman, 2000). To test for nonresponse erro r, participant groups (i.e., those who did and those who did not respond to item three) were compared acro ss eight respondent-level variables that were judged to be important to the study. Comparisons were made using the Mann-Whitney Test, a nonparametric test used to compare groups of data that may not be normally distributed. Results suggest that participant groups came from identical populations (T able 2-5). Therefore, despite the relatively high nonresponse rate, data are considered unbiased with re spect to the variables tested. Responses were then coded according to theme (Table 2-6). Seven themes, or codes, were used: 1 = ADHD; 2 = seizure disorder; 3 = medical or neurological disorder; 4 = environmental explanation; 5 = no problem; 6 = problem is inte rnal to the child, but no t pathological; and 7 =

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88 participant misunderstood the quest ion. For a response to be coded 1, it had to reflect that the child had ADHD (e.g., ADHD or ADD). Sim ilarly, for a response to be coded 2, it had to reflect that the child had a seizure diso rder (e.g., seizure disorder, s eizures, or epilepsy). To be coded 3, the participants response ha d to reflect that something was distinctly wrong with the child (e.g., medical disorder or neuro logical problem). Responses were coded 4 when they reflected that the inattention stemmed from an ex ternal source, or that the inattention could be mediated through the environment (e.g., schoolwork not challenging enough or lessons are too boring). For a response to be coded 5, the participant had to indi cate that the child did not have a problem with inattention (e.g., no problem or there is nothing wrong with her). To be coded 6, the response had to reflect that the problem was internal to th e child, but that the problem behavior was not inherently abnormal (e.g., she has difficulty pa ying attention or she gets distracted easily) Stated differently, responses were coded 6 when the problem was one of degree (i.e., everyone gets distracted at times) and not type (i.e., a behavior that is not expected to occur under any circumstances, such as losi ng consciousness). Finally, responses were coded 7 when it was clear that the participant misunde rstood the question (e.g., h er eyelids flutter, the episodes last up to 30 seconds, or she does not respond to redirection). Demographic Information Participan ts were asked to complete the 16-item Proteach Demographic Information Survey (PDIS). Participants responses to the PD IS were coded numerically and entered into a database. Several of the items were dummy-coded and included as respondent characteristics, or predictor variables, in the regression analyses. Knowledge and Beliefs About ADHD Participants were asked to respond to the K nowledge of Attention Deficit Disorders S cale (KADDS). Specific instructions were included on the scale. They directed the participant to

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89 respond to each of the questions regarding Attention-Deficit/Hyperact ivity Disorders (ADHD) by circling their answer: True, False, or Dont K now. The directions indicat ed that participants should not guess when they are unsure of an an swer and, instead, should respond by circling the response option Dont Know (DK). Finally, participants were reminded not to leave any items blank. Completed KADDS scales were scored as prescribed in the KADDS manual. Participants responses were entered into a database as follo ws: True = 1, False = 2, Dont Know = 3. In order to obtain total scale scores and subscale scores all responses were recoded so that correct answers were assigned a score of 1 and incorrect and dont know answers were assigned a score of 0. Participants scores were then summed, gene rating subscale scores and a total scale score. Participants total scale scores on the KADDS ranged from 8 to 32 and, on average, they answered half of the items correctly (49.82%) ( M = 19.43, SD = 4.76). Total scale scores were used as a respondent characteristic, or as a predictor variable, in the regression analyses. Consistent with the broader body of literature, preservice teachers answered more questions correctly on the symptoms and diagnosis subscale (66.33%) than on the asso ciative features and treatment subscales (44.47% and 49.25%, respectively) (Sciutto et al., 2000). Preservice teachers subjective knowledge of ADHD (i.e., as pe r their ratings on the PDIS) was not significantly correlated with their objective knowledge of ADHD (i.e., their global score on the KADDS) ( r = .20, p = .052). Their scores on the sympto ms and diagnosis subscale of the KADDS, however, were significantly correlated with their subjective knowledge of ADHD ( r = .26, p = .009). Although having received formal in struction on ADHD was significantly correlated with preservice teachers subjective knowledge of ADHD ( r = .37, p = .000), it was not significantly correlated with objective knowledge of ADHD ( r = -.14, p = .170). See Table 2-

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90 7 for a summary of correlations between preser vice teachers subjective and objective knowledge of ADHD. Knowledge and Beliefs About Epilepsy Participants were asked to respond to The Scale of Knowledge and Attitudes Toward Epilepsy and Persons with Epilepsy (ATPE -Form S). Specific instructions were included on the scale. They directed th e participant to read ea ch statement carefully a nd then to circle the appropriate number, rangi ng from -3 to 3, that best corresponded to how they felt. They were informed that there was no time limit for the ques tionnaire, but that they should work as rapidly as they could. Finally, participants were reminde d to respond to every statement. Participants responses to the ATPE were entere d into a database as follows: -3 = 1, -2 = 2, -1 = 3, 1 = 4, 2 = 5, 3 = 6. Sixteen of the items (i.e., ten of the atti tude items and six of the knowledge items) were reverse scored, since disagreement to these items i ndicates either a positive attitude or a correct answer. Participants scores on the 28 items were then summed to generate a global ATPE score. Participants global ATPE scores ranged from 60 to 174 ( M = 143.95, SD = 17.82). Global ATPE scores were used as a respondent character istic, or predictor vari able, in the regression analyses. Participants knowledge scores on the ATPE ranged from 17 to 63 ( M = 48.56, SD = 6.90), which equates to answering 73.58% of items correctly. Their attitudes scores ranged from 43 to 117 ( M = 95.39, SD = 11.68). Research suggests that a positive relationship between teacher knowledge and attitudes exists (Bannon, Wilding, & Jones, 1992; Dantas et al., 2001). Consistent with this finding, participants scores on the knowledge subscale of the ATPE were highly correlated with thei r scores on the attitudes subscale on the ATPE ( r = .841, p = .000). Preservice teachers subjective knowledge of se izure disorders (i.e., as per their ratings on the PDIS) was significantly correlated with their objective knowledge of seizure disorders (i.e., their global scor e on the ATPE) ( r = .24, p = .015). However, when separating ATPE scores into

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91 subscales, knowledge and attitudes, only scores on the attitudes subscale were significantly correlated with preservice teachers subjective knowledge of seizure disorders ( r = .26, p = .008). Although having received formal instruction on se izure disorders was significantly correlated with preservice teachers subjective knowledge of seizure disorders (r = .35, p = .000), it was not significantly correlated with their object ive knowledge of seizure disorders (r = .17, p = .095). See Table 2-7 for a summary of correlations between preservice teachers subjective and objective knowledge of seizure disorders.

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92 Table 2-1. Preservice Teacher-Related Demogra phic Information as Reported on the Proteach Demographic Information Survey (PDIS) Variable Mean/SD % Age (n = 100) 22.40/3.19 Gender (n = 100) Female 95 Male 5 Ethnicity (n = 100) Non-Hispanic, White 83 African American 7 Hispanic 4 Asian 2 Multiracial 3 Other 1 Intended setting (n = 100) Regular education 84 Special education 16 Certification seeking (n =100) Bachelors degr ee, no certification 23 Masters degree, single certification 58 Masters degree, dual certification 19 Formal ADHD instruction (n = 99a) Yes 50.5 No 49.5 Formal seizure disorder instruction (n = 100) Yes 10 No 90 Formal referral in struction (n= 100) Yes 10 No 90 aEvery participant did not complete this item.

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93 Table 2-2. Preservice teachers knowledge, attitude s, and experiential information as reported on the Proteach Demographic Information Survey (PDIS) Variable Mean/SD Percent Subjective ADHD knowle dge (n = 100) 3.22/0.89 1 (No knowledge) 0 2 23 3 39 4 32 5 5 6 (Extensive knowledge) 1 Frequency of contact with ADHD (n = 100) 3.70/1.31 1 (Very infrequent) 4 2 15 3 27 4 24 5 21 6 (Very frequent) 9 ADHD identification efficacy (n = 100) 3.11/1.02 1 (Not at all confident) 4 2 23 3 41 4 23 5 8 6 (Extremely confident) 1 Subjective seizure disorder knowledge (n = 100) 2.31/1.13 1 (No knowledge) 22 2 47 3 17 4 7 5 6 6 (Extensive knowledge 1 Frequency of contact with se izure disorders (n = 100) 1.85/1.39 1 (Very infrequent) 61 2 20 3 6 4 2 5 8 6 (Very frequent) 3 Seizure disorder identification efficacy (n = 100) 2.34/1.13 1 (Not at all aonfident) 23 2 41 3 22 4 8 5 5 6 (Extremely confident) 1

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94 Table 2-2. Continued Variable Mean/SD Perc ent Referral efficacy (n = 100) 2.02/0.94 1 (Not at all confident) 35 2 34 3 27 4 2 5 2 6 (Extremely confident) Role beliefs (n = 100) 4.96/0.97 1 (Definitely not responsibility) 0 2 1 3 7 4 22 5 35 6 (Definitely responsibility) 35 Note. Variables were presented as Likert-type items Table 2-3. Correlation matrix for selected preservice teacher characteristics as reported on the Proteach Demographic Information Survey (PDIS) Characteristics 1 2 3 4 5 6 7 8 9 10 11 1. ADHD knowledge __ .42 .41 .21.75.40.29.28 .37 .26.14 2. SD knowledge __.25.60.38.78.23.25 -.12 .35-.06 3. ADHD frequency __.32.54.13.08.15 .35 .08.13 4. SD frequency __.26.48.06.09 .02 .08-.16 5. ADHD efficacy __.43.29.13 .33 .13.10 6. SD efficacy __.21.22 -.03 .31-.13 7. Referral efficacy __.14 .04 .10.24 8. Beliefs about role __ .17 .12.01 9. ADHD instruction __ .20.31 10. SD instruction __.22 11. Referral instruction __ Note. N = 100. ADHD knowledge = respondents subjective knowledge of ADHD; SD knowledge = respondents subjective knowledge of seizure disorders; ADHD frequency = frequency of contact with persons with ADHD; SD frequency = frequency of contact with persons with seiz ure disorders; ADHD efficacy = respondents confidence that they can recognize ADHD; SD effi cacy = respondents confidence that th ey can recognize a seizure disorder; Referral efficacy = respondents confidence that they can initiate a referral correctly; Beliefs about role = respondents belief about whether it is the teachers role to refer; ADHD instruction = fo rmal instruction on ADHD; SD Instruction = formal instruction on seizure disorders; Referral instruction = formal instruction on initiating a referral.

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95 Table 2-4. Independent variables and levels assigned within the vignettes Vignette levels IV Levels Absence seizure ADHD-PI Behavior 4 (Categorical) Eyes role upward Head drops slightly Eyelids flutter Smacks her lips Fidgets Response 2 (Categorical) Unresponsive to physical redirection Unresponsive to verbal redirection Usually responds to redirection Sustained attention 2 (Categorical) Usually completes homework assignments Usually stays on-task in class Starts, but does not complete homework assignments and does not remain on-task in class. Intensity 2 (Ordinal) Normal, or average range Moderate, or at-risk range Severe, or clinical range. Onset 2 (Categorical) Abrupt; stops talk ing mid-sentence Abrupt; stops walking mid-step Begins gradually Situations 3 (Categorical) In all situations, even during play Most often during physical activity (hyperventilation) Early in the morning and directly following lunch In boring situations, or those that require sustained attention and concentration Duration 2 (Categorical) Up to 30 seconds Up to 60 seconds Until something interesting happens Frequency 3 (Categorical) Frequent Sporadic Consecutive Occasional and predictable Post-episode behavior 2 (Categorical) Has no recollection of what happened during the elapsed time Resumes to previous train of thought as shown by speech or action Alert

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96 Table 2-4. Continued Vignette levels IV Levels Absence seizure ADHD-PI History 3 (Categorical) Indicates that she has received a diagnosis of ADHD-PI Documents a pattern of problems that began suddenly in the second grade Provides no indication that she has had problems with inatten tion or concentration in the past Documents a pervasive and longstanding history of attention and concentration problems Note. Behavior = behavior during episode; Response = response to redirection; Sustained attention = problems with sustained attention; Intensity = intensity of inattention; Onset = onset of episodes; Situations = situations episodes occur; Duration = duration of episodes; Frequency = frequency of episodes; History = history of episodes. Table 2-5. Mann-Whitney test statistics to asse ss for nonresponse error on the open-ended item across the vignettes Absence Seizure ADHD Variable z (p) z (p) ADHD knowledge -1.31 (.258) -0.80 (.426) SD knowledge -0.03 (.975) -1.50 (.132) ADHD frequency -0.72 (.472) -0.86 (.391) SD frequency -0.67 (.500) -1.49 (.135) ADHD efficacy -1.03 (.304) -0.69 (.491) SD efficacy -0.60 (.550) -0.69 (.945) Referral efficacy -1.69 (.091) -0.31 (.758) Beliefs about role -0.23 (.821) -0.15 (.885) Note. Comparisons were made across participants who did and who did not provide a response on item three on the vignette instrument, which asked them to specify the best explanation for the childs presenting episodes of inattention. ADHD knowledge = respondents objective knowledge of ADHD; SD knowledge = respondents objective knowledge of seizure disorders; ADHD frequency = frequency of contact with persons with ADHD; SD frequency = frequency of contact with persons with seizure disorders; ADHD efficacy = respondents confidence that they can recognize ADHD; SD efficacy = respondents confidence that they can recognize a seizure disorder; Referral efficacy = respondents confidence that they can initiate a referr al correctly; and Beliefs about role = respondents belief about whether it is the teachers role to refer.

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97 Table 2-6. Preservice teachers explanations for the hypothetical childrens presenting episodes of inattention Vignette Explanation Absence Seizure ADHD 1. ADHD 5 (2.0%) 120(45.5%) 2. Seizure disorder 158 (61.7%)0(0%) 3. Medical or neurological problem 27 (10.5%)3(1.1%) 4. Environmental source 7 (2.7%) 45(17.0%) 5. No problem 1(0.4%) 6(2.3%) 6. Internal (degree) 3(1.2%) 63(23.9%) 7. Participant misunderstood 48(18.8%)27(10.2%) Total 256a (100%) 264b (100%) Note. Numbers in parentheses indicate percent of participants endorsing the response. aTotal number of participants who responded to the item on the absence seizure vignettes. bTotal number of participants who r esponses to the item on the ADHD vignettes.

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98 Table 2-7. Correlations between preservice teachers objective and subjective knowledge Variables 1 2 3 4 5 6 7 8 9 10 11 1. Subjective ADHD knowledge -.42** .16 .26** .18 .06 .07 .04 .09 .37** .26* 2. Subjective SD knowledge -.10 .25* .04 -.01 .24* .18 .26** -.01 .35** 3. KADDS global score -.65** .80** .79** -.08 -.08 -.07 -.14 .03 4. KADDS symptoms/diagnosis -.32** .38** .05 .04 .05 .08 .16 5. KADDS associated features -.42** -.05 -.02 -.06 -.08 -.05 6. KADDS treatment --.13 -.17 -.10 -.27 -.02 7. ATPE global score -.94** .98** .11 .17 8. ATPE knowledge --.10 -.27** -.02 9. ATPE attitudes -.10 .15 10. Formal instruction ADHD -.20* 11. Formal instruction SD -________________________________________________________________________________________________________ Note. SD = seizure disorder. Subjective ADHD knowledge = self-assessed knowledge of ADHD rating; Subjective SD knowledge = self-asses sed knowledge of seizure disorders rating; KADDS global score = Knowledge of Attention Deficit Disorders Scale summed score; KADDS symptoms/diag nosis = Knowledge of Attention Deficit Disorders Scale symptoms and diagnosis subscale score; KADDS associa tive features = Knowledge of Attention De ficit Disorders Scale associative features subscale score; KADDS treatment = Knowledge of Attention Defic it Disorders Scale treatment subscale score; ATPE global score = The Scale of Knowledge and Attitudes Toward Epile psy and Persons with Epilepsy total summed score; ATPE knowledge = The Scale of Kn owledge and Attitudes Toward Epilepsy and Persons with Epilepsy knowledge subscale scor e; ATPE attitudes = The Scale of Knowledge and Attitudes Towar d Epilepsy and Persons with Epilepsy attitudes subscale score. *p <.05. **p <.01

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99 CHAPTER 3 RESULTS This study exam ined whether preservice teachers recognized absence seizures, differentiated them from ADHD, and anticipated that they would initiate a referral; and it explored whether childand res pondent-level variables affected their ratings. More specifically, this study was designed to answer seven research questions. The resu lts of this investigation will be presented by research question. Question 1 Do preservice teachers recognize absence seizures? Descriptive statistics f or item two on the ab sence seizure test-vignettes, which asked participants to rate to what extent the childs presenting behavior was co nsistent with a seizure disorder, were calculated. Participants were aske d to provide ratings on a Likert-type scale from 1 (Definitely Not a seizure Disorder) to 9 (Definitely a Seizure Disorder). Participants mean rating was 7.71 (SD = 1.42). Both the median and m ode ratings were 8, and participants ratings ranged from 1 to 9. The vast majority of par ticipants (92.33%) provided ratings above the midpoint on the scale (i.e., they provided ratings between 6 and 9), i ndicating that they thought the childs presenting behavior was consistent with a seizure disorder. Very few participants (3.33%) rated the childs behavior as be ing inconsistent with a seizur e disorder, or provided ratings between 1 and 4. The remaining percentage of pa rticipants provided neutral ratings, or provided a rating of 5. Descriptive statistics were also calculated for item three on the absence seizure testvignettes, which was the open-ended item that asked participants to specify the best explanation for the childs presenting episodes of inattention. See Table 2-6 for a summary of participants responses to item three. The major ity of participants (61.7%) correctly specifi ed that the childs

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100 inattention could be explained by a seizure di sorder. An additional 10.5% of participants provided a more general explanatio n: that something was distinc tly wrong with the child (e.g., a medical or neurological disorder). Of the participants who responded to item three, all but one recognized that the child was expe riencing problems with inattention, and very few participants incorrectly attributed the childs inattention to ADHD (2%) or to an environmental origin (2.7%). Participants res ponses on item three were significan tly correlated with their ratings on item two on the absence seizure te st vignettes (r = .17, p = .003). Th at is, the more a participant thought that the childs presenti ng behavior was consistent with a seizure disorder the more likely he or she was to indicate that a seizure disorder was th e best possible explanation. Seizure disorder ratings acro ss the give-away vignettes and the test vignette depicting absence seizures were compared using the W ilcoxon Signed Rank Test, a nonpa rametric test that does not require assumptions about the form of the distribution of the measurements. Theoretically, if participants recognized ab sence seizures, they should have provided significantly higher ratings on the absence seizure test vignettes, given that they contained many more indicators than the give-awa y vignettes (i.e., they contained ten explicit indicators vs. a few ambiguous indicators, respectively). As a group, th e preservice teachers provided significantly higher ratings on the absence seizure test vignett e than on the give-away vignettes (z = -14.57, p = .000), suggesting that they did accu rately recognize absence seizures. Question 2 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers recognition ratings? Since preservice teachers graduating from th e UEP program do appear to be able to recognize absence seizures, a multilevel regressi on analysis was conducted to identify those

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101 characteristics, both child and respondent, that allowed them to recognize absence seizures. To determine which type of regression analysis was most appropriate (i .e., OLS or HLM), an unconditional model was estimated, which allowed the researcher to calcu late the intra-class correlation (ICC = .284). Given the nested structur e of the data (i.e., each respondent responded to three absence seizure test vignettes), and that a substantial amount of the variance in responding was due to respondent characteristics (28%), the researcher determined that HLM was most appropriate (i.e., Type 1 error would have been considerable had it been assumed that the data came from a simple random sample) (Willms & Smith, 2005). The data were analyzed using HLM 6 Hierarchical Linear and Nonlinear Modeling software. Cases with missing data were excluded, essentially performing listwise de letion on the level-two data file. Restricted maximum likelihood (REML) estimation method wa s selected, which estimates variances and covariances assuming regression coeffi cients are unknown (Raudenbush, Bryk, Cheong, Congdon, & Toit, 2004). Given that the DV was a Like rt-type variable, and that the data may have violated one or more normality assumptions the fixed effects were estimated with robust standard errors (Ra udenbush et al., 2004). The combined model specified for the recognition regression analysis contained a total of 23 predictor variables (Equation 1-1). The 10 IVs (25 levels) that were randomly combined in the absence seizure test vignettes, and th at were dummy coded into 15 variables ( Xij) were included as the level-one explanatory variab les (Table 2-4). Eight selected respondent characteristics derived from the PDIS, KADDS, and ATPE were specified as the level-two explanatory variables: (1) knowledge/beliefs about ADHD (W1j), (2) knowledge/beliefs about seizure disorders (W2j), frequency of contact with ADHD (W3j), frequency of contact with seizure disorders (W4j), efficacy for recognizing ADHD (W5j), efficacy for recognizing a seizure

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102 disorder (W6j), efficacy for initiating a referral (W7), and beliefs about whether it is the teachers role or responsibility to initi ate a referral when they suspect that a student has an underlying medical problem (W8j). All predictor variables in the m odel were specified as having fixed effects. Level-two predictor vari ables were grand-mean centered to facilitate interpretation (i.e., recognition ratings were adjusted as if all respondents had the overall sample-average level of each respondent characteristic). Yij = 00 + 01W1j + 02W2j+ 03W3j+ 04W4j+ 05W5j+ 06W6j + 07W7 (3-1) + 08W8j +1X1j +2X2j +3X3j +4X4j +5X5j +6X6j +7X7j +8X8j +9X9j +10X10j +11X11j +12X12j +13X13j +14X14j +15X15j + uoj + rij Note. Yij = Recognition rating on particular vignette j; 00 = Grand Mean Recognition rating; uoj = Level-two residual; rij = (Respondent Recognition rating on vignette j) (Respondent Mean Recognition rating). In terms of predicting preservice teachers reco gnition of absence seizures, the coefficients estimated for knowledge of ADHD, eyelids flutte r, no recollection of wh at happened during the elapsed time, and having a previous diagnosis of ADHD-PI were all st atistically significant: t (90) = -2.034 ( p = .045), t (275) = 2.231 ( p = .026), t (275) = 2.264 ( p = .024), and t (275) = -2.301 ( p = .022), respectively. The coefficient estimated fo r knowledge of ADHD, which was a level-two predictor variable, was negative (01 = -0.040, SE = 0.020), meaning that greater knowledge of ADHD predicted lower recognition ratings for preservice teachers average on every other respondent characteristic. Regarding the level-one explanatory va riables, the coefficients for eyelids flutter (6 = 0.429, SE = 0.192) and having no recollecti on of what happened during the elapsed time (11 = 0.295, SE = 0.130) were positive, indicati ng that the presence of these characteristics predicted higher recognition rati ngs. The coefficient for having received a previous diagnosis of ADHD-PI (13 = -0.425, SE = 0.185), in contrast, was negative, meaning

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103 that the presence of this characteristic predic ted lower recognition ratings See Table 3-1 for the complete recognition regression analysis. Question 3 Do preservice teachers differentiate absence seizures from ADHD? A Chi-Square Test of Independence was c onducted to test the association between participants ratings on item two on the vignettes and type of disord er (i.e., whether participants ratings depended on whether the child presented w ith absence seizures or ADHD). The data used in this analysis were particip ants responses to qu estion two, which asked them to rate on a Likert-type scale to what extent the childs pr esenting behavior was consistent with a seizure disorder, with 1 representing Definitely Not a Seizure Disorder and 9 representing Definitely a Seizure Disorder The data were set up so that the ro ws were respondents responses to the Likert-type item and the columns were the groups, which in this case were absence seizures and ADHD. See Table 3-2 for the crosstabulation results of this analysis. On the vignette depicting ADHD, the vast majority of respondents (96%) indi cated that they did not think that the childs presenting behavior was consistent with a seizure disorder; they provided ratings below five, or below the mid-point on the scale (i.e., participan ts provided a rating between one and four). On the vignettes depicting absence seizures, in contra st, the vast majority of participants (92.33%) provided ratings above the mid-poi nt on the scale (i.e., they pr ovided ratings between six and nine), indicating that they did be lieve that the childs presenting behavior was consistent with a seizure disorder. The Pearson X2 (8, N = 600) = 535.309 was st atistically significant ( p = .000), meaning that participants ratings did depend on whether the hypothetical children presented with absence seizures or ADHD. Results suggest th at preservice teachers are able to differentiate between the disorders.

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104 Chi-Square Tests of Independence were also calculated with re sponses to item three, which asked participants to specify the best expl anation for the childs presenting episodes of inattention. The analyses served to assess whet her participants explanations depended on the disorder depicted in the vignett es. Theoretically, if participants could differentiate between the disorders, they should have provided the explanation ADHD significantly more on the ADHD vignette, and, conversely, they should have provided the explanation seizure disorder significantly more on the seizure disorder vignettes. The data used in this analysis were participants responses coded 1 and 2 on question three, which represented ADHD and seizure disorder, respectively (see Table 2-6 for a summa ry of themes and thei r corresponding codes). The data were then dummy-coded into dichotomous variables (i.e., 0 and1). See Table 3-3 for the crosstabulation result s of these analyses. More than half of participants (61.7%) correctly specified that the hypothetical ch ildren in the absence seizure vi gnettes had a seizure disorder. Moreover, not a single particip ant incorrectly iden tified the hypothetical child in the ADHD vignette as having a seizure disorder. The Pearson X2 (2, N = 600) = 227.586 for the seizure disorder explanation was statistically significant ( p = .000), indicating that participants were significantly more likely to provi de the explanation on the absence seizure test vignettes. The Pearson X2 (2, N = 600) = 135.127 for the ADHD explanati on was also statistically significant ( p = .000), indicating that participan ts were significantly more likel y to provide the explanation on the ADHD vignette. Overall, results indicate that preservice teachers e xplanations did depend on the type of disorder depicted in the vignettes, which suggests that they ar e able to differentiate between the disorders.

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105 Question 4 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers Differentiation Ratings? Since preservice teachers graduating from the UEP do seem to be able to differentiate between the disorders, a regression analysis was conducted to identify which characteristics, both child and respondent, allowed them to differentiate between the disorders. That is, on any given vignette, what lead preservice teachers to conc lude that the childs presenting behavior was consistent with a seizure diso rder and not consistent with ADHD? The process of deriving participants differentiation ratings was discussed in the procedures section (chapter two). To determine which type of regression analysis was most appropriate, OLS or HLM, an unconditional model was estimated, which allowed the researcher to calcu late the intra-class correlation (ICC = .28). Given the nested structure of the data, and that a substantial amount of the variance in responding was due to respondent characteris tics (28%), the researcher determined that HLM was most appropriate (i.e., Type 1 error would have been considerable had it been assumed that the data came from a simple random sample) (Willms & Smith, 2005). The data were analyzed using HLM 6 Hierarchical Linear and Nonlinear Modeling software. Cases with missing data were excluded, essentially pe rforming listwise deletion on the level-two data file. Restricted maximum likelihood (REML) es timation method was selected, which estimates variances and covariances assuming regression coefficients are unknown (Raudenbush et al., 2004). Given that the DV was a Likert -type variable, and that the da ta may have violated one or more normality assumptions, the fixed effects were estimated with robust standard errors (Raudenbush et al., 2004).

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106 The combined model specified for the differentiation regression analysis contained a total of 23 predictor variables (Equation 3-2). The 10 IV s (25 levels) that were randomly combined in the absence seizure test vignettes, and th at were dummy coded into 15 variables ( Xij) were included as the level-one explanatory variab les (Table 2-4). Eight selected respondent characteristics, derived from the PDIS, KADDS, and ATPE were cons idered the level-two explanatory variables: (1) knowledge/beliefs about ADHD (W1j), (2) knowledge/beliefs about seizure disorders (W2j), frequency of contact with ADHD (W3j), frequency of contact with seizure disorders (W4j), efficacy for recognizing ADHD (W5j), efficacy for recognizing a seizure disorder (W6j), efficacy for initiating a referral (W7j), and beliefs about whether it is the teachers role or responsibility to initi ate a referral when they suspect that a student has an underlying medical disorder (W8j). All predictor variables in the m odel were specified as having fixed effects. Level-two predictor vari ables were grand mean centered to facilitate interpretation (i.e., variance in differentiation ratings were adjusted as if respondents had the overall sample-average level of each respondent characteristic). Yij = 00 + 01W1j + 02W2j+ 03W3j+ 04W4j+ 05W5j+ 06W6j +07 W7j + (3-2) + 08 W8 +j 1X1j +2X2j +3X3j +4X4j +5X5j +6X6j +7X7j +8X8j +9X9j + 10X10j +11X11j +12X12j +13X13j +14X14j +15X15j + uoj + rij Note. Yij = Differentiation rating on particular vignette j; 00 = Grand Mean Differentiation rating; uoj = Level-two residual; rij = (Differentiation rating on vignette j) (Respondent Mean Differentiation rating). In terms of predicting preservice teachers diffe rentiation ratings, the coefficients estimated for referral self-efficacy and having received a previous diagnosis of ADHD-PI were statistically significant: t (90) = -2.328 ( p = .022) and t (275) =-4.678 ( p = .000), respectively. The coefficient for referral efficacy, a respondent level variable th at assessed how confident preservice teachers

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107 were that they knew how to initiate a referral correc tly, was negative (07 = -0.379, SE = 0.163). This suggested that, for a preservice teacher who was average on every other respondent characteristic, higher referral efficacy predicted lower ratings, or poorer differentiation. The coefficient for having received a previous diagnosis of ADHD-PI was also negative (13 = 1.616, SE = 0.346), meaning that the presence of this child characteristic predicted lower, less accurate differentiation ratings. See Table 3-4 for the complete differentiation regression analysis. Question 5 What referral decisions do pr eservice teachers make for students presenting with absence seizures? Descriptive statistics for question four on the abs ence seizure test vi gnettes, which asked participants to indicate how likely they were to initiate a referral, were calculated. Participants were asked to provide ratings on a Likert-type scale from 1 ( Not At All Likely) to 9 (Extremely Likely) Participants mean rating was 7.52 (SD = 1.62). The median rating was 8, and the mode rating was 9. Participants ratings ranged from 1 to 9. The vast majority of participants (86.29%) provided ratings above the mid-point on the scale (i.e., they provided ratings between 6 and 9), indicating that they anticipated that they would be likely to in itiate a referral for a student presenting with absence seizures. Moreover, only 5.65% of participants anticipated that they would be unlikely to initiate a referral (i.e., they provided ratings on the bottom half of the scale, or below the mid-point on the scale). Results suggest that, as a group, preservice teachers graduating from the UEP do anticipat e that they would initiate a referral for a student presenting with absence seizures.

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108 Question 6 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers Referral Ratings? Since preservice teachers do anticipate that th ey would initiate a referral for a student presenting with absence seizures, a regression analysis was conducted to identify which characteristics, both child and respondent, predict preservice teachers referral ratings. To determine which type of regression analysis was most appropriate (i .e., OLS or HLM), an unconditional model was estimated, which allowed the researcher to calcu late the intra-class correlation (ICC = .62). Given the nested structure of the data, and that a significant amount of the variance in responding was due to respondent characteris tics (62%), the researcher determined that HLM was most appropriate (i.e., alpha inflation would have been considerable had it been assumed that the data came from a simple random sample) (Willms & Smith, 2005). The data were analyzed using HLM 6 Hierarchical Linear and Nonlinear Modeling software. Cases with missing data were excluded (n = 10) essentially performing listwise deletion on the level-two data file. Restricted maximum likelihood (REML) estimation method was selected, which estimates variances and covariances assuming regression coefficients are unknown (Raudenbush et al., 2004). Given that the DV was a likert-type variable, and that the data may have violated one or more normality assumptions the fixed effects were estimated with robust standard errors (Ra udenbush et al., 2004). The combined model specified for the referral regression analysis c ontained a total of 24 predictor variables (Equation 33). The 10 IVs (25 levels) that were randomly combined in the absence seizure test vignettes, and that were dummy coded into 15 variables ( Xij) were included as level-one explanatory variable s (Table 2-4). Eight selected re spondent characteristics, derived

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109 from the PDIS, KADDS, and ATPE were specifie d as level-two explanatory variables: (1) knowledge/beliefs about ADHD (W1j), (2) knowledge/beliefs about Seizure Disorders (W2j), frequency of contact with ADHD (W3j), frequency of contact with seizure disorders (W4j), efficacy for recognizing ADHD (W5j), efficacy for recognizing a seizure disorder (W6j), efficacy for initiating a referral (W7j), and beliefs about whether it is th e teachers role or responsibility to initiate a referral when they suspect that a student has an underlyi ng medical disorder (W8j). Level-two predictor variables were grand mean cen tered to facilitate interpretation (i.e., referral ratings were adjusted as if all respondent s had the overall sample-a verage level of each respondent characteristic). Mean recognition rating (X16), another explanatory variable added to the model, was modeled as a cross level inte raction. Mean recognition rating was group-mean centered, or centered around the re spondents mean. All predictor variables in the model were specified as having fixed effects, except for mean recogniti on rating, which was allowed to have random effects. Yij = 00 + 01W1j + 02W2j+ 03W3j+ 04W4j+ 05W5j+ 06W6j + 07W7j (3-3) + 08 W8j +09 W9j + 1X1j +2X2j +3X3j +4X4j +5X5j +6X6j +7X7j +8X8j +9X9j +10X10j +11X11j +12X12j +13X13j +14X14j +15X15j +16X(W01 + W02 +W03 + W04 + W05 + W06 + W07 + W08)16j + uoj + rij Note. Yij = Referral rating on particular vignette j; 00 = Grand Mean Referral rating; uoj = Level-two residual; rij = (Referral rating on vignette j) (Respondent Mean Referral rating). In terms of predicting preservice teachers refe rral ratings, the coefficient for beliefs about role and the intercept for recogni tion were statistically significant: t (90) = 3.98, p = .022 and t (90) = 6.40, p = .000, respectively (Table 3-6). The coeffi cient for beliefs about role, which was a respondent level variable that assessed pres ervice teachers beliefs about whether it is the teachers role or responsibility to initiate a referral when they suspect that a student has an

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110 underlying medical problem, was positive (08 = 0.474, SE = 0.111). This suggests that, for a preservice teacher average on every other respondent characteristic, the more he or she believes that referring a student is part of the teachers role, the more he or she anticipated that he or she would initiate a referral. The intercept for r ecognition was also positive, indicating that the higher a preservice teachers mean recognition rati ng, the more he or she anticipated that he or she would initiate a referral. Ho wever, modeled as a cross-leve l interaction, mean recognition depended on frequency of contact with persons with seizure disorders (t = 2.176, p = .032, df = 90) and on beliefs about the teachers role ( t = -2.563, p = .012, df = 90). See Table 3-5 for the complete referral regression analysis. Question 7 Do preservice teach ers provide different referra l ratings for hypothetical children presenting with absence seizures and hypothetical children presenting with ADHD? A Chi-Square Test of Independence was conducted to assess whether referral rating depended on type of disorder (i .e., absence seizures or ADHD). The data used in this analysis were participants responses to question four, which asked them to rate on a Likert-type scale how likely they were to initiate a referral. Th e data were set up so that the rows were respondents responses to the Likert-type item and the columns were the groups, which in this case were ADHD and absence seizures. See Table 3-6 for the crosstabulation results of this analysis. On the vignette depicting ADHD, the ma jority of respondents (7 9.80%) anticipated that they were likely to initiate a referral by providing ratings above five, or above the mid-point on the scale (i.e., participants provided a rating between 6 and 9). However, participants anticipated that they would be even more likely to initiate a referral for the students depicted in the absence seizures vignettes; 86.29% provide d ratings above the mid-point on the scale (i.e., they provided

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111 ratings between 6 and 9). The Pearson X2 (8, N = 596) = 39.220 was st atistically significant ( p = .000), indicating that refe rral ratings did depend on type of disorder. Results suggest that, although preservice teachers antici pate that they would initiate referrals for students presenting with both disorders, they anticipat e that they would be more likely to initiate a referral for a student presenting with absence seizures.

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112 Table 3-1. Summary of hierarchical linear modeling analysis for variables predicting preservice teachers ability to recognize absence seizures Variable () SE t df p. Level-one explan atory variables Frequency Frequent (X1) -0.1110.197-0.562275 .574 Sporadic (X2) 0.3130.1971.591275 .113 Situations In all situations (X3) 0.0820.2180.377275 .706 Physical activity (X4) 0.3180.1841.727 275 .085 Onset Stop talking (X5) -0.1810.164-1.102275 .272 Physiological Eyelid flutters (X6) 0.4290.1922.231275 .026* Lip-smacking (X 7 ) -0.1620.244-0.666275 .506 Eyes roll back (X8) 0.3130.1891.653275 .099 Duration Up to 30 seconds (X9) -0.1420.158-0.897275 .371 Response to Redirection Verbal redirection (X10) -0.1420.169-0.835275 .405 Post Behavior No recollection (X11) 0.2950.1302.264275 .024* Sustained attention Completes homework (X12) 0.1360.1610.843275 .400 History Diagnosis of ADHD-PI (X13) -0.4250.184-2.301275 .022* No indication (X14) 0.0890.1740.513275 .608 Intensity Normal intensity (X15) -0.2320.142-1.642275 .101 Level-two explanatory variables (Respondent characteristics) ADHD knowledge ( W1) -0.4000.020-2.03490 .045* SD knowledge ( W2) -0.0010.007-0.20690 .837 Frequency ADHD ( W3) -0.0640.107-0.59390 .554 Frequency SD (W4) 0.0490.0860.56890 .571 Efficacy ADHD ( W5) 0.2040.1281.60090 .113 Efficacy SD (W6) 0.0260.1290.19990 .843 Referral efficacy ( W 7 ) -0.0580.091-0.63290 .529 Role/beliefs (W8) 0.1650.1121.47990 .142 Note. SD = Seizure disorder. See Table 2-4 for a description of all level-one variables. ADHD knowledge = Knowledge of Attention Deficit Disorders Scale score; SD knowledge = Scale of Knowledge and Attitudes Toward Epilepsy and Persons with Epilepsy score; Frequency of ADHD = frequency of contact with persons with ADHD; Frequency SD = frequency of contact with persons with a SD; Efficacy AD HD = efficacy for recognizing ADHD; Efficacy SD = efficacy for recognizing a seizure disorder; Referral efficacy = efficacy for initiating a referral effectively; Role/beliefs = belief about whether it is the teachers responsibility to initiate a referral. p < .05.

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113 Table 3-2. Crosstabulation results for preservice teachers seizure disord er ratings across the ADHD and absence seizure vignettes. Ratings Vignette 1 2 3 4 5 6 7 8 9 Total ADHD 41% (123) 42% (126) 12% (36) 1% (3) 3% (9) 1% (3) 0% (0) 0% (0) 0% (0) 100% (300) Absence seizure 0.33% (1) 1.33% (4) 0.67% (2) 1% (3) 4.33% (13) 6.33% (19) 17% (51) 38% (114) 31% (93) 100% (300) Total 20.67% (124) 43.33% (130) 6.33% (38) 1% (6) 3.67% (22) 3.67% (22) 8.5% (51) 19% (114) 15.5% (93) 100% (600) Note. N = 600. Numbers in parentheses indicate frequency of responses. Seizure disorder ratings represent participants responses to item two on the vignettes, which as ked them to rate on a Likert-type scale to what extent the childs presenting behavior was consistent with a seizure disorder with 1 representing Definitely Not a Seizure Disorder and 9 representing Definitely a Seizure Disorder. Table 3-3. Crosstabulation results for preser vice teacher explanations for the hypothetical childrens presenting epis odes of inattention Vignette Explanation Absence seizure ADHD Seizure disorder 165(61.7%) 0(0.0%) ADHD 7(2.0%) 120(45.5%) Note Numbers in parentheses indicate percent of pr eservice teachers that en dorsed that response.

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114 Table 3-4. Summary of hierarchical linear modeling analysis for variables predicting preservice teachers ability to differentiate absence seizures from ADHD Variable () SE t df p Level-one explan atory variables Frequency Frequent (X1) -0.3640.348-1.047275 .297 Sporadic (X2) 0.4380.3731.174275 .242 Situations In all situations (X3) 0.0690.3920.177275 .860 Physical activity (X4) 0.4440.3341.331275 .185 Onset Stop talking (X5) -0.2370.302-0.786275 .433 Physiological Eyelid flutters (X6) 0.4950.3241.527275 .128 Lip-smacking (X 7 ) -0.3240.446-0.726275 .468 Eyes roll back (X8) 0.3430.3920.875275 .382 Duration Up to 30 seconds (X9) -0.0440.277-0.158275 .875 Response to redirection Verbal redirection (X10) -0.1160.322-0.361275 .718 Post behavior No recollection (X11) 0.4010.2371.690275 .092 Sustained attention Completes homework (X12) -0.0080.291-0.028275 0.978 History Diagnosis of ADHD-PI (X13) -1.6160.345-4.678275 0.000** No indication (X14) 0.0670.2930.229275 0.819 Intensity Normal intensity (X15) -0.1340.284-0.473275 0.636 Level-two explanatory variables (Respondent characteristics) ADHD knowledge ( W1) -0.0360.038-096390 .339 SD knowledge ( W2) 0.0070.0110.59290 .555 Frequency ADHD ( W3) -0.1840.191-0.96290 .339 Frequency SD (W4) -0.0200.159-0.12590 .901 Efficacy ADHD ( W5) 0.0400.2371.43490 .155 Efficacy SD (W6) 0.2790.2051.36390 .177 Referral efficacy ( W 7 ) -0.3790.163-2.32890 .022* Role/beliefs (W8) 0.2280.2101.08390 0.282 Note. SD = Seizure disorder. See Table 2-4 for a description of all level-one variables. ADHD knowledge = Knowledge of Attention Deficit Disorders Scale score; SD knowledge = Scale of Knowledge and Attitudes Toward Epilepsy and Persons with Epilepsy score; Frequency of ADHD = frequency of contact with persons with ADHD; Frequency SD = frequency of contact with persons with a SD; Efficacy AD HD = efficacy for recognizing ADHD; Efficacy SD = efficacy for recognizing a SD; Referral ef ficacy = efficacy for initiating a referral effectively; Role/beliefs = belief about whether it is the t eachers responsibility to initiate a referral. p < .05. **p < 01.

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115 Table 3-5. Summary of hierarchical linear modeling analysis for variables predicting preservice teachers referral decision Variable () SE t df p. Level-one explan atory variables Frequency Frequent (X1) 0.1630.132-0.749266 .216 Sporadic (X2) -0.0110.116-0.091266 .928 Situations In all situations (X3) 0.0140.1060.135266 .893 Physical activity (X4) -0.002-.109-0.019266 .985 Onset Stop talking (X5) 0.0350.1040.338266 .736 Physiological Eyelid flutters (X6) -0.1110.167-0.666266 .506 Lip-smacking (X 7 ) -0.1020.172-.590266 .555 Eyes roll back (X8) -0.0070.157-0.043266 .966 Duration Up to 30 seconds (X9) -0.0520.093-0.563266 .573 Response to redirection Verbal redirection (X10) 0.0750.1030.730266 .466 Post behavior No recollection (X11) -0.0470.122-0.384266 .701 Sustained attention Completes homework (X12) -0.06170.100-0.618266 .536 History Diagnosis of ADHD-PI (X13) -0.0310.109-0.285266 .776 No indication (X14) 0.0750.1150.653266 .514 Intensity Normal intensity (X15) -0.1150.096-1.198266 .232 Recognition (X16) Intercept 0.5920.0926.46090 .000** Knowledge of ADHD -0.0110.017-0.64490 .521 Knowledge of SD 0.0020.0040.52790 .599 Frequency ADHD -0.0230.071-0.32090 .749 Frequency SD 0.1510.0702.17690 .032* Efficacy ADHD 0.0340.1340.25790 .798 Efficacy SD -0.1270.086-1.47390 .144 Efficacy referral -0.0180.078-0.23390 .817 Roles/beliefs -0.1870.073-2.56390 .012* Level-two explanatory variables (Respondent characteristics) ADHD knowledge ( W1) -0.0200.027-0.74990 .456 SD knowledge ( W2) 0.0010.0070.15590 .878 Frequency ADHD ( W3) -0.004-.126-0.03290 .975

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116 Table 3-5. Continued Variable ( ) SE t df p. Frequency SD (W4) 0.1320.0771.71690 .089 Efficacy ADHD ( W5) 0.1630.1631.00190 .320 Efficacy SD (W6) -0.0400.124-0.32490 .747 Referral efficacy ( W 7 ) 0.0340.1300.26390 .747 Role/beliefs (W8) 0.4740.1199.98390 .000** Note. SD = Seizure disorder. See Table 2-4 for a description of all level-one variables. ADHD knowledge = Knowledge of Attention Deficit Disorders Scale score; SD knowledge = Scale of Knowledge and Attitudes Toward Epilepsy and Persons with Epilepsy score; Frequency of ADHD = frequency of contact with persons with ADHD; Frequency SD = frequency of contact with persons with a SD; Efficacy AD HD = efficacy for recognizing ADHD; Efficacy SD = efficacy for recognizing a seizure disorder; Referral efficacy = efficacy for initiating a referral effectively; Role/beliefs = belief about whether it is the teachers responsibility to initiate a referral. p < .05. **p < .01. Table 3-6. Crosstabulation results for preservice teachers referral deci sions on the vignettes Ratings __________________________________________________ Vignette 1 2 3 4 5 6 7 8 9 Total ADHD 0% (0) 1.01% (3) 6.06% (18) 6.06% (18) 7.07% (21) 10.10% (30) 28.28% (84) 22.22% (66) 19.19% (57) 100% (297) Absence seizure 0.33% (1) 0.67% (2) 1.34% (4) 3.34% (10) 8.03% (24) 8.70% (26) 15.72% (47) 26.42% (79) 35.45% (106) 100% (299) Total 0.17% (1) 0.84% (5) 3.70% (22) 4.70% (28) 7.55% (45) 9.40% (56) 21.24% (131) 24.33% (145) 27.35% (163) 100% (596) Note. N = 596. Numbers in parentheses indicate frequency of responses. Percentages are rounded to the nearest hundredth and may not total 100% when summed.

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117 CHAPTER 4 DISCUSSION Introduction Absence seizures are th e most common t ype of pediatric epilepsy, occurring in approximately 2-10% of children with epilepsy (A gnew et al., 1998). Characterized by impaired consciousness that is unaccompanied by large convul sive movements, (typical) absence seizures are often considered benign, given that they rarely cause permanent neurological damage (Leppik, 2000). However, prolonged periods of unconsciousness that result from absence seizures are associated with adverse outcom es, particularly at school (Svoboda, 2004). With proper diagnosis and treatment, much of the l ong-term sequelae of absence seizures can be prevented or redirected. Howeve r, unfortunately, absence seizures are frequently overlooked or misidentified for other pediatric disorders due to the subtlety of their symptoms (Williams et al., 1996). ADHD, and more specifi cally ADHD-PI, is another common pediatric disorder characterized by inattention th at may mimic absence seizures (Pearl et al., 2001). ADHD and absence seizures often occur co-morbidly, whic h further complicates accurate differentiation between the disorders (Schubert, 2005). While re searchers and practitione rs allege that the misdiagnosis of absence seizures for ADHD is a real problem, the magnitude of the problem remains unknown, given that the topic has never been directly investigated. Teachers, perhaps more than any other adult, are in an ideal position to identify absence seizures. Working with a diversity of children, they know what is developmentally normal. Moreover, teachers observe children under dema nding learning conditions where problems with inattention might be expected to arise. Unfortuna tely, previous research has demonstrated that teachers often have limited knowledge of and hold inaccurate beliefs about seizure disorders and ADHD (Bishop & Slevin, 2004; Ghani zadeh et al., 2006). More discon certing is that while their

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118 referral accuracy for ADHD tends to be low, they do not appear to partic ipate in the evaluation process for seizure disorders (Bishop & Boa g, 2006; Cotugno, 1993; Sciutto et al., 2000). Given the unique and influential role they can play in the diagnostic and eval uation process, teachers should be familiarized with absence seizures (i.e., regarding their symptomology and the ways they impair functioning, especially at school) and encouraged to initiate appropriate referrals. The purpose of this study was to investigat e relationships among a number of childand respondent-level characteristics that may affect preservice teac hers judgment and decisionmaking with respect to absence seizures. More sp ecifically, this study exam ined investigated (1) whether preservice teachers re cognized absence seizures, (2) wh at characteristics predicted preservice teachers recognition ratings, (3) whet her preservice teachers differentiated absence seizures from ADHD, (4) what characteristics predicted preservice te achers differentiation ratings, (5) whether preservice te achers anticipated initiating referrals for hypothetical children presenting with absence seizures, (6) what charact eristics predicted preservice teachers referral ratings, and (7) whether preservice teachers anti cipated making different referral decisions for hypothetical children presenting with absence seizures and hypothetical ch ildren presenting with ADHD? If characteristics that predict rec ognition, differentiation, a nd anticipated referral likelihood are identified, research ers and practitioners may gain a better unders tanding of why some teachers refer some children and not others. More importantly, this information can be used to make recommendations for programmatic changes to preservice teacher preparation programs so that teachers are prepared to display good judgment and decision-making from the moment they enter the field. Results of the current study suggest that pres ervice teachers do recogni ze absence seizures. Recognition ratings depended on respondentand child level characteristics. Preservice teachers

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119 were able to differentiate reliably between unambiguous cases of absence seizures and ADHD. However, their proficiency declined when th e hypothetical children pres ented with co-morbid disorders (i.e., when the children presenting with absence seizures had received a previous diagnosis of ADHD-PI). Preservice teachers di fferentiation ratings we re not significantly affected by any other child-level characteristics, which may suggest that they were basing their ratings on their global impressions of the children. In general, preservice teachers anticipated initiating referrals for students presenting with absence seizures. Surprisingly, variance in referral ratings depended exclusiv ely on respondent-level character istics. As a group, preservice teachers anticipated being more lik ely to initiate a referral for a student presenting with absence seizures than a student presenting with ADHD. Question 1 Do preservice teachers recognize absence seizures? Given the lim ited, broader body of literature, th e finding that preservi ce teachers in the current study were able to recognize absence se izures was unexpected (Ghanizadeh et al., 2006; Sciutto et al., 2000). Research suggests that pract ical skills, such as being able to recognize an absence seizure, depend on knowledge (Ghaniza deh et al., 2006; Gl ass, 2000). Preservice teachers in the current study reliably recogni zed absence seizures despite having limited knowledge. For example, the vast majority of preservice teache rs (92.33%) rated the hypothetical childs behavior depict ed in the absence seizure vignettes as being consistent with a seizure disorder. Moreover, only 3.33% of pres ervice teachers rated the childs presenting behavior as being inconsistent with a seizure disorder (i.e., th e remaining 4.33% of preservice teachers provided neutral ratings). More than half of preservice teachers (61.7%) correctly specified that a seizure disorder was the best explanation for the childs presenting episodes of inattention. However, the phrase seizure disorder which appeared in the stem of the preceding

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120 question on the vignette instrument (i .e., item two asked participants to specify to what extent the childs presenting behavior was consistent with a seizure disorder), may have served as a cue and enhanced preservice teachers performance on this item. An additional 10.5% of preservice teachers provi ded a more general explanation: that the hypothetical childs inattention stemmed from an underlying medical or neurological problem. Given preservice teachers job f unction and training (i.e., they are not medical professionals responsible for making a diagnosis), this represents a correct response. The response signifies that something is distinctly wrong with the child, but that the preservice te acher recognizes that he or she is not in a position to assign a medi cal label to the behavior. Recognizing the specific disorder affecting a child is helpful in that it can facilitate early and accurate diagnosis. For example, recognizing a seizure disorder may compel a teacher to initiate a referral promptly, and may increase the likelihood that an appropriate specialist (e.g., a ne urologist) evaluates the child. However, more important is that a teacher recognizes that someth ing is distinctly wrong with a child and initiates an appropriate referral. Once th e referral is initiated, he or she can provide the parent or the professional responsible for conducting the evaluation with detailed information, describing the presenting concern(s) in behavi oral terms. The profe ssional can use this information to assign an appropriate label to the behavior, or provide the child with an accurate diagnosis. Given the results of international studies indicating that teacher s have limited knowledge and hold erroneous, often dangerous, beliefs about seizure disorders, preservice teachers limited knowledge in the current study was not surpri sing (Bishop & Boag, 2006; Bishop & Slevin, 2004; Prpic, et al., 2003). While researchers and educators have not established a benchmark for seizure disorder-related knowledge defining what constitutes low, average, or high levels of

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121 knowledge, it seems reasonable to expect highly educated indi viduals, such as preservice teachers in the U.S., to answer more items correctly. While seizure disorder-related knowledge and information can be transmitted to preservice teachers through a range of educational experiences, most researchers and educators cons ider formal instruction the most efficient mechanism. For this, the researcher asked pr eservice teachers to spec ify whether they had received formal instruction on seizure disorders in the past. Consistent with existing research, only a sm all minority of preservice teachers in the current study indicated that they had received formal instruction on seizure disorders (Bishop & Boag, 2006; Bishop & Slevin, 2004; Prpic, et al., 2003). Theoretical ly, formal instruction should enhance knowledge (Bishop & Boag, 2006). Surprisi ngly, however, formal instruction was not significantly correlated w ith objective seizure disorder-rela ted knowledge (i.e., as measured by the ATPE) in the current study. The significance of this finding remains unclear, since many factors may explain the absence of this im portant relationship. For example, since the relationship between formal instruction and know ledge was ancillary to the main research questions, the researcher did not ask the participants to elaborat e on the type and nature of the instruction they received (e.g., how much instruction they recei ved, or what types of seizure disorders were covered). Preservice teachers classification of formal instruction, then, was subjective, and could not be c ontrolled for systematically (e .g., by the amount of formal instruction they received). More over, since only 10% of the samp le, or 10 participants, endorsed that they had received formal instruction on se izure disorders, the analysis may not have had enough statistical power to dete ct a significant relationship. Although formal instruction did not correlate significantly wi th objective seizure disorderrelated knowledge (i.e., as measured by the ATPE), formal instruction was significantly

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122 associated with participants subjective knowledge of seizure diso rders (i.e., perceived knowledge). The preservice teachers, it seems, assu med that they were more knowledgeable just for receiving the formal instruction. Preservice teachers subjective knowledge was significantly correlated with their ob jective knowledge of seizure disorder s (i.e., their global ATPE score). However, when separating ATPE scores into their corresponding subscales (i.e., knowledge and attitudes), subjective knowledge was only significantly associated with attitudes. This finding suggests that preservice teacher s who perceived themselves as being more knowledgeable did not actually possess more seizure disorder-related knowledge, but, instead, held more positive attitudes towards persons w ith seizure disorders. The literature suggests that subjective knowledge underlies efficacy, and that efficacy motivates behavior (Tschannen-Moran et al., 1998) As expected, preservice teachers subjective seizure disorder knowledge correlated very strong ly with their efficacy for recognizing a seizure disorder in the current study ( r = .78). Therefore, the researcher hypothesized that the relationship between subjective kno wledge of seizure disorders and attitudes towards persons with seizure disorders (i.e., as measured on the ATPE) was mediated by efficacy. That is, preservice teachers who provided higher subjective knowledge ra tings held more favorable attitudes towards persons with seizure disorders because they were more confident that they could recognize seizure disorder s accurately. Surprisingly, pr eservice teachers efficacy for recognizing a seizure disorder was not significan tly associated with th eir attitudes towards persons with seizure disorders. This finding doe s not suggest that all types of efficacy are unrelated to preservice teachers attitudes towa rds persons with seizur e disorders. For the purposes of the current study, the researcher asse ssed very specific types of efficacy. Other types

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123 of efficacy that were not assessed (e.g., effi cacy for managing childrens problem behaviors) may very well influence preser vice teachers attitudes. Question 2 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers recognition ratings? Respondent characteristics Considering previous research stressing the relationship betw een knowledge and practice, the researcher hypothesized that seizure disorder-related knowledge would have a significant, positive effect on preservice teachers ability to recognize absence se izures (Bishop & Boag, 2006; Ghanizadeh et al., 2006; Glass, 2000). Surp risingly, seizure diso rder-related knowledge did not predict preservice teacher s ability to recognize absenc e seizures in the current study. Stated differently, preservice teachers were able to recognize absence seizures with roughly the same accuracy independent of the level of seizure disorder-related knowledge they possessed. This finding challenges the fundamental assump tion that preservice teachers draw on their knowledge to inform their practice (Ghanizadeh et al., 2006; Glass, 2000). However, several explanations may clarify the ab sence of this impo rtant relationship. For example, although researchers often select Likert-t ype scales for their ability to detect va riability in responding, preservice teachers in the current study demonstrated limited variability in responding on the recognition item. More specifically, they tended to provi de ratings on the upper end of the scale. This may suggest that, for research purposes, th e absence seizure test vignettes designed for the current study were too easy (i.e., the correct response was obvious to a ll preservice teachers, regardless of their knowledge or background). Mo re importantly, this may have diluted the

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124 relationships assessed between the predictor vari ables (e.g., knowledge of seizure disorders), and the DV, which was recogniti on of absence seizures. ADHD-related knowledge, in contrast, another respondent-level characteristic included in the regression analysis, did have a signifi cant effect on recognition in the current study. However, the direction of the relationship was astounding. The more ADHD-related knowledge preservice teachers possessed, the lower, less accurate recognition ratings they provided on the absence seizure test vignettes. The researche rs rationale for includi ng objective ADHD-related knowledge as a predictor variab le was that, by knowing what was ADHD, preservice teachers would be able to deduce what was not ADHD (Macey, 2005; Sciutto & Feldhamer, 2007). This assumption seemed particularly plausible considering that preservice teachers were only presented with two competing disord ers: seizure disorder or ADHD. The reason that greater ADHD-related know ledge predicted lower, less accurate recognition ratings remains unclear, especially given preservice teachers performance on the symptoms and diagnosis subscale of the KADDS (i .e., they performed particularly well on this subscale). One, tenuous hypothesis e xplaining this relationship is th at preservice teachers with more ADHD-related knowledge were more aware of allegations that ADHD is over-diagnosed and that teachers tend to over-identify the disorder (Cotugno, 1993; Macey, 2005; Sciutto et al., 2000). To avoid over-identifying children with seiz ure disorders, then, preservice teachers with more ADHD-related knowledge may have been mo re cautious in responding and provided more moderate ratings However, if preservice teachers with more ADHD-related knowledge were concerned about over-identifica tion, theoretically, th ey should have provided more moderate ADHD ratings on the ADHD vignette as well (i.e., to avoid over-identification of ADHD). They did not, calling the veracity of this hypothesis into question.

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125 To clarify the relationship between preser vice teachers knowledge of ADHD and their recognition ratings, supplementary co rrelation analyses were conducted. Overall, preservice teachers objective knowledge of ADHD (i.e., as measured by the KADDS) was not significantly correlated with their s ubjective knowledge of ADHD (i.e., as per their ratings on the PDIS). However, when breaking preservice teachers ob jective knowledge down by area, or by subscale on the KADDS, their objective knowledge on th e symptoms and diagnosis subscale was significantly correlated with thei r subjective knowledge of ADHD. This finding may suggest that preservice teachers define knowledge of ADHD na rrowly (i.e., in terms of symptoms and diagnosis). Consistent with the previous finding rela ting to formal instruction and subjective seizure disorder-related knowle dge, preservice teachers who had received formal instruction on ADHD perceived themselves as possessing more ADHD-related knowledge. However, objectively, they did not. Once more, it seems that the preservice teachers assumed that they were more knowledgeable just for receiving the formal instruction. Correlation analyses revealed that preser vice teachers subjective knowledge of ADHD correlated significantly with their recognition ratings on the abse nce seizure vignettes ( r = .28, p = .005) That is, the more ADHD-related knowledge pr eservice teachers believed that they possessed, the more likely they were to provide a ccurate recognition rating s (i.e., extreme ratings in the correct direction). This may suggest that, like the researcher, preservice teachers assumed that the more ADHD-related knowledge they pos sessed, the better able they would be at recognizing what was not ADHD (Macey, 2005). However, more importantly, this finding may suggest that preservice teachers ar e more likely to base their decisions on subjective, inaccurate beliefs than objective, accurate knowledge. Wh ile discouraging, the premise that preservice teachers base their decision-making and behavior on erroneous beliefs is not surprising. In fact,

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126 many researchers allege that it is teachers subjective knowledge that determines for the most part what happens in the classroom (Liljedahl, n.d.). The literature suggests and the preservice teachers in the cu rrent study corroborated that teachers tend to overestimate their knowledge and abilities (Tschannen-Moran et al., 1998). Clearly, overestimating ones level of know ledge or competence can have negative consequences. For example, in the current se nse, it may stifle a teachers motivation to investigate pediatric disorders. However, numerous studies suggest that slightly overestimating ones ability can have positive consequences as well, since it may lead to an increased sense of self-efficacy, which has been found to enhan ce teachers decision-making and behavior (Tschannen-Moran et al., 1998). That subjec tive knowledge and efficacy are interrelated constructs is bolstered by th e sizable correlations found between subjective seizure disorderrelated knowledge and efficacy for recognizing a seizure disorder ( r = .78) and subjective ADHD-related knowledge and efficacy for recognizing ADHD ( r = .75) in the current study. In fact, the subjective knowledge and efficacy variab les were so interrelated that having included both of them in the regression analyses could have caused coe fficients to be unstable and unreliable due to multicollinearity, making it di fficult or impossible to partition out their individual effects on the dependent variables. The aforementioned findings relating to knowledge, both objective and subjective, have several important practical implications. First, they suggest that, for research purposes, when studying preservice teachers or a ny other participant group of inte rest, objective measures should accompany or replace subjective measures of know ledge. Subjective measures lack the precision that objective measures afford researchers and, unfortunately, can tap into unintended constructs (e.g., questions gauging knowledge may actually be assessing efficacy). With respect to inservice

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127 needs, results suggest that preservice teachers shou ld not be relied on to id entify when they are in need of additional information about pediatric di sorders (i.e., they te nd to overestimate their knowledge and abilities). Moreover, preservice teachers should not be responsible for judging the success of an inservice; in the current study, they assume d they were more knowledgeable just for receiving formal instru ction. Instead, their mastery of important information and skills should be assessed formally with tests. This type of direct feedback should allow them to form more realistic appraisals of their level of knowledge. Child characteristics Two child characteristics predicted p reservi ce teachers recognition ratings: (1) eyelids flutter and (2) no recollection for what happened during the elapsed time. When a childs eyelids flutter, this behavior is highl y visible and physiological (Williams et al., 1996). When a child has no recollection of what happened during an el apsed time, it suggests that the child lost consciousness, an event that is unusual and qualitatively abnormal (i.e., no degree of unconsciousness is normal) (Williams et al., 1996). Th erefore, it is not surprising that preservice teachers provided higher ratings when these ch aracteristics were presen t. When the vignettes indicated that the hypothetical child had received a previous diagnosis of ADHD-PI, preservice teachers tended to provide lower recognition ratings The preservice teachers, it seems, assumed that the presenting sympomology was a manifestation of ADHD-PI, despite the irregularity of the symptoms. This finding is consistent with th e broader body of literature, which suggests that teachers tend to over-identify ADHD, and that they have a te ndency to overgeneralize other problematic behaviors to ADHD (Cotugno, 1993; M acey, 2005; Sciutto et al., 2000). Given that children with ADHD-PI are at increased risk for developing absence seiz ures, this finding was alarming.

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128 Question 3 Do preservice teachers differenti ate absence seizures from ADHD? Overall, preservice teachers in the current study differentiated reli ably between absence seizures and ADHD. When comparing their ratings across the vignettes, preservi ce teachers were significantly more likely to rate the childs behavi or depicted in the absence seizure vignettes as being consistent with a seizure disorder than the childs behavior depicted in the ADHD vignette (i.e., 92% vs. 1%, respectively). Moreover, whil e the majority of preservice teachers (61.7%) specified that a seizure disorder was the best explanation for the childs presenting episodes of inattention on the absence seizure vignettes, not a single preservice teacher provided this explanation on the ADHD vignette. According to th e literature, teachers re gularly misidentify a range of pediatric disorders for ADHD (Cot ugno, 1993; Macey, 2005). Therefore, preservice teachers ability to differentia te between absence seizures an d ADHD in the current study was surprising. Perhaps, preservice teachers profic iency can be explained by the fact that the vignettes depicted unambiguous, extreme cases of absence seizures and ADHD. Through examining preservice teachers respons es on the open-ended item, the researcher noted an important trend. Although absence se izures and ADHD are both medical disorders, preservice teachers seemed to delineate them accord ing to whether they differed quantitatively or qualitatively from normal behavior. More specif ically, they were more likely to perceive inattention stemming from AD HD as being a problem of degree whereas they seemed to perceive inattention stemming from abse nce seizures as being of a different type. For example, on the ADHD vignette, preservice teachers most common explanation for the childs presenting episodes of inattenti on was ADHD. However, the next most common response type reflected that Jennifer, the child depicted in the vi gnette, had a problem that was internal to her but not abnormal per se. For example, preservice teachers provided explanations

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129 such as she has difficulty paying attention, s he gets bored easily, or she has a hard time focusing. For an elementary school student, th ese behaviors are both normal and expected. Therefore, the behavior itself is not problematic, but the degree or amount that the child exhibits the behavior. Given the broader body of literatu re indicting that teachers tend to attribute problem behaviors to internal sources, or to sources within the child, the finding that 17% of preservice teachers in the current study attributed the childs inattention to external sources was surprising (Ysseldyke et al., 1983). For example, pa rticipants provided explanations such as the assignments are too boring or the work is not challenging enough, which implies that the behavior can be modified thr ough the environment. That a significant number of preservice teachers provided external or environmental explanations was encouraging, since ADHD is usually amenable to environmental intervention. Consistent with the lit erature, few preservice teachers (1.1%) attributed the chil ds behavior to a medical or physiological condition aside from ADHD (Haslam & Valletutti, 2004, p. 5). On the absence seizure vignettes, in contrast the majority of preservice teachers (61.7%) attributed the hypothetical child s episodes of inatte ntion to a seizure disorder. However, preservice teachers next most common explanation was that the childs behavior stemmed from an underlying medical or physiological problem (10.5%). A substantial number of preservice teachers (18.8%) misinterpreted the open-ended item ; rather than specifying the best explanation for the childs presenting episodes of inattention, many preservice teachers listed the details of the vignettes that caused them to rate the child s behavior as being cons istent with a seizure disorder. These responses, serendipitously, were informative. For example, they revealed that preservice teachers were partic ularly bothered by behaviors th at seemed physiological and involuntary (e.g., eyelids flutter, eyes roll bac k, smacks lips, and head drops) (Williams et al.,

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130 1996). Several preservice teachers responses sugg ested that they found it unusual that the child appeared to loose consciousness for a discrete period of time (e.g., up to 30 seconds) (Williams et al., 1996). It is not surprising, then, that on ly a small minority of preservice teachers (2.7%) attributed the problem behavior to an external source, which is good, sinc e absence seizures are not typically amenable to environmental interv ention. Very few preservice teachers incorrectly attributed the childs behavior to ADHD (2%) and even fewer indi cated that the child did not have a problem with inattenti on (0.4%). Taken together, these findings suggest that preservice teachers can differentiate between children presenting with unambiguous cases of ADHD and absence seizures and perceive them as i nvolving different type s of inattention. Question 4 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers D ifferentiation Ratings? Respondent characteristics Given that the preservice teach ers were able to differentiate between unambiguous cases of absence seizures and ADHD, the researcher identified the specific childand respondent-level characteristics that predicted preservice teachers differentiation ratings (i.e., to what extent they rated that the hypothetical childs behavior was consistent with a seizure disorder and was not consistent with ADHD). Generally speaking, an e fficacy expectation refers to having confidence that one can successfully execute a behavior to produce a desired outcome (Bandura, 1977, p. 193). Researchers hypothesize that efficacy, or confidence, affect s teachers decision-making and behavior (Macey, 2005; Reid et al., 1994). Ther efore, several types of efficacy were assessed and included as respondent-level characteristics in th e current study, and the effect they had on preservice teachers judgment and decision-maki ng was assessed. Referral efficacy, or preservice

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131 teachers confidence that they knew how to initia te a referral correctly, had a significant effect on preservice teachers differentiation ratings. Specifically, it had a ne gative effect, suggesting that the more referral efficacy a preservice teach er possessed, the worse he or she was at differentiating between the disorders. The mechanisms underlying this relationship cannot be concluded from the present study. However, a number of plausible hypotheses may be considered. First, recall that efficacy is both context and subject-matter specific and that th e appropriate level of specificity for assessing efficacy has not been established (Tschannen-Moran, 1998). For the purposes of the current study, three specific types of efficacy were a ssessed: (1) efficacy for recognizing ADHD, (2) efficacy for recognizing a seizure disorder, and (3 ) efficacy for initiating a referral. However, limiting assessment to specific types of efficacy did not preclude other types of efficacy from influencing preservice teachers ratings. For exampl e, perhaps referral efficacy is related to other types of efficacy, such as personal teaching efficacy. Studies sugge st that, among regular education teachers, higher personal teaching effi cacy predicts greater willingness to work with students who are experiencing difficulties and a reduced likelihood for initi ating a referral (i.e., to special education) (Tschanne n-Moran, 1998). Therefore, preser vice teachers in the current study with higher referral efficacy may have been more confident that they could effectively teach and manage the hypothetical children depi cted in the vignettes, and may have provided lower recognition ratings as a result (i.e., to avoid attr ibuting the behavior to a within child problem, which are often pe rceived as immutable). When considering the method used to deri ve differentiation scores, another plausible hypothesis emerges. Recall from the description a fforded in the procedures section of chapter two that differentiation scores were derived by subtracting pres ervice teachers ratings on item

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132 one, which asked them to indicate to what extent the childs presenting be havior was consistent with ADHD, from their ratings on item two, which as ked them to indicate to what extent the childs presenting behavior was consistent with a seizure disorder. Partic ipants who provided the most extreme ratings in the correct direction were assigned the highest differentiation scores. Theoretically, preservice teachers with higher refe rral efficacy should initia te referrals at higher rates. It is possible that, assumi ng they were going to refer the ch ild to a practitioner qualified to make a diagnosis, preservice teachers with highe r referral efficacy provided more moderate ratings to avoid labeling the childs behavior (i.e ., they reserved the responsibility of diagnosing the child for the qualified practitioner). Surprisingly, no other respondent characterist ics had a significant effect on preservice teachers differentiation ratings. Ag ain, preservice teachers limited variability in responding in the current study (i.e., they tende d to provide ratings on the uppe r-half of the scale) may have undermined the detection of important relationships. It is also possible that given the restricted nature of the sample (i.e., preservice teachers we re deliberately recruited at the same point in their program to control for their training), re spondent characteristics may have been too homogenous to reveal certain relationships. Mo reover, given that several of the respondent characteristics relied on self-report, variabil ity may have reflected preservice teachers interpretation of the scale rather than real di fferences (i.e., theoretically, preservice teachers should have comparable levels of referral se lf-efficacy, since they have received similar educational experiences and training). Child characteristics Although preservice teachers were able to differentiate between extrem e cases of absence seizures and ADHD consistently, only one child characteristic significantly affected their differentiation ratings: having received a previous diagnosis of ADHD-PI More specifically,

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133 having received a previous diagnosis of ADHD-PI had a negative effect on differentiation, meaning that when the characteristic was presen t in a vignette, preservice teachers provided lower differentiation ratings, or differentiated between the disord ers less accurately. This finding suggests that, although preservice te achers were able to recogn ize and differentiate between unambiguous cases of absence seizures and ADH D, their proficiency declined when the hypothetical children depicted in the vignettes presented with co-morbid disorders. This finding was not surprising given results of previous research, suggesting that teachers tend to overidentify and generalize other problematic be haviors to ADHD (Cotugno, 1993; Macey, 2005). That none of the other child characteristics had a significant effect was surprising and may suggest that preservice teachers we re attending to the whole pict ure of the child rather than specific characteristics. Question 5 What referral decisions do pr eservice teachers make for students presenting with absence seizures? The results of the current study suggest that, overwhelmingly, preservice teachers anticipate that they would initiate a referral for a child presenting with ab sence seizures. The vast majority of preservice teachers (86%) provided ratings on the top half of the scale, suggesting that they anticipated that they would initiate a referral. However, most encouraging was that preservice teachers mode response was 9, which was the highest possible rating and corresponded to being extremely likely to initiate a referral. Of th e decisions examined in this study, the researcher considered preservice teachers referral d ecision most important. Recognizing and differentiating pediatric disorders, such as absence seizures and ADHD, are important; they facilitate early and accurate di agnosis, which, logically, leads to prevention and early intervention. However, initi ating a referral when a child is suspected of having an

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134 underlying medical problem is critical. Trained professionals qualif ied to make a diagnosis are responsible for assigning a label to the child s behavior (Haslam & Valletutti, 2004). Other adults responsible for the childs well-being, such as parents and teachers, are responsible for alerting those professional s to a potential problem (H aslam & Valletutti, 2004). Question 6 What is the unique contri bution of each child characteristic (i .e., levels included in th e vignettes) and selected respondent characteri stic (i.e., knowledge, experience, efficacy, beliefs, etc.) on preservice teachers Referral Ratings? Respondent characteristics. Since preservice teachers in the current study anticipated that they would initiate a referral fo r a student presenting with abse nce seizures, the researcher identified those childand respondent-level char acteristics that predicte d their referral ratings. Beliefs about whether it is the teachers role or re sponsibility to initiate a referral when he or she suspects that a student has an underlying medical problem, a respondent characteristic included in the current study, was significant. That is, the more a preservice teacher believed that initiating a referral was part of the teache rs responsibility the more he or she anticipated that he or she would initiate a referral. This finding is partic ularly encouraging. It suggests that even with limited knowledge, experience, and efficacy preservice teachers can still be expected to initiate appropriate referrals assuming that they believe that it is their responsibility. Mean seizure disorder recognition rating ha d a significant, positive effect on referral ratings as well. That is, the hi gher a preservice teachers mean r ecognition rating the more he or she anticipated that he or she would initiate a referral. However, modeled as a cross level interaction, preservice teachers mean recognition ratings depended on frequency of contact with persons with seizure disorders and beliefs about th e teachers role (i.e., whether it is the teachers responsibility to initiate a referral when he or she susp ects that a student has an underlying

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135 medical problem). Frequency of contact with pers ons with seizure disorders had a positive effect on mean recognition ratings, which may suggest that contact with persons with seizure disorders enhances preservice teachers ability to recogni ze absence seizures. Preservice teachers beliefs about the teachers role, in contrast, predicted lo wer mean recognition ratings. That is, the more a preservice teacher believed that in itiating a referral is the teac hers responsibility, the lower recognition ratings he or she provided on average. Perhaps, preservice teachers who felt more responsible for initiating referra ls provided lower rec ognition ratings because they were more likely to initiate a referral and reserved the res ponsibility of labeling th e behavior for the person conducting the evaluation. This premise seems c onsistent with the previous finding that preservice teachers with higher referral-efficacy provided lower differentiation ratings. Question 7 Do preservice teach ers provide different referra l ratings for hypothetical children presenting with absence seizures and hypothetical children presenting with ADHD? Since preservice teachers differentiated betw een unambiguous cases of absence seizures and ADHD reliably, the researcher examined whether they provided different referral ratings for children presenting with the competing disorders. Results suggest that, while preservice teachers anticipated that they would initiate a referral fo r a child presenting with either disorder, they anticipated that they would be si gnificantly more likely to initiate a referral for a child presenting with absence seizures. Given previous research suggesting that teachers over-identify children with ADHD and under-identify children with seizure disorder s, the finding that preservice teachers anticipated that they would be more lik ely to initiate a referral for a student with absence seizures was surprising (Cotugno, 1993; Macey, 2005; Williams et al., 1996). Several theories may explain why the majority of preservice teachers in the current study anticipated that they would initiate a referral fo r a child presenting with absence seizures, while

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136 the literature suggests that few teachers par ticipate in the evaluati on process for seizure disorders. One plausible hypothesis is that, since the vignettes depicted unambiguous cases of absence seizures, they were much easier to identify than real life absence seizures. Perhaps, practicing teachers would initiate referrals for se izure disorders at rates comparable to those anticipated by preservice teach ers in the current study if real life absence seizures were as easily identifiable. Another viable explan ation is that preservice teachers provided what they perceived as the socially desirable response. That is, because they deduced that the researcher had an interest in seizure disorders and a concern for children with undi agnosed seizure disorders, they may have exaggerated their true anticipated likelihood of initiating a referral. While it remains unclear to what extent preservice teachers ratin gs in the current study generalize to real life situations, that they indicated th at they would be likely to init iate a referral is encouraging. It may suggest that, at least on some level, they believe that initiating a referral for a student suspected of having a seizure disord er is the appropriate thing to do. Practical Implications The results of this study have several im portant implications for practice. For example, although formal instruction on seizure disorder s did not improve seizure disorder-related knowledge in the current study, the literature suggests that formal instructi on is an effective and efficient mechanism for transmitting knowledge to teachers (Bishop & Boag, 2006; Macey, 2005; Sciutto et al., 2000). Therefore, the finding that only 10% of preservice teachers in the current study had received formal instruction on seizur e disorders is disconcerting. While seizure disorder-related knowledge did not predict pres ervice teachers recognition, differentiation, or referral ratings in the current study, theoretically, knowledge inform s practice (Ghanizadeh et al., 2006; Glass, 2000). To ensure that preservice te achers possess sufficient knowledge, which will allow them to engage in best practices, more formal instruction designed to convey specific,

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137 important information about seizure disorders sh ould be incorporated in to preservice teacher preparation programs (Bishop & Boag, 2006; Sciu tto & Feldhamer, 2007). Whenever possible, the instruction should focus on practical skills the teacher will be expected to display, such as recognizing a disorder, initiating an appropriate referral, and mana ging childrens behavior in the classroom. To ensure that preservice teachers mast er the material, instructors can formally assess their knowledge with tests. This t ype of direct, objectiv e feedback may allow preservice teachers to form more accurate appraisals of their level of knowledge. Although the literature suggest s that teachers often miside ntify a range of pediatric disorders for ADHD, the preservice teachers in the current study were able to recognize unambiguous cases of absence seizures and di fferentiate them from unambiguous cases of ADHD reliably (Cotugno, 1993; Macey, 2005). However, their proficiency declined when the hypothetical children presented with co-morbid di sorders (i.e., they presented with absence seizures, yet their cumulative r ecord indicated that they had received a medical diagnosis of ADHD-PI). The finding that preservi ce teachers were less likely to recognize absence seizures in children with ADHD-PI is discouraging, given that children with ADHD-PI are at increased risk for developing absence seizures. Moreover, only roughly half of preser vice teachers reported having received formal instruction on ADHD, whic h is surprising considering the prevalence of the disorder and the attention it has received in popular literature and the media. Clearly, more formal instruction on ADHD is warranted. However, while knowledge is theorized to in form better, more educated decision-making (Ghanizadeh et al., 2006; Glass, 2000), recall that greater ADHD-related knowledge predicted poorer recognition of absence seizures in the cu rrent study. This finding may suggest that a great deal of the ADHD-related information being tran smitted to teachers via formal instruction is

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138 superfluous (i.e., it will have little constructive e ffect on their practice). For example, as evidenced by preservice teachers performance on the symptoms and diagnosis subscale of the KADDS, formal instruction on ADHD usually incl udes a discussion on symptoms and diagnosis. However, out of context, this information may do little to help teacher s accurately recognize ADHD in real life. Recognizing ADHD, or any ot her pediatric disorder, may depend more on exposure to individuals with the disorder than formal instructi on. This highlights the importance of including practicum experiences as part of pr eservice teachers prep aration training (Macey, 2005) For teachers, knowledge of ADHD encompa sses knowing how to effectively teach and manage children with the disorder. Clearly, prin ciples of teaching and behavioral management can be conveyed via formal instruction; how ever, again, practicum experiences may afford preservice teachers the opportunity to master and hone these im portant skills (Macey, 2005). While ADHD is generally amenable to envir onmental intervention, su ccessful treatment frequently calls for stimulant medication, which requires a formal medical diagnosis. Formal instruction, then, should emphasize the role that teachers can play in the diagnostic process by recognizing ADHD, initiating ap propriate referrals, and by providing important, accurate information to practitioners (Sciutto & Feldha mer, 2007). To facilitate teachers ability to recognize ADHD and initiate appropriate referral s, formal instruction should move beyond understanding ADHD as a discrete disorder and should elucidat e similarities and differences among ADHD and other commonly occurring, often co-morbid pediatric disorders. Preservice teachers must understand that pediatric disorder s are not mutually exclusive, and should be taught to explore numerous causes for children attention difficulties. Ther efore, perhaps formal instruction on ADHD provided to preservice teache rs in preservice teacher preparation programs should prioritize conveyi ng practical skills over scholastic-type knowledge?

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139 Of the constructs assessed, the researcher c onsidered preservice teac hers referral decision most important. Medical disorders, such as ab sence seizures and ADHD, affect children in a variety of ways, especially at school. Fortunately, with early and accurate diagnosis, the longterm sequelae of many pediatric di sorders can be redirected and, in the best of cases, prevented entirely. Teachers are often in the best position to recognize deviations in behavior due to both their understanding of what is developmentally no rmal and the sheer amount of time they spend with students (Gresham, 2004; Sciutto et al., 2000). Therefore, teachers should be encouraged to participate actively in the diagnostic and evaluation process, na mely, by initiating appropriate referrals (Haslam & Valletutti, 2004). Preservice teachers in the current study anticipated that they would initiate a referral for a student presenting with absence seizures, which is encouraging, given that the literature implies that by and large, teachers do not participate in the diagnostic and evaluation process. Although the resu lts of the current stud y are hypothetical (i.e., whether preservice teachers would actually initiate a referral re mains unknown), they may suggest that preservice teachers be lieve that initiating a referral is the appropriate thing to do. Perhaps the most encouraging finding in the cu rrent study is that beli efs about the teachers role or responsibility (i.e., to initiate a refe rral when he or she suspects that a student has an underlying medical problem) predic ted referral ratings This finding suggest s that even with limited knowledge, experience, and efficacy, preservice teachers can still be expected to initiate appropriate referrals assuming they believe that it is their respons ibility. Therefore, if increasing teachers referral likelihood is the ultimate goal, then preservice teacher preparation programs should allocate more time to clarifying the teach ers role and responsibilities. Principally, the instruction could emphasize the benefits of accurate medical diagnoses and provide preservice teachers with guidelines for initia ting appropriate referrals. Howeve r, the instruction could also

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140 outline steps that preservice teachers can take when a students presenting behaviors seem inconsistent with an existing diagnosis (e.g., the child has received a diagnosis of ADHD-PI but seems to loose consciousness during his or her ep isodes of inattention). Finally, the instruction could inform preservice teachers that, even wh en a student is exhibi ting behaviors that are consistent with an existing diagnosis and thos e behaviors are interfer ing with his or her functioning at school, it may still be appropriate for a teacher to initiate a referral, given that the students treatment regimen may not be working effectively. Often, the teacher is in the best position to note the effectiveness of treatment, especially for sub tle behaviors like inattention. An important, unexpected trend that emerged in the current study is that the more a preservice teacher anticipated that he or she would initiate a referra l, the less likely he or she was to label the childs behavior. Theoretically, referral efficacy and beliefs about the teachers role/responsibility to in itiate a referral are positively a ssociated with referral likelihood. Surprisingly, preservice teacher s in the current study possessing higher referral efficacy and stronger beliefs about the teachers role/responsibility provided lower, less extreme recognition ratings. Therefore, it seems that the more they antic ipated initiating a referral, the less likely they were to conclude that the child depicted in the vignette possessed a seizure disorder. Given teachers job function and traini ng (i.e., they are not responsible for or qualified to make a medical diagnosis), this tendency is sensible. Th ey, presumably, reserved the responsibility of labeling the childs behavior for a professional qualified to make a diagnosis. That preservice teachers understand that they can facilitate an accurate diagnosis (i.e., by initiating appropriate referrals and providing professionals with important information) but that they do not have the authority to suggest or imply diagnoses is critical. To avoi d over-stepping this important boundary, preservice teachers should be taught to integrate informa tion about the childs

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141 presenting behavior into a written report that describes the presen ting concerns in detail and in behavioral terms. The report can then be provided a professional who is qualified to interpret the information and to assign a label to the behaviors (e.g., ADH D or seizures). Limitations While this study contributed to the existing literature, a num ber of im portant limitations must be considered. First, recruiting preservice teachers from the UEP may have limited the generalizability of the findings, since, unlike most preservice teacher preparation programs, the UEP prepares preservice teachers to work in elem entary education and with students with mild disabilities. Therefore, results may not generalize to preservice teachers in different preparation programs or to preservice teachers in general. Additionally, for the purposes of the current study, all preservice teachers were recruited at the same point in their program. While restricting the sample eliminated the need to control for numerous variables relating to participants training and experience, it also limited the generalizability of the findings. That is, results of the current study only apply to preservice teachers in their eighth semester of the UEP, or to preservice teacher s graduating with their B.A.E. Restricting the sample may have had other un intended consequences as well. For example, the homogeneity of the sample may explain why several respondent charact eristics demonstrated to affect decision-making did not have a sign ificant effect in the current study. That is, by receiving roughly the same instruction, participan ts demonstrated little variability on respondent characteristics, which may have diluted the stre ngth of the relationships measured between the respondent characteristics and the dependent variables. Given that the sample of participants was predominately female and White/Causasion, the results mat not generalize to male preservice teache rs or preservice teache rs of other ethnicities.

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142 Notably, however, most teachers are White and Cau casion; thus, the results are generalizable to the general teaching population. Additionally, give n the relatively large number of childand respondentlevel characteristics be ing investigated in the current study and that effect sizes were smaller than expected, a larger sample size may have revealed more re lationships by increasing statistical power and reducing the chances of a Type II error. Participants ratings on the vignette instrument were based on descriptions of hypothetical children rather than actua l children. Although the factorial surv ey research design is posited to have good external validity, in that participants decisions closely resemble those in daily life, whether participants would have made the same decisions in real life scenarios remains unknown. To control for extraneous factors, many child characteristics were identical across the vignettes or were held constant For example, among a number of other variables, participants were informed that all of the hypothetical children were female and in the third grade. As a result, preservice teachers decisions in the curre nt study can only be generalized to children with similar characteristics. For the purposes of the current study, three specific types of efficacy were assessed: (1) efficacy for recognizing ADHD, (2) efficacy for r ecognizing a seizure disorder, and (3) efficacy for initiating a referral. Unfortunately, no standard exists clar ifying the appropriate level of specificity for assessing efficacy. The results of the current study may suggest that other, broader types of efficacy that were not included as i ndependent variables were influencing preservice teachers ratings. A significant number of preservice teachers fa iled to respond to or misunderstood the open-ended item on the vignette instrument. Wh ile missing data did not cause significant

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143 nonresponse error (i.e., the respondents that did not respond to the item did not differ significantly from the respondents who did res pond to the item on one or more important variables), participants misinter pretation of the question did resu lt in significant measurement error (i.e., respondents answers could not be compared in any useful way) (Dillman, 2000). For the purposes of the current study, the res earcher designed the vignette instrument so that the words seizure disorder appeared in a question stem of item two. Clearly, this may have enhanced preservice teachers performance on ite m three, which was the open-ended item asking them to specify the best explanation for the chil ds presenting episodes on inattention. Therefore, the finding that the majority of preservice teachers correctly specified that a seizure disorder was the best explanation for the childs presenting episodes of inattention may not generalize to vignettes that do not contain this type of cue or to real life situations. A final limitation relating to the vignette in strument was that the vignettes depicted unambiguous, or extreme, cases of ADHD and ab sence seizures (i.e., many indicators were present in each of the vigne ttes). In real life children co mmonly display some but not all indicators of a disorder. Therefore, recognizing absence seizures on the vignette instrument was, in all likelihood, much easier than recognizing absence seizur es in real life. As a result, preservice teachers decisions in the current study may not generalize to real life situations, or to situations in which they are provided w ith incomplete or ambiguous information. Implications for Future Research The results of the current st udy suggest that both childand respondentlevel variables affect preservice teachers abil ity to recognize ab sence seizures and differentiate them from ADHD, and, surprisingly, that only respondent-lev el characteristics aff ect their anticipated referral likelihood. Additional exploration of thes e relationships should be conducted to provide further support of these relations hips. Several studies suggest that child de mographic variables,

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144 such as gender and SES, affect teachers decisi ons (e.g., their decision to initiate a referral for special education) (Podell & Soodak, 1993; Tsch annen-Moran, 1998). Therefore, to extend the current study, child demographic variables may be in cluded as child-level i ndependent variables. Since relationships between respondent charact eristics and outcome decisions may have been diluted due to the homogeneity of the samp le, the study could be replicated using a more diverse, representative sample (e .g., by recruiting preservice teacher s at all stages of training). This would have the added benefit of im proving the generalizability of the findings. Additionally, given the importance th at all teachers (i.e., preservice and practicing) are prepared to recognize pediatric disorders and initiate appropriate referrals, it may be interesting to replicate the study using practicing teachers. A positive consequen ce of using practicing teachers is that it would, without doubt, l ead to greater variability in respondent characteristics (i.e., knowledge, experience, and efficacy). Perhaps, mo re relationships between respondent variables and outcome decisions would emerge as a result. Clearly, for a number of reasons, the results of the current investiga tion may not generalize to real life situations. It may be interesting, then, to explore whether preservice and practicing teachers recognize, differentiate, and initiate appropr iate referrals for actual students with seizure disorders. Additionally, while the literature sugg ests that teachers do not initiate referrals for students presenting with absence seizures, this s upposition has not been investigated directly or substantiated by data. Identifying how often teachers initiate re ferrals for students presenting with seizure disorders and to what extent they participate in the diagnostic and evaluation process may be extremely informative. Finally, while the literature suggests that misdiagnosis of absence seizures for ADHD is a common occurrence, estimates of the incidence are not readily available.

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145 Surprisingly, although preservice te achers in the current study were able to differentiate reliably between unambiguous cases of ab sence seizures and ADHD, only one childcharacteristic, previous diagnosis of ADHD-PI, had a significant effect on differentiation. This may suggest that preservice teachers were attending to the whole picture of the child rather than specific child characteristics. Temperament, which concerns the way (authors emphasis) in which an individual behaves, may explain this tendency (Thomas & Chess, 1977), especially the sensing-intuitive continuum. I ndividuals who prefer sensing fo cus mainly on the five senses. Individuals who prefer intuition, in contrast, focus on patterns or interrelationships (Myers & McCaulley, 1985). These preferences affect both what individuals attend to and how they perceive (Myers & McCaulley, 1985). Preservice t eachers in the current study seemed to prefer intuition, or to focus on the big picture. Sin ce preservice teachers temperament may have influenced their outcome decisions, it may be interesting to extend the study by including temperament as a respondent-level characteristic. Research suggests that efficacy, or confidence that one can successfully execute a behavior to produce a desired outcome, influences teach ers decision-making and behavior (Macey, 2005; Reid et al., 1994). Researchers have yet to dete rmine the appropriate level of specificity for measuring efficacy and, as a result, researchers wishing to investigate efficacy must rely on their judgment (Tschannen-Moran, 1998). For the purposes of the current study, three specific types of efficacy were assessed: (1) efficacy for recognizing ADHD, (2) efficacy for recognizing a seizure disorder, and (3) efficacy for initiati ng a referral. However, limiting assessment to specific types of efficacy did not preclude other types of efficacy from influencing preservice teachers decisions. For future extensions and rep lications of this study, it may be interesting to assess additional types of efficacy, such as pers onal teaching efficacy or efficacy for classroom

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146 management. Assessing broader type s of efficacy provides the resear cher with the added benefit of being able to utilize existing efficacy measures. Preservice teachers demonstrated limited va riability in responding on the dependent variables in the current study. Specifically, they tended to provide ratings on the upper-end of the Likert-type scales. Given that the goal was to detect va riability in respondi ng, this tendency may suggest that the vignettes were t oo easy. Since this study represente d the first systematic attempt to learn about preservice teachers and absence seizures, all of the vignettes depicted unambiguous, or extreme, cases of absence seizures and ADHD (i.e., many indicators were present in each of the vignettes). However, upon subsequent administrations of the vignette instrument, it may be beneficial to include a null level for each dimension. The null level would cause the dimension to be left blank in some vignettes, or stated differently, would systematically create incomplete vignettes. The incomplete vignettes should mirror real-life absence seizures more closely and, because they would be more difficult, should increase variability in responding. This would also allow the researcher to ascertain the effect of a dimension on a decision of interest. A significant number of preservice teachers failed to respond to or misinterpreted the openended item on the vignette instrument. To enhance participants comprehension of the question and their motivation for completing the item, the open-ended item could be moved to the beginning of the vignette instrument (Dillman, 2000) The item may also be transformed into a closed-ended item (Dillman, 2000). The response categories used for the closed-ended item could be based on the results of this preliminary study (Dillman, 2000). Finally, the study could be repl icated using participants other than current and future teachers. For example, teachers often refer students suspected of having problems with

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147 inattention to the school psychologist. School psyc hologists receive little, if any, instruction on the recognition of neurological disorders. In genera l, they tend to have time-limited interactions with students, which is particularly problematic for recognizing episodic disorders like epilepsy. Taken together, these facts may suggest that sc hool psychologists are un prepared to recognize pediatric disorders and to display good decisi on-making by initiating an appropriate referral (Wodrich et al., 2006).

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148 APPENDIX A INSTRUCTOR INVITATION LETTER Dear PROTEACH Instructor, My name is Nicole Nasewicz and I am a doctoral candidate in school psychology at the University of Florida. As part of my graduate research, I would like to invite your PROTEACH students to participate in a re search study that I am conducting, exploring whether preservice teachers can differentiate between qualitatively di fferent forms of inattention. The study will also explore whether case characteristics or responde nt characteristics predict classification accuracy. Participating students will be asked to complete a couple of questionnaires. First, they will be asked to read six vignettes about hypothetical children. After reading each vignette, they will be asked to respond to a series of questi ons about the child presented. Second, they will be asked to complete a questionnaire that will provide me with information about their background and experiences (for example, whether they have completed a formal internship). These questionnaires should take 20 minutes or less to complete. I am inviting all PROTEACH preservice teacher s in your class to part icipate; they were selected to participate in this study based on their status as PROTEA CH preservice teachers. There is no risk to your students. They are free to withdraw thei r permission for participation at any time without consequence. Each participa ting student will be assigned a confidential number. Their names will not be revealed to anyo ne, with the exception of my advisor and I, or appear in any written work. I f you give your permission for me to collec t data from your students, please email me at nicolecn@ufl.edu to discuss logistics (i.e., what day and time to come to you r class). Also, please complete the bottom half of this form and mail it to me, Nicole Nasewicz, at 3724 NW 26th st Gainesville, Fl 32605. If you have any questions, please do not hesitate to contact me at (941)545-8812 or by email at nicol ecn@ufl.edu, or to contact my supervisor, Tina Smith-Bonahue, at (352)392-0273. Questions or con cerns about human participants rights may be directed to the University of Florida Inst itutional Review Board (U FIRB) office at PO Box 112250 Gainesville, Fl 32611 or (352)392-0433. Thank you in advance for your support. Sincerely, Nicole Nasewicz Please read the above description and return the bottom portion I, ________________________________, give the researcher permission to collect data on preservice teachers in my class. Phone: Email: Do you prefer that I contact you through email or by telephone? At what location is your PROTEACH seminar held? ___________________________________ On what days and time is your PROTEACH seminar held? ______________________________

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149 APPENDIX B INFORMED CONSENT Protocol Title: Can Preservice Teachers Differentiate Atten tion Deficit Hyperactivity Disorder from Seizure Disorders? Please read this consent document carefully before you decide to participate in this study. Purpose of the research study: The purpose of this study is to assess whether preservi ce teachers differentiate Atte ntion Deficit Hyperactivity Disorder from Seizure Disorders, and to explore the factors that affect their decision to make a referral. This information can be used in future research, and for making recommendations for programmatic changes to preservice teacher preparation programs. What you will be asked to do in the study: If you participate in this study, you will be asked to complete several instruments. You will be asked to answer questions that correspond to vignettes about hypothetical children, to complete an instrument pertaining to ADHD and an instrument pertaining to epilepsy, a nd to complete a teacher information survey. Time required: 40 minutes Risks and Benefits: This study involves very few discomfort s or risks. You will be asked to answer questions that require some thinking. Some of the questions may be challenging for you to answer or you may have emotional feelings towards some of the questions. You will not necessarily benefit directly by participating in this experiment. Compensation: No compensation is offered for participation in this study. Confidentiality: Your confidentiality will be kept confidential to the extent provided by law. You will not be asked to put your name anywhere on the study materials. Therefore, your name will not, and cannot, be linked to any of your responses. Your name will not be used in any report. Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from the study at anytime without consequence.

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150Whom to contact if you have questions about the study: Nicole Nasewicz, B.S., Graduate Student, Department of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Tina Smith-Bonahue, Ph.D., Associate Professor, Department of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Whom to contact about your rights as a research participant in the study: UFIRB Office, Box 112250, University of Flor ida, Gainesville, FL 32611-2250; ph 392-0433. Agreement: I have read the procedure described abov e. I voluntarily agree to participate in the procedure and I have received a copy of this description. Participant: ___________________________________________ Date: _________________ Principal Investigator: ___________________________________ Date: _________________

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151 APPENDIX C SAMPLE VIGNETTE INSTRUMENT Research Vignettes Assum e you are an elementary school teacher in a medium-sized school district. The school is located in a lower-middle class neighbor hood and has approximately 500 students in Kindergarten through grade five. You will be asked to answer questions about case descriptions that briefly describe six children. For each case, you should assume that you are the childs teacher and that it is the end of the third nine -week grading period. Each of the six children has cer tain characteristics in common. They are all Caucasian females in the third grade. Academically, they are struggling and are described as absent-minded, sluggish, and day-dreamy. Specifically, each of the children has difficulty, to some extent, paying attention, concentrating, remembering daily activitie s, listening when spoken to, and following through on instructions in class. Recently, each of the children were referred to and evaluated by the child-study team at your school None of them met e ducational criteria for Specific Learning Disability (S LD); both their general cogni tive ability and academic achievement fell within age a nd grade level expectations. Please read each case and answer the questions based on the information presented. Each case has the same basic structure, but the details will vary. Please consider each child separately. Remember to respond to the questions from the perspective of a teacher, not an intern.

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152 Jennifer Jennifer exp eriences predictable episodes of inatte ntion that occur, on average, several times a day. The episodes occur in many academic situations, especially those that require sustained attention and concentration. Typi cally, the episodes begin gradua lly; she first grows bored or uninterested in the assignment or task at hand. During the epis odes, she stares blankly and fidgets in her seat. The episodes last, in general, until something interesting happens. Notably, Jennifer responds reliably to redirection and startles easily. After the episode s, she is alert, but she is reluctant to resume the assignment or task and tends to procrastinate. Regarding her schoolwork, Jennifer is distracted easily by extraneous stimuli and, as a result, is almost always off-task. She seldom comple tes her homework assignments. Her cumulative record documents a pervasive and longstanding history of attenti on and concentration problems. A behavioral rating scale, completed by one of her parents for her most recent school-based evaluation, suggests that he r inattention falls in the severe, or clinically significant, classification range Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. Fo r items one, two, and f our, please use the corresponding rating scales by circling th e appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to make a referral for this child? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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153 Katie Katie experiences occasional episodes of inattent ion that occu r, on average, several times a week. The episodes occur most in academically challenging situations. Typically, the episodes begin gradually; she grows uninterested in th e task and will gaze around the room. During the episodes, she stares blankly a nd taps her foot repetitively on the floor. The episodes last, in general, until something interesting happens. No tably, Katie responds reliably to redirection. After the episodes, she is alert, but she will avoid resuming the assignment or task. Regarding her schoolwork, Katie is often off-task. She sometimes completes her homework assignments. Her cumulative record indicates th at she began to experience problems with attention and concentration in the second grade, around the same time she began to struggle academically. A behavioral rating scale, completed by one of her parents for her most recent school-based evaluation, suggests that her inat tention falls in the moderate, or at-risk, classification range. Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. For items one, two, and four, please use the corresponding rating scales by circling the appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to make a referral for this child? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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154 Anne Anne experiences regular episodes of inattenti on that occur, in general, on most days. The episodes occur m ost when she is tired a nd while completing task s that are monotonous. Typically, the episodes begin abruptly; she will gr ow sluggish and begin to mumble or slur her words. During the episodes, she stares blankly. The episodes last up to one minute and usually end abruptly. Notably, Anne responds to redirect ion but only after loud and repeated attempts. After the episodes, she is alert, and she usually in dicates that the task is boring or that she is tired. Regarding her schoolwork, Anne is sometimes off-task. She usually completes her homework assignments. Her cumulative record does not prov ide any indication that she has had difficulty with attention or concen tration in the past. A behavioral ra ting scale, completed by one of her parents for her most recent school-based evaluation, suggests that her inattention falls in the moderate, or at-risk, classification range. Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. For items one, two, and four, please use the corresponding rating scales by circling the appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to make a referral for this child? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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155 Julie Julie experiences frequent episodes of inattenti on that occur, on average, 10 to 12 tim es a day. The episodes occur most during physical activity. Typically, the episodes begin abruptly; she stops talking suddenly, mid-sentence. During the epis odes, Julie stares blankly and her eyes role upward. The episodes end abruptly and last, on av erage, up to 30 seconds. Notably, Julie does not respond reliably to physical redirection. After the episodes, she is alert, but she has no recollection of what happened during the elapsed time. Regarding her schoolwork, Julie is seldom off-ta sk while completing assignments and activities. Her cumulative record documents a pattern of problems with inattention that began suddenly in the first grade. A behavioral rating scale, comp leted by one of her parents for her most recent school-based evaluation, suggests that her inat tention falls in the normal, or average, classification range. Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. Fo r items one, two, and f our, please use the corresponding rating scales by circling th e appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to make a referral for this child? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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156 Kelly Kelly experiences cons ecutive episodes of inat tention that occur, s eemingly, continuously throughout the day. The episodes occur in all s ituations, even during play. Typically, the episodes begin abruptly; she stops walking sudde nly, standing nearly motionless. During the episodes, Kelly stares blankly and her eyelids flutter. The episodes end abruptly and last, on average, up to one minute. Notably, Kelly does no t respond reliably to physical redirection. After the episodes, she is alert, but she has no recoll ection of what happened during the elapsed time. Regarding her schoolwork, Kelly is seldom off-task while completing assignments and activities. Her cumulative record documents that she has received a medical diagnosis of ADHD-Primarily Inattentive Subtype. A behavioral rating scale, completed by one of her parents for her most recent school-based evaluation, suggests that her inattention falls in the moderate, or at-risk, classification range. Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. Fo r items one, two, and f our, please use the corresponding rating scales by circling th e appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to make a referral for this child? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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157 Tracy Tracy experiences frequent episod es of inattention that occur, on average, 10 to 12 times a day. The episodes occur in all situat ions, even during play. Typica lly, the episodes begin abruptly; she stops walking suddenly, standing nearly mo tionless. During the episodes, Tracy stares blankly and her head drops slightly. The episodes end abruptly and last, on average, up to one minute. Notably, Tracy does not respond reliably to physical redirection. After the episodes, she is alert, but she has no recollection of what happened during the elapsed time. Regarding her schoolwork, Tracy is seldom off-task while completing assignments and activities. Her cumulative record provides no indication that she has had difficulty with attention or concentration in the past. A behavioral rating scale, comple ted by one of her parents for her most recent school-based evaluation, suggests that her inattention falls in the moderate, or atrisk, classification range. Remembering the attributes common to all the children (i.e., Caucasian female, absent-minded, sluggish, day-dreamy, etc.), that it is the end of the third 9-week gradi ng period, and that you are the childs teacher, please provide your profe ssional judgment about the child described above by responding to the following questions. Fo r items one, two, and f our, please use the corresponding rating scales by circling th e appropriate number for each item. 1. To what extent is this childs behavior co nsistent with Attention Deficit Hyperactivity Disorder (ADHD)? Definitely Not Definitely ADHD ADHD 1 2 3 4 5 6 7 8 9 2. To what extent is this childs behavior consistent with a seizure disorder? Definitely Not a Definitely a Seizure Disorder Seizure Disorder 1 2 3 4 5 6 7 8 9 3. What is the best explanation for this ch ilds presenting episodes of inattention? _________________________________________________________________________ 4. How likely are you to refer this child for an evaluation? Not At All Extremely Likely Likely 1 2 3 4 5 6 7 8 9

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158 APPENDIX D PROTEACH DEMOGRAPHIC INFORMATION SURVEY 1. What is you r age? ____________ 2. What is your sex? (check one) ______ Female ______ Male 3. What is your ethnicity? (check one) ______ Non-Hispanic, White ______ African American ______ Hispanic ______ Asian ______ Multiracial ______ Other (please specify)_________________________________________ 4. Which best describes the setting in whic h you intend to teach? (check one) ______ Regular Education ______ Special Education 5. Which best describes the degree and certif ication you are seeking? (check one) ______ Bachelors Degree No certification ______ Masters Degree Single Certification ______ Masters DegreeDual Certification 6. Have you received formal instruction on ADHD (e.g., coursework, in-service, seminar, etc.)? (check one) ______ Yes (please describe) ___________________________________________ ______ No 7. Have you received formal instruction on seizure disorders (e.g., coursework, inservice, seminar, etc.)? (check one) ______ Yes (please describe) ___________________________________________ ______ No 8. Have you received formal instruction on how to initiate a referral (check one) ______ Yes (please describe) ___________________________________________ ______ No 9. Please rate your general knowledge of ADHD: No Knowledge Extensive Knowledge 1 2 3 4 5 6

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159 10. How would you describe your frequency of contact with persons with ADHD? Very Infrequent Very Frequent 1 2 3 4 5 6 11. How confident are you that you can accurately identify ADHD? Not at all Extremely Confident Confident 1 2 3 4 5 6 12. Please rate your general knowledge of seizure disorders: No Knowledge Extensive Knowledge 1 2 3 4 5 6 13. How would you describe your frequency of contact with persons with a seizure disorder? Very Infrequent Very Frequent 1 2 3 4 5 6 14. How confident are you that you can a ccurately identify a seizure disorder? Not at all Extremely Confident Confident 1 2 3 4 5 6 15. How confident are you that you know how to initiate a referral correctly? Not at all Extremely Confident Confident 1 2 3 4 5 6 16. To what extent do you believe that it is a teachers role or respo nsibility to initiate a referral when a student is suspected of having an underlying medical disorder? Definitely not Definitely Responsibility Responsibility 1 2 3 4 5 6 Thank you for participating!!!

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160 APPENDIX E UNIFIED ELEMENTARY PROTEACH PROGRAM CORE REQUIREMENTS Table E-1. Unified Elem entary Program (UEP ) core curriculum and field experiences Semester Course prefix Course title Field component 5 Fall 2006 EDF 3115 Child Development for Inclusive Education Mentoring EEX 3070 Teachers and Learners in Inclusive Schools SDS 3430 Family and Community Involvement in Education LAE 3005 Childrens Literature in Childhood Education 6 Spring 2007 EEX 3257 Core Teaching St rategies Integrated into EEX 3257, EEC 3706, and EEX 3616 EEX 3616 Core Classroom Management Strategies RED 3307 Teaching Reading in the Primary Grades LAE 4314 Language Arts for Diverse Learners 7 Fall 2007 SCE 4310 Elementary Science Methods for the Inclusive Classroom Placement integrating Math/Science/Technology experience; Placement for TSL 3526 MAE 4310 Teaching Mathematics in the Inclusive Elementary Classroom TSL 3526 ESOL: Language and Culture EME 4401 Integrating Technology in the Classroom 8 Spring 2008 RED 4324 Reading Intermediate Grades EDE 4942 (Monday Friday, 7:30 to 11:30) EEX 4905 Integrated Teaching Seminar SSE 4312 Social Studies for Diverse Learners EDE 4942 Integrated Teaching in Elementary Education Note. Students have already fulfilled four semesters, or 60 credit hours, of general undergraduate coursework.

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161 APPENDIX F INSTRUCTION ON ADHD AND ABSENCE SEIZURES Table F-1. Instruction on ADHD and seizure disord ers provided in Unified Elem entary Program (UEP) core courses Course Prefix Title Instructor description Test items EDF 3115 Child Development for Inclusive Education Discuss accommodations for students with ADHD No discussion on seizure disorders ADHD: 1 case study pertaining to accommodations SD: none EEX 3070 Teachers and Learners in Inclusive Schools Special Education law is covered. ADHD is included in discussion. Seizure disorders are not discussed specifically None EEX 3257 Core Teaching Strategies ADHD nor seizure disorders are discussed specifically None EEX 3616 Core Classroom Management Strategies Neither ADHD nor seizure disorders are discussed specifically Classroom management techniques for students demonstrating behaviors consistent with ADHD (e.g., impulsivity and hyperactivity) are discussed. None HSC 3301 Health Science Education in Elementary ADHD is not discussed in great length None Note. SD = seizure disorder. HSC 3301, Health Science Educatio n in Elementary, is not a core course in the UEP. Instead, the course was included beca use, traditionally, health conditions, such as seizure disorders, are covered. Chart may not include all instruction preservice teachers received on ADHD and seizure disorders, since some instructors failed to respond to the researcher via email.

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162 APPENDIX G COGNITIVE INTERVIEWS INFORMED CONSENT Protocol Title: Ass essing Preservice Teachers A ccuracy at Differentiating Between Qualitatively Different Forms of Inattention Please read this consent document carefully befo re you decide to partic ipate in this study. Purpose of the research study: The purpose of this study is to assess sources of response error in a questionnaire measuring preservice teachers ability to di fferentiate between qualitatively different forms of inattention. More specifically, the questi onnaire will provide the resear chers with information about preservice teachers accuracy at classifying st udents with Attention Deficit Hyperactivity Disorder-Primarily Inattentive Subtype and the factors that affect th eir decision to make a medical referral. This information can be used in future research, and eventually, can be used to facilitate teachers understanding of organic causes of inattention. Ul timately, it is hoped that the information may serve to help prevent and re mediate the problems common to children with organic bases of inattention at school. What you will be asked to do in the study: If you participate in this study, you will be asked to read six case descriptions about hypothetical children. After each case, you will be asked to respond to a few questions about the child presented. Afterward, you will be asked to partic ipate in a focus group meeting, during which we will discuss the vignettes and the questionnaires. Time required: 1 hour. Reading the cases and answering the ques tions should take approximately 30 minutes. The focus group meeting will take approximately 30 minutes. Risks and Benefits: This study involves very few discom forts or risks. You will be asked to answer questions that require some thinking. Some of the questions may be challenging for you to answer or you may have emotional feelings towards some of the questions. You will not necessarily benefit di rectly by participating in this experiment. However, I would be happy to provide you with a summary of the research results when the study is completed (upon request). Compensation: You will be provided with a $ 25.00 gift certificate for par ticipating in this study.

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163 Confidentiality: Your confidentiality will be kept confidential to the extent provided by law. Your information will be assigned a code number. The list connecti ng your name to this number will be kept in a locked file in my office. When the study is comp leted and the data have been analyzed, the list will be destroyed. Your name will not be used in any report. Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from th e study at anytime without consequence. Whom to contact if you have questions about the study: Nicole Nasewicz, B.S., Graduate Student, Depa rtment of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Tina Smith-Bonahue, Ph.D., Associate Professor, Department of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Whom to contact about your rights as a research participant in the study: UFIRB Office, Box 112250, University of Florida, Gainesville, FL 32611-2250; ph 392-0433. Agreement: I have read the procedure described above. I volunt arily agree to pa rticipate in the procedure and I have received a copy of this description. Participant: ___________________________________________ Date: _________________ Principal Investigat or: ___________________________________ Date: _________________

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164 APPENDIX H PILOT STUDY CONSENT FORM Protocol Title: Ass essing Whether Preservice Teachers Ca n Differentiate Between Qualitatively Different Forms of Inattention. Please read this consent document carefully before you decide to partic ipate in this study. Purpose of the research study: The purpose of this study is to assess the accura cy and consistency of a questionnaire measuring preservice teachers accuracy at differentiati ng between qualitatively different forms of inattention, more specifically, thei r ability to accurately identi fy Attention Deficit DisorderPrimarily Inattentive Subtype. This information can be used in future research, and eventually, can be used to facilitate t eachers understanding of ADHD-PI, which may serve to remediate many of the problems common to children with ADHD-PI at school. What you will be asked to do in the study: If you participate in this study, you will be asked to complete a teacher information survey, which provides the researchers with important demographic information, and to respond to questions that correspond with si x vignettes of hypothe tical children. Time required: 20 minutes Risks and Benefits: This study involves very few discom forts or risks. You will be asked to answer questions that require some thinking. Some of the questions may be challenging for you to answer or you may have emotional feelings towards some of the questions. You will not necessarily benefit di rectly by participating in this experiment. Your professor may elect to give you extra cred it points towards your grade in his/her class if you elect to participate. Compensation: No compensation is offered for participation in this study. Confidentiality: Your confidentiality will be kept confidential to the extent provided by law. Your information will be assigned a code number. The list connecti ng your name to this number will be kept in a locked file in my office. When the study is comp leted and the data have been analyzed, the list will be destroyed. Your name will not be used in any report.

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165 Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from th e study at anytime without consequence. Whom to contact if you have questions about the study: Nicole Nasewicz, B.S., Graduate Student, Depa rtment of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Tina Smith-Bonahue, Ph.D., Associate Professor, Department of Educational Psychology, 1403 Norman Hall, P.O. Box 117047, Gainesville, FL 32611 (352) 334-1713 Whom to contact about your rights as a research participant in the study: UFIRB Office, Box 112250, University of Florida, Gainesville, FL 32611-2250; ph 392-0433. Agreement: I have read the procedure described above. I volunt arily agree to pa rticipate in the procedure and I have received a copy of this description. Participant: ___________________________________________ Date: _________________ Principal Investigat or: ___________________________________ Date: _________________

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166 APPENDIX I KADDS INSTRUMENT Please answer the fo llowing questions regarding Attention-Deficit/Hyperactivity Disorders (ADHD). If you are unsure of an answer, respond Don't Know (DK), DO NOT GUESS. True (T), False (F), or Do n't Know (DK) (circle one): 1. T F DK Most estimates suggest that ADHD occurs in approximately 15% of school age children. 2. T F DK Current research suggests that ADHD is largely the result of ineffective parenting skills. 3. T F DK ADHD children are frequen tly distracted by extr aneous stimuli. 4. T F DK ADHD children are typically mo re compliant with their fathers than with their mothers. 5. T F DK In order to be diagnosed with ADH D, the child's symptoms mu st have been present before age 7. 6. T F DK ADHD is more common in the 1s t degree biological relatives (i.e. mother, father) of children with ADHD than in the general population. 7. T F DK One symptom of ADHD children is that they have been physically cruel to other people. 8. T F DK Antidepressant drugs have b een effective in reducing symptoms for many ADHD children. 9. T F DK ADHD children often fidget or squirm in their seats. 10. T F DK Parent and teacher training in managing an ADHD child are generally effective when combined with medication treatment. 11. T F DK It is common for ADHD children to have an inflated sense of self-esteem or grandiosity. 12. T F DK When treatment of an ADHD child is terminated, it is rare for the child's symptoms to return. 13. T F DK It is possible for an adult to be diagnosed with ADHD. 14. T F DK ADHD children often have a history of stealing or destroying other people's things

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167 15. T F DK Side effects of stimulant drugs used for treatment of ADHD may include mild insomnia and appetite reduction. 16. T F DK Current wisdom about ADHD suggests two clusters of symptoms: One of inattention and another consisting of hyperactivity/impulsivity. 17. T F DK Symptoms of depression are found more frequently in ADHD children than in nonADHD children. 18. T F DK Individual psychotherapy is us ually sufficient for the treatment of most ADHD children. 19. T F DK Most ADHD children "outgrow" their symptoms by the onset of puberty and subsequently function normally in adulthood. 20. T F DK In severe cases of ADHD, medi cation is often used before other behavior modification techniques are attempted. 21. T F DK In order to be diagnosed as ADHD, a child must exhibit relevant symptoms in two or more settings (e.g., home, school). 22. T F DK If an ADHD child is able to dem onstrate sustained attention to video games or TV for over an hour, that child is also able to sustain attention for at least an hour of class or homework. 23. T F DK Reducing dietary intake of suga r or food additives is generally effective in reducing the symptoms of ADHD. 24. T F DK A diagnosis of ADHD by itself ma kes a child eligible fo r placement in special education. 25. T F DK Stimulant drugs are the most co mmon type of drug used to treat children with ADHD 26. T F DK ADHD children often have di fficulties organizing ta sks and activities. 27. T F DK ADHD children generally experi ence more problems in novel situations than in familiar situations. 28. T F DK There are specific physical features which can be identifi ed by medical doctors (e.g. pediatrician) in making a definitive diagnosis of ADHD. 29. T F DK In school age children, the prevalence of AD HD in males and females is equivalent. 30. T F DK In very young children (less than 4 years old), the probl em behaviors of ADHD

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168 children (e.g. hyperactivity, inattention) are distinctly different from age-appropriate behaviors of non-ADHD children. 31. T F DK Children with ADHD are more distingui shable from normal children in a classroom setting than in a free play situation. 32. T F DK The majority of ADHD children ev idence some degree of poor school performance in the elementary school years. 33. T F DK Symptoms of ADHD are ofte n seen in non-ADHD children who come from inadequate and chaotic home environments. 34. T F DK Behavioral/Psychological interventions for children with ADHD focus primarily on the child's problems with inattention. 35. T F DK Electroconvulsive Therapy (i.e. shock treatment) has been found to be an effective treatment for severe cases of ADHD. 36. T F DK Treatments for ADHD which focus pr imarily on punishment have been found to be the most effective in reduci ng the symptoms of ADHD. 37. T F DK Research has shown that pr olonged use of stimulant medications leads to increased addiction (i.e., dr ug, alcohol) in adulthood. 38. T F DK If a child responds to stimulant medi cations (e.g., Ritalin), th en they probably have ADHD. 39. T F DK Children with ADHD generally display an inflexible adherence to specific routines or rituals.

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169 APPENDIX J ATPE INSTRUMENT Directions: Listed below are a number of statements expressing opinions or ideas about persons with epilepsy. There are many differences of opinion; many persons agree and many persons disagree with each statement. We would like to know your opini on about them. Read each statement carefully and then circle the appropriate number, from -3 to +3, that best corresponds with how you feel about the statement. There is no time limit for the completion of this questionnaire, but you should work as rapidly as you can. KEY -3: I disagree very much +1: I agree a little -2: I disagree pretty much +2: I agree pretty much -1: I disagree a little +3: I agree very much Please Respond To Every Statement 1. Schools should not place children with epilepsy into -3 -2 -1 +1 +2 +3 regular classrooms. 2. Persons with epilepsy have the same rights as all people. -3 -2 -1 +1 +2 +3 3. Persons with epilepsy can safely operate machinery. -3 -2 -1 +1 +2 +3 4. The individual with epilepsy does not possess a normal -3 -2 -1 +1 +2 +3 life expectancy. 5. Insurance companies should not deny insurance to an -3 -2 -1 +1 +2 +3 individual with epilepsy. 6. The individual with epile psy should not be prevented -3 -2 -1 +1 +2 +3 from having children. 7. Persons with epilepsy should be prohibited from driving. -3 -2 -1 +1 +2 +3 8. Children with epilepsy shou ld attend regular public -3 -2 -1 +1 +2 +3 schools. 9. The onset of epileptic seizures in a spouse is sufficient -3 -2 -1 +1 +2 +3 reason for divorce. 10. Individuals with epilepsy are also mentally retarded. -3 -2 -1 +1 +2 +3 11. Persons with epilepsy are a danger to the public. -3 -2 -1 +1 +2 +3 12. The responsibility for educating children with epilepsy -3 -2 -1 +1 +2 +3 rests with the community. 13. Individuals with epilepsy are accident-prone. -3 -2 -1 +1 +2 +3 > Over Please >

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170 Please Respond To Every Statement KEY -3: I disagree very much +1: I agree a little -2: I disagree pretty much +2: I agree pretty much -1: I disagree a little +3: I agree very much 14. Children need to be protected from classmates who -3 -2 -1 +1 +2 +3 have epilepsy. 15. Parents should expect of their child who has epilepsy -3 -2 -1 +1 +2 +3 what they expect of other children. 16. Persons with epilepsy can safely participate in -3 -2 -1 +1 +2 +3 strenuous activity. 17. Persons with epilepsy are more likely to develop and -3 -2 -1 +1 +2 +3 express criminal tendencies than are other people. 18. Persons with epilepsy should not be prohibited from -3 -2 -1 +1 +2 +3 marrying. 19. Laws citing epilepsy as the basis for the annulment -3 -2 -1 +1 +2 +3 of adoption should be repealed. 20. Persons with epilepsy prefer to live with others of -3 -2 -1 +1 +2 +3 similar characteristics. 21. Equal employment opportunities should be available to -3 -2 -1 +1 +2 +3 individuals with epilepsy. 22. You can expect the condition of a person with epilepsy -3 -2 -1 +1 +2 +3 to deteriorate. 23. The offspring of parents with epilepsy will also have -3 -2 -1 +1 +2 +3 epilepsy. 24. When their seizures are controlled by medication, -3 -2 -1 +1 +2 +3 persons with epilepsy are just like anyone else. 25. Families of children with epilepsy should not be -3 -2 -1 +1 +2 +3 provided supportive social services. 26. Epilepsy is not a contagious disease. -3 -2 -1 +1 +2 +3 27. Children with epilepsy in regular classes have an -3 -2 -1 +1 +2 +3 adverse effect on the other children. 28. Individuals with epileps y can cope with a 40-hour -3 -2 -1 +1 +2 +3 work week. Thank You For Your Assistance In Completing This Questionnaire

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174 Dunn, L., & Kontos, S. (1997). What have we learned about developmentally appropriate practice? Research in review. Young Children, 52 (5), 4-13. DuPaul, G. (1992). How to assess attention deficit disorder within school settings. School Psychology Quarterly, 7, 60-74. DuPaul, G., & Stoner, G. (1994). ADHD in the schools: Assessment and intervention strategies. New York: Guilford Press. DuPaul, G., & Stoner, G. (2002). Interventions for attention problems. In M. Shinn, H. Walker, and G. Stoner, Interventions for academic and behavioral problems II: Preventive and remedial approaches (pp. 913-938). Bethseda: Nationa l Association of School Psychologists. Fastenau, P., Shen, J., & Austin, J. (2008). A cademic underachievement among children with epilepsy: Proportion exceeding psychometric criteria for learning disability and associated risk factors. Journal of Learning Disabilities, 41(3), 195-207. Finch, J. (1987). The vignette technique in survey research. Sociology, 21 (1), 105-114. Forness, S., & Kavale, K. (2001). ADHD and a return to the medical model of special education. Education and Treatment of Children, 24 (3), 224-247. Fritz, J., Miller-Heyl, J., Kreutzer, J., & M acPhee, D. (1995). Fostering personal teaching efficacy through staff development and classroom activities. Journal of Educational Research, 88, 200-208. Fuchs, D., Mock, D., Morgan, P., & Young, C. (2003). Responsiveness-to-intervention: Definitions, evidence, and implications for the learning disabilities construct. Learning Disabilities Research & Practice, 18, 157-171. Garcia-Sanchez, C., Estevez-Gonzalez, A., Su arez-Romero, E., & Junque C. (1997). Right hemisphere dysfunction in subjects with attention deficit disord er with and without hyperactivity. Journal of Child Neurology, 12, 107-115. Gastaut, H. (1973). Dictionary of Epilepsy. World Health Organization: Geneva. Ghanizadeh, A., Bahredar, M., & Moeini, S. (200 6). Knowledge and attitudes towards attention deficit hyperactivity disorder am ong elementary school teachers. Patient Education and Counseling, 62, 84-88. Gibson, S., & Dembo, M. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76, 569-582. Glass, C. S. (2000). Factors influencing teachi ng strategies used with children who display attention deficit hyperactivity disorder characteristics. Education, 122, 70-79.

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175 Gresham, F. (2004). Current status and future directions of school -based behavioral interventions. School Psychology Review, 33 (3), 326-343. Hakola, S. (1992). Legal rights of students w ith attention deficit hyperactivity disorder. School Psychology Quarterly, 7, 285-297. Hale, J., Kaufman, A., Naglieri, J., & Kavale, K. (2006). Implementation of IDEA: Integrating response to intervention and cognitive assessment methods. Psychology in the Schools, 43(7), 753-769. Haslam, R., & Valletutti, P. (2004). Medical problems in the classr oom: The teachers role in diagnosis and management. Austin: Pro-Ed, Inc. Herbert J. D., Crittenden, K., & Dalrymple, K. L. (2004). Knowledge of soci al anxiety disorder relative to attention defic it hyperactivity diso rder among education professional. Journal of Clinical Child and A dolescent Psychology, 33, 366-372. Hesdorffer, D., Ludvigsson, P., Olafsson, E., Gudmundsson, G., Kjartansson, O., & Hauser, A. (2004). ADHD as a risk factor for incident unpro voked seizures and epilepsy in children. Archives of General Psychiatry, 61, 731-736. Hinshaw, S., Morrison, D., Carte, E., & Cornsw eet, C. (1987). Factorial dimensions of the revised behavior problem ch ecklist: Replication and validation within a kindergarten sample. Journal of Abnormal Child Psychology, 15, 309-327. Hox, J., & Kreft, I. (1994). Multilevel analysis methods. Sociological Methods & Research, 22(3), 283-299. Hynd, G., Lorys, A., Semrud-Clikeman, M., Niev es, N., Huettner, M., & Lahey, B. (1991). Attention deficit disorder wit hout hyperactivity: A distinct behavioral and neurocognitive syndrome. Journal of Child Neurology, 6, S37-S43. International League Against Epil epsy. (2003). Living with epilepsy. Epilepsia, 44( 6), 45-48. Kaleyias, J., Tzoufi, M., Kotsalis, C., Papa vasiliou, A, and Diamantopoulos, N. (2005). Knowledge and attitude of the greek educat ional community toward epilepsy and the epileptic student. Journal of Epilepsy and Behavior, 6, 179-186. Leone, P. (1989). Beyond fixing bad behavior and boys: Multiple pers pectives on education and treatment of troubled and tr oubling youth. In R.B. Rutherford, Jr., & S.A. DiGangi (Eds.), Severe behavioral disorders of children and youth. (Vol. 12, pp. 1-10). Reston, VA: Council for Children with Behavioral Disorders. Leppik, I. (2000). Contemporary diagnosis and management of the patient with epilepsy (5th ed.). Newtown, Pennsylvania: Handbooks in Healthcare.

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181 BIOGRAPHICAL SKETCH Nicole Nasewicz was born in 1982 on Long Islan d, New Yor k. The oldest of two siblings, she spent her formative years in Bradenton, Florida, graduating from Manatee High School (MHS) in 2000. She earned her B.S. in psycholog y and her M.Ed. in school psychology from the University of Florida (UF) in 2000 and 2007, resp ectively. Specializing in pediatric populations, Nicole completed many unique practicum rotati ons to further her knowledge, including the public school system, a multidisciplinary center, a cr aniofacial clinic, a pediatrics clinic, and a private practice setting. A year long internship with the Pinellas County Schools culminated her formalized training experience, equipping her with skills to function i ndependently and as an important member of a team. Nicole married Warren Pies, a fellow MHS and UF graduate, in December of 2006. Geographically, the couple anticip ates settling permanently in the Bradenton area, so that they remain in close proximity to their families and to Warrens job with a private, local law firm. Nicoles future plans include l eading a fulfilling career as a licensed psychologist, and to spending time with and expanding her family.