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Computerized screening in adolescents and young adults with ADHD Strangway, Carrie Lynn 2005

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C O M P U T E R I Z E D S C R E E N I N G IN A D O L E S C E N T S A N D Y O U N G A D U L T S WITH ADHD by Carrie Lynn Strangway B . A . , University of Western Ontario, 1996 A THESIS S U B M I T T E D IN P A R T I A L F U L F I L M E N T OF T H E R E Q U I R E M E N T S F O R T H E D E G R E E OF M A S T E R OF A R T S in T H E F A C U L T Y OF G R A D U A T E STUDIES (School Psychology)  T H E U N I V E R S I T Y OF BRITISH C O L U M B I A August 2005  © Carrie L y n n Strangway, 2005  Abstract This study examined the sensitivity o f a computerized neuropsychological screening battery ( I m P A C T ) to the cognitive effects o f A D H D in a sample o f 68 young adults with A D H D and 68 healthy students matched for age, education, gender, and history o f head injury. Students with A D H D self-reported more cognitive difficulties on the Post-Concussion Scale o f I m P A C T (p < .005, d = .68, medium-large effect size), and performed more poorly on the M e m o r y Composite (p < .005, d = .50, medium effect size). The two groups did not differ significantly on the Processing Speed Composite or the Impulse Control Composite. There was a nonsignificant trend for the individuals with A D H D to display slower reaction times (p < .076, d = .33, small effect size). This is the second study using f m P A C T in A D H D research. The brevity and sensitivity o f f m P A C T to the cognitive effects o f A D H D warrants further research with this population.  Table o f Contents  Abstract Table o f Contents List of Tables List of Figures Acknowledgments  Page ii iii iv v vi  ,  Introduction Literature Review . Overview of Attention Deficit Hyperactivity Disorder Neuropsychological Functioning in adults and adolescents with A D H D Summary of Results on Specific Neuropsychological Tests Tests o f Executive Functions Language Skills Tests Learning and M e m o r y Tasks..... Tests o f Intelligence Summary  .  1 3 3 7 20 20 26 27 29 30  Rationale for the Current Study Immediate Post-Concussion Assessment and Cognitive Testing ( I m P A C T ) Hypotheses  31 33 39  Methodology Participants Procedure Measures , Module 1 W o r d Discrimination Module II Symbol M e m o r y & Module III Color C l i c k Module I V Symbol Match Module V Color-Word Match Module V I Sequential Digit Tracking/Trigram Memory Module V I I Visual Attention Span I m P A C T composite scores Analyses •  42 42 43 43 46 47 48 49 50 50 51 53  ;  Results  53  Discussion Conclusions Limitations Future Directions  58 63 65 67  References  69  iii  List o f Tables Page Table 1.  Summary o f Studies Reporting on the Neuropsychological Performance o f A D H D Adults  9  Number o f Studies Reporting Significant differences between Adults with A D H D , n o n - A D H D controls, and patients with psychiatric disorders, on commonly administered neuropsychological tests.....  19  Table 3.  Post-Concussion Scale  45  Table 4.  Descriptive statistics for the I m P A C T composite scores  54  Table 5.  Pearson's Correlation coefficients among the composite scores  55  Table 6.  Descriptive statistics, significance tests, and effect sizes (Cohen's d)  56  Table 7.  Percentages and cumulative percentages o f subjects with unusual scores  57  Table 2.  List o f Figures Page  Figure 1. Overlapping distributions based on effect sizes (using the IQ metric)  63  Acknowledgments This thesis was conducted as partial fulfillment o f the primary author's Master o f A r t ' s degree in Educational and Counselling Psychology. I thank Dr. Shelley Hymel and Dr.Grant Iverson for their supervision with the content and completion o f this study. I also thank Dr. Nicholas Bogod, Dr.Tracey Brickell, Dr. Rael Lange, and Dr. Todd Woodward, for their guidance in writing the manuscript. I would also like to thank Jennifer Bernardo for her friendship and assistance with preparing the final manuscript. I thank m y Mother, Linda N i x o n , for believing in me and helping me to believe in myself. Finally, I thank my Father, Dr. J.F. Strangway, for both the love he has given me, and the sacrifices he has made to provide me with the support to achieve this goal. I aspire to carry out m y life with as much dignity and selflessness as he has shown me.  vi  Introduction  Attention deficit hyperactivity disorder ( A D H D ) is recognized as a serious neurobehavioral disorder that arises in early childhood and is prevalent throughout the lifespan (American Psychiatric Association, 2000; Barkley, 1997; Culbertson & K r u l l , 1996; Epstein, Johnson, Varia, & Conners, 2001). Neuropsychological problems in children with A D H D have been well documented (e.g., Halperin et al., 1990; Konrad, Gauggel, Manz, & Scholl, 2000; Kupietz, 1990; Loge, Staton, & Beatty, 1990; Seidel & Joschko, 1990; van der Meere & Sergeant, 1988). In the past, the disorder was thought to subside i n adolescence (Culbertson & K r u l l , 1996; Johnson et al., 2001), and as a result the neuropsychological deficits associated with A D H D i n adults are less well documented. Adults with A D H D have been shown to perform significantly more poorly on a variety of cognitive tests measuring attention, memory, reaction time, processing speed, set shifting (i.e., the ability to shift from one cognitive task to another), inhibition, and problem solving (Epstein et al., 2001; Murphy, Barkley, & Bush, 2001; Murphy, 2002b; Seidman, Biederman, Weber, Hatch, & Faraone, 1998; Walker, Shores, Trollor, Lee, & Sachdev, 2000; Woods, Lovejoy, Stutts, B a l l , & Fals-Stewart, 2002). However, these studies have been criticized for their lack o f consistency in differentiating adults and adolescents with A D H D from controls (Corbett & Stanczak, 1999; Kovner et al., 1998; Murphy, 2002a; Schmitz et al., 2002; Seidman, Biederman, Faraone, Weber, & Ouellette, f 997). A s a result, the existing literature examining cognitive functioning in young adults with A D H D is not conclusive, and further research with more refined measures o f cognitive functioning is needed. Woods, Lovejoy, and B a l l (2002) suggest that the use o f new neuropsychological assessment tools incorporating multiple cognitive constructs that assess a broad array o f  1  attentional and executive functions is needed. M a n y o f these tests measure the frontal. subcortical circuit dysfunction proposed to underlie A D H D (Faraone & Biederman, 1998). Implementing these measures in A D H D research may advance the understanding o f the neurocognitive deficits associated with A D H D in adults. The present thesis builds upon previous research on adults with A D H D by utilizing a new assessment tool called I m P A C T (Immediate Post-Concussion Assessment and Cognitive Testing; Lovell et al., 2003; Maroon et al., 2000) in a young adult A D H D sample. I m P A C T is a computerized, self-administered, 25-minute neuropsychological test battery composed o f seven individual test modules that are used to measure five aspects o f cognitive functioning: attention, memory, reaction time, processing speed, and impulse control. The purpose o f this study is to examine the sensitivity o f this computerized neuropsychological screening battery for distinguishing the cognitive effects o f A D H D in young adults from the performance o f nonA D H D controls. Specifically, the present study compares young adults with an A D H D diagnosis (as determined by self-report) to n o n - A D H D controls matched for education, gender, and history o f head injury, to determine whether or not there are cognitive differences between the two groups in terms o f their memory, reaction time, processing speed, and impulse control. I m P A C T also includes a symptom questionnaire. O f additional interest is whether or not there are differences in self-reported cognitive difficulties, such as perceived concentration and memory functioning, between the A D H D sample and the matched n o n - A D H D controls. If I m P A C T proves sensitive to cognitive problems associated with A D H D in young adults, it might be a useful measure in research and clinical practice due to its ease and rapidity o f administration. It might also be useful as a primary outcome variable in the evaluation o f the efficacy o f pharmacological interventions on cognitive symptoms associated with A D H D .  2  Literature Review Overview of Attention Deficit Hyperactivity  Disorder  Attention Deficit Hyperactivity Disorder ( A D H D ) is the one o f the most common emotional, cognitive, and behavioral disorders diagnosed and treated in youth. A D H D affects approximately 3-5% o f school age children with a male: female gender ratio o f 3:1 (American Psychiatric Association, 2000; Barkley, 1997; Culbertson & K r u l l , 1996; Schachar, Mota, Logan, Tannock, & K l i m , 2000; Wilens, Biederman, & Spencer, 2002). The disorder emerged i n the early 1900's medical literature, with researchers describing aggressive and defiant children as having poor volitional inhibition and defective moral regulation o f behavior (Barkley, 1997). Under the diagnostic term hyperkinetic reaction o f r  childhood, it first appeared in the second edition o f the Diagnostic and Statistical Manual o f Mental Disorders ( D S M ; American Psychiatric Association, 1968), referring to excessive activity as the primary symptom (Culbertson & K r u l l , 1996). In the early 1970's, Douglas (1972; as cited i n Schachar et al., 2000) provided a model that proposed attention deficit, rather than excessive activity, was the main feature o f the disorder. This model guided future research and led to the term attention deficit disorder, which appeared in the DSM-1II (American Psychiatric Association, 1980) reflecting an attention deficit, rather than excessive activity, as the main feature o f the disorder. B y the 1980's there was a movement towards distinguishing a hyperactivity component, and the term attention deficit hyperactivity disorder emerged as a separate disorder from A D D . This was adopted in the D S M - I I I - R (American Psychiatric Association, 1987). In both the D S M - I V and D S M - I V - T R (American Psychiatric Association, 1994, 2000) A D H D is divided  3  into three primary subtypes: predominantly inattentive type, predominantly hyperactiveimpulsive type, and combined type. A D H D is characterized by age-inappropriate levels o f inattention, with or without impulsivity, and overactivity that occurs across settings and causes functional impairment. A D H D begins i n childhood, and 50-70% o f childhood cases persist into adulthood (Murphy & Schachar, 2000; Wilens et al., 2002). Although the observable symptoms can change in quality and quantity over time, most individuals with A D H D continue to experience some symptoms as adults (Mercugliano, 1999). Adolescents and adults with A D H D are at a higher risk for academic problems, poor peer and family relations, anxiety and depression, aggression, conduct problems, delinquency, early substance abuse, driving accidents, and unemployment (Barkley, 1997; Gallagher & Blader, 2001; Schmitz et al., 2002). A s a result, A D H D is considered a major clinical and public health problem, due to its associated morbidity and disability i n individuals across all ages (Wilens et al., 2002). > The majority o f researchers and clinicians agree that the primary disturbance o f A D H D results v i a poor control over executive functions, with at least some o f these executive functions linked to the frontal and sub-cortical regions o f the brain (Faraone & Biederman, 1998; Gallagher & Blader, 2001; Royall et al., 2002). However, evidence to support this view has been somewhat mixed, and it is not yet clear which aspects o f cognitive functioning reliably distinguish people with A D H D from those without. According to Barkley (1997), the primary behavioral characteristics o f A D H D are age-inappropriate levels o f inattention, impulsivity, and hyperactivity. These problems are considered to reflect difficulty with the management and executive control o f behavior. Deficits in attention are not considered the result o f an inability to attend, but rather a problem in the executive tasks o f organising  4  attention (i.e., sustaining attention on stimuli and shifting attention). Similarly, impulsivity is not defined as a failure to control one's actions. Rather, it is a difficulty with deciding when actions should be taken, and controlling the impact and order o f those actions. Lastly, hyperactivity is not seen as a result o f overactivity, but as a disturbance in the executive task o f controlling the appropriate situational level o f arousal and activity (Gallagher & Blader, 2001). Using neuropsychological testing i n children with A D H D , researchers have identified reduced performance in attention, inhibition, and executive functions compared to n o n - A D H D controls (Benezra & Douglas, 1988; Douglas & Parry, 1983; Pineda et al., 1998; Schachar et al., 2000; Seidel & Joschko, 1990). Despite these findings, the role o f neuropsychological testing in children remains controversial. This is due to the inconsistent findings across neuropsychological measures, and concerns regarding inadequate positive and negative predictive power o f the cognitive measures. These may be partially attributable to methodological limitations o f the studies (Kempton et al., 1999). In addition, childhood A D H D might be characterized by more overt behavioral characteristics (i.e., hyperactivity), rather than cognitive deficits i n attention and executive functioning. The behavioral symptoms o f A D H D subside as children mature, and signs o f excessive gross motor activity are less common in early adolescence (American Psychiatric Association, 2000). Researchers believe that adults are more likely to exhibit cognitive deficits i n attention and inhibition than the behavioral deficits that characterize children with A D H D (Barkley, 1997; Woods, Lovejoy, & B a l l , 2002). However, the potential cognitive differences between children with A D H D and adults with A D H D have not yet been established, due to the limited research in this area. Preliminary research suggests that young adults and adults with A D H D have deficits compared to n o n - A D H D controls on measures o f attention, memory, reaction time, processing  5  speed, inhibition, problem solving, and set shifting (Epstein et al., 2001; Murphy et al., 2001; Murphy, 2002b; Seidman et al., 1998; Walker et al., 2000; Woods, Lovejoy, Stutts et al., 2002). However, similar to the children's literature, these results are not consistent across tests and studies. Moreover, controversy still exists regarding the validity o f A D H D as a disorder o f adulthood due to the lack o f a reliable set o f diagnostic criteria, and the few neuropsychological tests that can clearly differentiate the putative cognitive deficits associated with the condition (Johnson et al., 2001). According to D S M - I V - T R (American Psychiatric Association, 2000), an individual  (  must have had symptoms o f A D H D that date back to childhood. For an adult that was not diagnosed with A D H D as a child it is not always possible to obtain this information from multiple raters or sources. A s a result, the clinician or researcher must often rely on an individual's self-report o f their symptoms. Further, the age-of-onset criterion o f the disorder y  requires that symptoms be apparent prior to the age o f seven. A n adult's ability to validly selfreport past symptoms necessary to retrospectively diagnose the condition has been constantly debated in the literature (Applegate et al., 1997; Barkley & Biederman, 1997; Levin, 1998; M o t a & Schachar, 2001). Murphy and Schachar (2000) explain that researchers and clinicians are often forced to rely on an individual's account o f current and childhood symptom because it is often impractical or impossible to obtain this information from a former teacher, parent, or current employer. To advance research on young adults with A D H D it is necessary to determine i f they can accurately self-report past and current symptoms. Moreover, according to Woods, Lovejoy, and B a l l (2002), new neuropsychological assessment techniques that include a comprehensive  6  battery approach (e.g., assess multiple constructs at one time) are needed to better characterize the cognitive deficits in adults with A D H D . Neuropsychological  Functioning in Adolescents and Adults with ADHD  O f primary interest to the present study is the role o f neuropsychological tests i n the identification o f adolescents and adults with A D H D . Surprisingly few studies to date have examined whether neuropsychological tests o f particular cognitive abilities can consistently differentiate adults with A D H D from those without the disorder. A. review o f studies designed specifically to examine the neurocognitive functioning o f adolescents and adults with A D H D is provided i n Table 1. The purpose o f the review is to provide the reader with an overview o f the current state o f this literature in terms o f the varied measures, diagnostic criteria, and sample selections. Due to the limited literature available i n this area, all studies pertaining to this area were included. Studies were not excluded based on possible methodological weaknesses, including small sample sizes, or the use o f tests with limited psychometric properties. These findings are reviewed according to the neuropsychological tests (rather than the study) and the cognitive areas measured. Most o f these studies focus on attention and executive functions because much o f the current research is based on the conceptualization o f A D H D as a frontal-subcortical disorder (Barkley, 1997; Faraone & Biederman, 1998; Gallagher & Blader, 2001; Johnson et al., 2001; Mercugliano, 1999). The emerging neuroimaging literature suggests the presence o f abnormalities i n frontal networks as shown by positron emission tomography brain imaging i n adults with A D H D (Wilens et al., 2002). However, empirical support for the precise neural pathways associated with A D H D remains elusive. Hence, the nature o f the proposed connection between frontal lobe function  7  and actual cognitive task performance i n A D H D is not yet supported by consistent data, as stated earlier in the review. Given the recency o f this area o f inquiry, it is not surprising that many researchers are considering many different indices o f cognitive performance that (they hope or hypothesize) are loosely linked to the broad construct called "executive functioning.'  i  8  Table 1 Summary of Studies Reporting on the Neuropsychological  Study  Participants (Sex, age range)  Diagnostic criteria (Medication use, subtypes of A D H D indicated; use of subtypes in analysis)  Performance  of ADHD  Adults  Design and grouping procedures (Using IQ as a covariate)  Measures  Major Findings  Murphy (2002a)  18 A D H D 18 Controls (Males, aged 27-58 years)  DSM-IV semistructured interview (Medication: not indicated, subtypes not indicated)  IQ not significant between groups.  SSRT; GSRT  Adults with A D H D performed significantly more poorly than controls on tasks of inhibitory control. However the results were not significant between the two groups on a reaction time test.  Murphy (2002b)  18 A D H D 18 Controls (Males, aged ' 27-58 years)  DSM-IV semistructured interview (Medication: not indicated, subtypes not indicated)  IQ not significant between groups.  BVRT; TOH; TMTA&B  Adults with A D H D performed significantly more poorly than the control group on tests of executive control (i.e., T O H , and T M T - B).  Johnson et al. (2001)  56 A D H D 38 N C (71% males, aged 20-63 years)  DSM-IV Semistructured interview (Medication: subjects were washed out, subtypes identified but not used in analysis)  Age was used as a covariate, IQ not significant between groups. (IQ was used as a covariate in a secondary analysis).  WMS-R; COWA; Stroop; WCST; TMT-A& TMT-B; RTT  Adults with A D H D showed deficits relative to controls on tasks of memory, selective attention, visuomotor tracking, and reaction time. Using IQ as a covariate showed no significant differences between groups.  9  Study  Participants  Diagnostic Criteria  Design and grouping criteria  Walker et al. (2000)  30 A D H D 30 Controls 30 Psychiatric (Sex mixed, aged 17-50 years)  DSM-IV criteria (Medication: subjects were not on any, subtypes not identified)  Seidman et al. (1998)  64 A D H D 73 Controls (Sex mixed, agedl9-59 years)  Epstein et al. (2001)  Epstein et al. (1998)  Measures  Major findings  Age was used as a covariate, IQ not significant between groups.  COWA; CPT; Stroop; TMT; WAIS-R subtests  Compared to healthy controls, adults with A D H D scored significantly more poorly on the dependent measures. However, no significant differences on any task were identified between adults with A D H D and those with a psychiatric disorder.  DSM-III criteria, and self-report of childhood symptoms (Medication: subjects were not on any, subtypes not identified)  Age was used as a covariate, IQ not significant between groups.  WAISFD; CVLT; Stroop. WCST; CPT; ROCF  Significant differences were found between the adults with A D H D and control subjects on reaction time and verbal learning tasks. The groups did not differ on any traditional measures of executive functioning.  25 A D H D 15 Controls 15 Psychiatric (Sex mixed, aged 18-65 years) c  Computer interviewself report of symptoms (Medication: subjects were not on any, subtypes were not identified)  Gender, age, and education were not different between any groups. IQ was not measured.  CPT; PVOT; SST  Adults with A D H D demonstrated significantly poorer performance on measures of response inhibition (e.g., reaction time) as compared to normal controls and individuals with anxiety disorders.  60 A D H D 72 Controls (Sex mixed, mean age 25 & 35 years)  Semi-structured interview (Medication: not reported, subtypes identified and used in analysis)  Age was used as a covariate, IQ was not examined.  CPT  Adults with A D H D performed significantly more poorly on all C P T indices (i.e., omission, commission, and reaction time scores) compared to normal controls. No significant differences between the A D H D subtypes were found. Diagnostic classification results for the C P T were moderate.  10  Study  Participants  Diagnostic Criteria  Murphy et al. (2001)  105 A D H D 65 Controls Sex mixed, aged 17-28 years)  Structured interview, (Medication ceased 24 hours prior to testing, subtypes identified and used in analysis)  Corbett & Stanczak(1999)  27 A D H D 10 Controls (Sex mixed, aged 18-72 years)  Woods, Lovejoy, Starts et al. (2002)  Kovner et al. (1998)  Design and grouping ' procedures  Measures  Major Findings  Groups did not differ on age or sex. IQ scores were significant on the KBIT. (IQ and gender were used as covariates in a secondary analysis)  CPT; Stroop; WAIS-III Digit Span & Digit Symbol; COWA  After controlling for IQ significant between group differences were found in areas of attention, nonverbal working memory, interference control, and verbal fluency. Women with A D H D scored significantly higher than men on one measure (digit symbol subtest). No significant differences between the A D H D subtypes were found.  Semi-structured interview, (Medication: subjects were asked to refrain on day of testing, subtypes not identified)  No difference between groups on gender and age. IQ was not examined.  Stroop; TOAD  Significant differences between the adults with A D H D and normal controls were found on the dependent measures. The Goldman-Fristoe-Woodcock Test of Auditory Discrimination (TOAD) showed high specificity and predictive power in discriminating adults with A D H D from controls. This test appears to be a measure of distractibility and behavioral disinhibition.  26 A D H D 26 N C (Sex mixed, aged 21-55 years)  DSM-IV criteria from normative database, (Medication: Subjects were not on any, subtypes identified)  No group differences between groups on gender, age, or education. (IQ was used in analysis)  COWA; CVLT; Stroop; TMT; WAIS-R FD  Significant group differences between adults with A D H D and normal controls were found using a discrepancy analysis between intelligence and executive function. The diagnostic accuracy was moderate for the individual tests.  19 A D H D 10 Psychiatric (Sex mixed, aged 18-57 years)  Structured interview (Medication: Subjects were not on any, subtypes were identified but not used in the analysis)  No group differences were found on age, education, or intelligence. (IQ was not examined)  WAIS-R; Benton; Boston Naming Test; CPT; SST; WMRT  Adults with A D H D scored significantly lower than a psychiatric group on a measure of simple attention (WAIS-R Digit Span subtest) and the reaction time component of the Shifting Sets Test (SST). Group classification rates between the psychiatric group, and the A D H D group, were adequate.  11  Design and grouping procedures  Measures  Major Findings  The groups were not significantly different on age, gender, or IQ.  Anticascde task; Negative Priming Task  Young adults with A D H D had significantly more difficulty with effortful motor inhibition on a computer task than the control group  Structured clinical interview. (Medication discontinued prior to testing, subtypes not identified)  Age was used as a covariate. The groups were not significantly different on IQ.  Stroop Test; WCST; CPT; ROCF  Young adults with A D H D showed no significant differences from healthy controls on any of the dependent measures.  30 A D H D 60 Controls (Sex mixed, aged 12-16 years)  Structured clinical interview (Medication: some subjects were taking medication, subtypes were identified and used in analysis)  The groups were not significantly different on any demographic variables. (No effect of sex or IQ was found in any measure).  WCST; Stroop; Digit Span.  The authors examined effects of the three subtypes of A D H D . Adolescents with predominantly inattentive and combined subtypes performed more poorly on tasks of attention and psychomotor speed. Adolescents with predominantly hyperactive-impulsive type did not differ from the control group on any of the measures. These findings moderately support the diagnostic distinction among the A D H D subtypes proposed in the DSM-IV.  118 A D H D 99 Controls (Males, aged 9-22 years)  Structured clinical interview (Medication: 80% of A D H D group on medication. No significant differences between medicated and non-medicated groups, subtypes not identified)  The groups were significantly different on age and IQ. (IQ was purposefully not controlled for).  WCST; ROCF; Stroop test; C P T ; CVLT  Young adults with A D H D performed significantly more poorly on tasks of visual memory, problem solving, and set shifting. No significant differences were found between the two groups on tasks of attention and reaction time (CPT), or on a verbal list learning task ( C V L T ) .  Study  Participants  Diagnostic criteria  Nigg et al. (2002)  22 A D H D 21 Controls (Sex mixed, mean age was 23 and 21 years for the two groups)  Previous diagnoses by psychiatrist and selfreport of symptoms. (Medication: Subjects were not on any, subtypes identified but not used in analysis)  Fischer et al. (1990)  100 A D H D 60 Controls (Males, aged 12-20 years)  Schmitz et al. (2002)  Seidman et al. (1997)  12  Study  Participants  Diagnostic Criteria  Stearns et al., (2004)  70 A D H D (Sex mixed, mean age= 25 years)  Structured interview, (21.1% taking medication, subtypes not identified)  Design and grouping procedures Sample did not differ on age, sex, or education. IQ scores were not significantly different between sample (i.e., sex, or those on medication).  Measures  Major Findings  WAIS-III; WMS-III (Working Memory Indices); Brown ADD Scales  In a group of-adults with A D H D no significant relationship was found between working memory and self-reported symptoms. Moreover, no significant effects were found for gender or those taking stimulant medications.  Note: A D H D = Attention Deficit Hyperactivity Disorder group. SSRT = Stop Signal Reaction Time Test; G S R T = Go Signal Reaction Time; B V R T ; Benton Test of Visual Recognition; TOH= Tower of Hanoi; Stroop = Stroop Test Color Word Task; WCST= Wisconsin Card Sorting Test; T M T = Trail Making Test; R T T = Reaction Time Test; COWA= Controlled Oral Word Association; WMS-R = Wechsler Memory Scale-Revised; CPT = Continuous Performance Test; WAIS-R = Weschler Adult Intelligence Scale; WRAT=Wide Range Achievement Test; C V L T = California Verbal Learning Test; R O C F = Rey-Osterrieth Complex Figure; PVOT=Posner Visual Orientating Task; T O A D = Goldman-Fristoe-Woodcock Test of Auditory Discrimination; W M R T = Warrington Recognition Memory Test.  13  A general profile o f poor performance on tests o f frontal/executive function is evident in adults with A D H D (Epstein et al., 2001; Johnson et al., 2001; Murphy, 2002a, 2002b; Woods, Lovejoy, & B a l l , 2002). However, as shown in the reviewed studies (Table 1) adults with A D H D do not perform consistently more poorly than healthy controls across studies, nor do they consistently perform more poorly on specific measures (Fischer et al., 1990; Kovner et al., 1998; Seidman et al., 1998). Alexander and Stuss (2000) argue that the lack o f discriminant validity (i.e., differentiating A D H D from healthy controls; differentiating clinical subtypes o f A D H D ; differentiating A D H D from other disorders) on specific measures may be due to the fact that individual neuropsychological tests (e.g., C P T , W C S T ) assess too many dimensions o f executive functioning. A s a result, they are not always helpful in discriminating neurocognitive problems associated with A D H D , where primary involvement is thought to reside with frontal subcortical systems. Future research needs to incorporate new assessment techniques to help characterize the cognitive deficits o f adults with A D H D (Alexander & Stuss, 2000; Barkley, 1997; Johnson et al., 2001; Schmitz et al., 2002; Seidman et al., 1998). Moreover, implementing a battery approach utilizing multiple neuropsychological tests has been shown to improve the discriminant validity i n this population (e.g., Woods, Lovejoy, Stutts et al., 2002). Numerous methodological limitations are inherent in the A D H D literature. Primarily, the lack o f a reliable and valid method for diagnosing A D H D in adults is a major problem. In the reviewed studies, researchers often relied on only one diagnostic indicator (e.g., self-report in a clinical interview) with no cross-validation o f symptoms from multiple settings (Epstein et al., 1998; Epstein et al., 2001; Murphy, 2002a, 2002b; N i g g et al., 2002).  14  Murphy and Schachar (2000) explored the use o f self-ratings in the assessment o f symptoms o f A D H D in adults (ranging from 20 to 50 years o f age) in two studies. The first study examined the validity o f childhood recollections o f A D H D behavior by having the individual with A D H D and a parent or spouse fill out similar rating scales. The second study followed a similar methodology but examined an individual's ability to self-report current symptoms o f A D H D . Correlations between the self-reports o f over 2100 individuals with A D H D , and their partners or spouses, were calculated. Results from both studies revealed significant similarity between ratings, and the authors concluded that adults with A D H D can provide reliable self-reports of past and present A D H D symptoms (Murphy & Schachar, 2000). The use o f small sample sizes was a weakness in many o f thestudies reviewed i n Table 1. Most studies had no more than 20 participants in the A D H D or control group (e.g., Corbett & Stanczak, 1999; Kovner et al., 1998; Murphy, 2002a, 2002b; Schmitz et al., 2002) resulting in l o w statistical power and increasing the probability o f type II errors. Moreover, many researchers did not provide effect sizes or other indices o f diagnostic efficiency (e.g., Fischer et al., 1990; Schmitz et al., 2002; Seidman et al., 1998), leaving specific interpretation o f the findings uncertain, and decreasing the clinical utility o f the results (Woods, Lovejoy, & B a l l , 2002). The age ranges o f the samples were often large, with participants ranging in age from 18-72 years o f age (Corbett & Stanczak, 1999; Kovner et al., 1998; Murphy, 2002a, 2002b; Seidman et al., 1998; Walker et al., 2000; Woods, Lovejoy, Stutts et al., 2002). Thus, the potential effects o f developmental changes that occur across the lifespan, and potential agerelated declines i n executive functions, were not controlled for.  15  Numerous studies have examined the effects o f age-related declines on healthy adults using measures o f executive and other cognitive functions. The prefrontal cortex (i.e., the primary region examined by tests o f executive function) has been found to be the most vulnerable area to aging compared to other areas o f the brain, and age-related declines are thought to begin i n early adulthood (Salthouse, 2003). However, most o f the A D H D research to date is cross sectional, and longitudinal data is needed to examine the precise relationship between aging and its effects on cognitive tests in the A D H D population. M a n y o f the reviewed studies had stringent inclusion criteria and controlled for factors known to affect cognitive performance (i.e., comorbid disorders such as depression or anxiety, and medication use). However, some studies did not (e.g., Epstein et al., 1998). Although individuals with A D H D often reported higher levels o f depression than controls (Seidman et al., 1998; Walker et al., 2000), it is often difficult to distinguish individuals with A D H D from those with a psychiatric disorder (e.g., anxiety disorder) on neuropsychological tests. From the studies reviewed, only three examined psychiatric groups compared to individuals with A D H D (Epstein et al., 2001; Kovner et al., 1998; Walker et al., 2000), and only one study (Kovner et al., 1998) reported differences between individuals with A D H D and a psychiatric sample. Differentiation o f A D H D from commonly comorbid disorders (i.e., depression, anxiety, substance abuse) is cited as a weakness o f the literature (Woods, Lovejoy, & B a l l , -2002). Future research needs to examine the ability o f tests to discriminate A D H D from other comorbid conditions. The use o f stimulant medications is generally found to increase the cognitive performance o f individuals with A D H D (Schmitz et al., 2002). In the study for this thesis, the use o f medication could not be controlled for. However, two studies reviewed examined this  16  issue (Seidman et al., 1997; Steams et al., 2004) and found no significant differences on cognitive performance between medicated and unmedicated participants with A D H D , although differences were found i n Schmitz et al. (2002). In the children's A D H D literature, executive function deficits have been examined more thoroughly i n males than in females (Carte, N i g g , & Hinshaw, 1996; N i g g , Hinshaw, Carte, & Treuting, 1998). Some researchers suggest that girls with A D H D display greater cognitive impairment, while boys with A D H D display more obvious behavioral impairments (Gaub & Carlson, 1997). However, Halperin et al. (1990) found no cognitive differences between boys and girls with A D H D . In the adult A D H D literature, potential sex differences have received little attention, and some studies include only male participants (Fischer et al., 1990; Murphy, 2002a, 2002b; Seidman et al., 1997). Other studies included both sexes (Kovner et al., 1998; Murphy et al., 2001; Woods, Lovejoy, Stutts et al., 2002), but only analyzed whether the ratio of males to females i n the A D H D group differed from the sex ratio in the control group. However, these studies did not examine whether or not there were performance differences on tests according to sex. However, Murphy et al., (2001) explored the potential cognitive differences between males and females with A D H D , and reported that women demonstrated higher scores than men on two measures: attention and working memory. In contrast, other studies (Schmitz et al., 2002; Seidman et al., 1998) found no significant sex differences i n young adults with A D H D on multiple measures o f cognitive functioning. A long-standing debate i n the literature is whether or not to separate adults with A D H D by D S M - I V - T R subtypes. Some researchers maintain that executive function deficits do not appear to be a function o f A D H D subtype (Woods, Lovejoy, & B a l l , 2002). Due to small sample sizes, the majority o f reviewed studies did not partition their A D H D sample by subtype  17  (Epstein et al., 2001; Kovner et al., 1998; N i g g et al., 2002; Walker et al., 2000). Only three studies have identified subtypes o f A D H D and included them in their analyses (Epstein et al., 1998; Murphy et al., 2001; Schmitz et al., 2002), and only one study o f the three found cognitive differences across the three D S M - I V - T R subtypes (Schmitz et al., 2002). Specifically, Schmitz et al. (2002) found that adolescents with predominantly inattentive and combined type performed more poorly on tasks o f attention and psychomotor speed. Adolescents with the predominantly hyperactive-impulsive subtype did not differ from the control group on any measures. These findings appear to support the diagnostic distinction among the A D H D subtypes proposed in the D S M - I V that individuals with the hyperactiveimpulsive subtype experience attentional deficits to a lesser degree than the other subtypes, and show the greatest decline in A D H D symptoms with age (Epstein et al., 1998; Schmitz et al., 2002). However, these results are very preliminary and run counter to the bulk o f the literature to date. The present study did not partition the A D H D sample by A D H D subtype because this information was not available. Accounting for the different results across studies is difficult due to methodological differences (i.e., sample sizes, age ranges, and inclusion criteria). Further, the disparity may relate to the differences i n the measures and the constructs examined. However, these findings mirror results in the pediatric literature that, thus far, have not consistently identified different cognitive profiles among the A D H D subtypes (Barkley, Grodzinsky, & DuPaul, 1992; Carlson, Lahey, & Neeper, 1986; Trommer, Hoeppner, Lorber, & Armstrong, 1988). Future research with larger numbers o f participants and more stringent inclusion criteria is needed to determine whether or not there are cognitive differences on tests o f executive functions among the A D H D subtypes. The total number o f tests across studies that have reported significant and non-  18  significant group differences between adults with A D H D , n o n - A D H D controls, and psychiatric groups is reported i n Table 2. Table 2 Number of Studies Reporting Significant differences between Adults with ADHD,  non-ADHD  controls, and patients with psychiatric disorders, on commonly administered neuropsychological  tests  •  •  .  Measure  Non-ADHD Controls  Psychiatric Group  Attention/Executive Function Tests  Yes N o  Yes N o  7 1 6 2 3  3 4 3 2 1  0 0 0 0 0  2 1 1 1 1  3  1  0 -  1  2 1 . 2 1  2 2 0 0  0 0 0 0  0 0 1 1  . 2 3 3  5 0 1  0 0 0  0 0 1  Continuous Performance Test ( C P T ) Wisconsin Card Sorting Test ( W C S T ) Stroop Test Trail M a k i n g Test- A ( T M T - A ) Trail M a k i n g Test- B ( T M T - B ) Language S k i l l Tests Word Fluency: C O W A T Learning/Memory Tests California-Verbal Learning Test ( C V L T ) Rey Complex Figure Test ( R C F T ) W M S - R Logical Memory W M S - R Visual Reproduction Intelligence Tests W A I S - R F u l l Scale IQ* WISC-III & W A I S - R Digit Span WISC-III & W A I S F D / D i g i t Symbol  Yes = significant differences between adults with A D H D and comparison group/psychiatric group; No = No significant differences between adults with A D H D and comparison/psychiatric group; A D H D =Attention Deficit Hyperactivity Disorder group. W M S - R = Wechsler Memory Scale-Revised; WAIS-R = Weschler Adult Intelligence Scale-Revised; WISC-III = Wechsler Intelligence Scale for Children- Third edition; C O W A T = Controlled Oral Word Association Test.  Note:  19  Summary of Results for Specific Neuropsychological  Tests  A s can be seen in Table 2, the results from the studies are highly variable. However, most studies (although not all) have demonstrated significant differences between young adults with A D H D and healthy controls. The individual tests and subsequent results presented in Table 2 are discussed i n detail below. Tests of Attention/Executive Functions. Barkley (1997) defines executive functions as a variety o f higher-order cognitive skills that assist with the self-regulation o f behavior. However, others have proposed different definitions, and a precise standardized operational definition has yet to be agreed upon in the literature. The term executive functions seems to incorporate planning or any goal-directed action, including persistence toward achieving a goal, inhibition (i.e., one's ability to resist a response or behavior), problem solving and strategy development, including monitoring, flexibility, and self-awareness across time (Barkley, 2000). These activities are underpinned by many lower order cognitive operations, with working memory being one o f the most important processes (Spreen & Strauss, 1998). It is important to note that impairment o f executive functions such as planning, flexibility, and judgment can be present with any major change in intellectual functioning (Lezak, 1995). Following this approach, many researchers' working definition o f executive functions includes the following components: working memory, response inhibition, planning, cognitive flexibility, and concept formation (Royall et al., 2002). The cognitive tasks that measure these executive functions are typically components o f large neuropsychological batteries, made up o f many different tests, which include tests o f frontal or executive functioning, and tests o f other cognitive abilities (e.g., language and memory).  20  The Continuous Performance Test (CPT) is the most commonly used test for assessing attention deficits in A D H D (Woods, Lovejoy, & B a l l , 2002). The C P T is a computerized test o f attention, impulsivity, and vigilance. It involves discriminating between visually presented target and non-target stimuli (Spreen & Strauss, 1998). The task requires an individual to rapidly press a computer space bar or click a mouse button to letters presented in sequence i n the center o f the screen. In the standard condition, the examinee is required to press the space bar (mouse click) for every letter presented except the letter " X . " The test takes 14 minutes to complete. The omission errors (number o f targets the person did not respond to), commission errors (number o f times the person responded to a non-target " X " ) , incidental reaction time (mean response time), and variability o f reaction time (consistency o f response time) are calculated (McGee, Clark, & Symons, 2000). L o w to moderate correlations are reported between the C P T and other measures o f attention. However, the precise cognitive processes assessed by the C P T are unclear; The general consensus (Halperin, Sharma, Greenblatt, & Schwartz, 1991; as cited i n Spreen & Strauss, 1998) is that omission errors reflect difficulties with sustained attention, while commission errors reflect problems with impulsivity, attention, and memory. The C P T normative data is most representative o f males (75.4% i n sample) between 6 and 30 years o f age (only one-fifth o f the sample was over eighteen years o f age). The usefulness o f the C P T as a measure that can distinguish children with A D H D from controls has been demonstrated consistently in the literature (Barkley, DuPaul, & M c M u r r a y , 1990; Halperin et al., 1990; Halperin et al., 1991). However, the measure has not been demonstrated to discriminate children with A D H D from other clinical groups (Barkley et al., 1990).  21  A more mixed pattern o f results using the C P T is found in the adult A D H D literature. Kovner et al. (1998) found no differences on C P T performance between adults with A D H D and a psychiatric control group. Further, the C P T did not discriminate between adults with A D H D and controls in terms o f hit reaction time (Murphy et al., 2001). In contrast, two other studies comparing adults with A D H D to healthy controls found that the A D H D group made significantly more errors o f commission and omission than the control group (Epstein et al., 1998; Walker et al., 2000). Still, the majority o f studies have found significant differences between groups on the C P T (see Table 2). The Wisconsin Card Sorting Test ( W C S T ) assesses conceptualization and measures an individual's ability to problem-solve and/or shift cognitive strategies (Johnson et al., 2001). The task requires the examinee to sort a set o f cards based upon three different criteria (i.e., color, form, and number). N o instructions on the sorting criteria are given to the examinee. The examinee is instructed to match their cards, one at a time, with one o f four "key cards." They are then only given feedback on a correct or incorrect placement, and are required to use that feedback to guide their future card placements to optimize correct responses. After correctly matching a card according to a matching stimulus (i.e., color) for 10 consecutive trials, the matching feature changes without warning (e.g., color to form), and the examinee must again discern the correct sorting criteria by the examiner's feedback (Lezak, 1995). This occurs six times (i.e., color, form, number, color, form, number), or until all 128 cards are administered. Successful performance on the W C S T requires that an individual determine the correct response for each set, maintain it, and then shift set (e.g., color to form) according to feedback (Romine et al., 2004). The problem-solving component involves the examinee considering a variety o f hypotheses and maintaining or rejecting them according to the feedback they receive.  22  Performance is scored by categories completed (the number o f correct matches completed i n each category), trials to complete first category (the number o f cards it takes to complete the first matching task), number of failures to maintain set (the number o f times the examinee makes an incorrect category response more than four times i n a row), and percent preservative errors (which reflects the amount o f preservative errors as a percentage o f overall test performance). Normative data for the test are available for individuals 6 to 89 years o f age (Spreen & Strauss, 1998). A g e has the strongest demonstrated relationship to W C S T performance. Performance increases are reported from ages 5 to 19 years; performance stability is noted for individuals aged 20-50 years; and declines in some aspects of performance are reported in individuals aged 60 years and above (Heaton, Chelune, Talley, K a y , & Curtis, 1993; as cited i n Spreen & Strauss, 1998). The test's sensitivity and specificity as a measure o f executive functioning has been demonstrated in numerous studies (Lezak, 1995). Similar to the C P T , statistically significant differences on the W C S T between children with A D H D and controls frequently are reported (Barkley et al., 1992; Schmitz et al., 2002). However, there has been little success using the W C S T to discriminate children with A D H D from other clinical populations (Snow, 1998). W i t h regard to the reviewed literature, only the studies that included adolescents and young adults with A D H D found significant differences compared to healthy controls (Schmitz et al., 2002; Seidman et al., 1997). T w o other studies using older participants (aged 19-63) found no significant differences on the W C S T compared to healthy controls (Johnson et al., 2001; Seidman et al., 1998). Moreover, similar to the difficulty discriminating children with A D H D from other clinical populations, Fischer et al. (1990) found no significant differences on the W C S T between a group o f adults with A D H D {  23  and psychiatric controls. Taken together (see Table 2), the majority o f studies fail to differentiate between adults with A D H D and controls using the W C S T , especially in adulthood. The Stroop Test is a classic test o f reading fluency, visual attention, mental flexibility, and inhibitory control requiring participants to read lists o f words and colors (Johnson et al., 2001). The first part o f the task requires the examinee to read color names printed i n black ink (e.g., red, green). The second part o f the test requires the individual to name the colors that colored X s , are printed i n . In the last part o f the task the individual is presented with color names that are now printed in different colored ink (e.g., the word "red" printed i n blue ink), and they are required to disregard the word, and name the ink color. This requires the individual to inhibit the over-learned, automatic response o f reading the stimulus word i n order to respond to the more novel task o f naming the color o f the ink. For each part o f the test, both the time to complete the test and the number o f errors are recorded and scored. Having to inhibit the over-learned (prepotent) word reading response results in significantly slower performance than word reading or color naming alone. This decrement in performance has been labeled the Stroop "interference effect" (Spreen & Strauss, 1998). The construct validity o f the Stroop test has been examined in adolescents with and without A D H D . M a c L e o d and Prior (1996) found significant correlations between Stroop interference and the Paced Auditory Serial Addition Task (a task requiring speeded processing, mental arithmetic, and the ability to divide attention), but not between the Stroop and a test purported to measure intelligence (Slossan Test o f Intelligence). However, normative data for the Stroop test suggests that both age and intellectual levels are strong predictors o f performance. Individuals aged 25-35 years o f age have shown higher levels o f performance on ,the first part o f the task (reading the color names i n black ink), and lower levels o f performance  24  on the interference part o f the task (naming the ink color). However, older participants, aged 70-80 years o f age are relatively slow on the first part o f the task, but relatively faster on the interference part o f the task (Klein, Ponds, Houx, & Jolles, 1997, as cited i n Spreen & Strauss, 1998). The Stroop Test has been frequently used to differentiate between children with A D H D and healthy controls (Barkley et al., 1992; Loge et al., 1990; Pineda et al., 1998) and has been effective in discriminating A D H D and non A D H D individuals i n the majority o f studies conducted (see Table 2). However, similar to the previous reviewed tests o f executive functioning (e.g., C P T , W C S T ) , only the studies that included adolescents and young adults with A D H D found significant differences compared to healthy controls (Murphy et al., 2001; Schmitz et al., 2002; Seidman et al., 1997). T w o other studies using older participants, up to sixty-three years o f age, found no significant differences on the Stroop test compared to healthy controls (Johnson et al., 2001; Seidman et al., 1998). The Trail M a k i n g Test ( T M T ) is a test o f speed o f visual scanning/attention, visuomotor speed, sequencing, and mental flexibility. The T M T has two parts. Part A requires the participant to draw lines in numerical sequence (1-25) connecting 25 circled numbers placed randomly on a page. Part B also requires the examinee to draw lines i n a similar fashion, but with the addition o f having to alternate between connecting numbers (i.e., 1-13) and letters (i.e., A - L ) (i.e., connecting 1-A-2-B-3-C and so on). Part B is a more complex task than Part A because it requires divided attention, set shifting, and maintaining two different streams o f information in working memory. Moreover, besides switching between numbers and letters i n Part B , the actual distances between the circles are larger (Spreen & Strauss, 1998). Both Parts A and B are timed, and feedback is given to the examinee i f an incorrect move is made (e.g.,  25  connecting out o f sequence) and the participant is required to continue with the correct connection. The score reflects the time to completion in seconds (Johnson et al., 2001). Normative data for the Trail M a k i n g test demonstrates that both parts o f the test ( A & B ) are sensitive to age, education, and intelligence (Salthouse & Fristoe, 1995). However, Part B is more sensitive to age-related declines and differences i n intelligence, which likely reflects the differing cognitive demands between the two tasks. The reported correlation between Part A and B is only .49 (less than 2 5 % o f the variance i n performance), suggesting they are underpinned by substantially different cognitive functions (Heilbrormer, Henry, Buck, Adams, & Fogle, 1991; as cited i n Spreen & Strauss, 1998). Similar to the children's A D H D literature, studies comparing the performance o f adults with A D H D to clinical or n o n - A D H D control samples show inconsistent results (Barkley et al., 1992). Specifically, two studies in the review demonstrated that adults with A D H D performed significantly more poorly than healthy controls on both Part A and Part B o f the T M T (Murphy, 2002a; Woods, Lovejoy, Stutts et al., 2002). In contrast, Walker et al. (2000) found no difference on Parts A or B when they compared adults with A D H D to either healthy controls or a psychiatric group. Finally, Johnson et al. (2001) administered the T M T to adults with A D H D and n o n - A D H D controls and found that the A D H D group performed significantly more poorly on Part B , but not on Part A . The authors suggest the reason for this discrepancy was that Part B is a more complex task with far greater cognitive demands, and is therefore more sensitive to differences between adults with A D H D and healthy controls. Language Skill Tests. Measures o f verbal fluency require an individual to generate words associated with a certain letter (phonemic verbal fluency - e.g., g= golf, gift, great) or a certain category (semantic verbal fluency - e.g., animals = dog, horse, cat) in a fixed amount o f  26  time (typically 60 seconds). Verbal fluency tests have shown mixed results i n distinguishing children with A D H D from n o n - A D H D controls (e.g., Barkley et al., 1992). The results with adults have been mixed, too (see Table 2). The Controlled Oral W o r d Association Test ( C O W A T ) was the only test used to measure verbal fluency i n the adult A D H D literature reviewed. O f the studies reviewed, three demonstrated significant differences i n C O W A T performance between adults with A D H D and n o n - A D H D controls (Murphy et al., 2001; Walker et al., 2000; Woods, Lovejoy, Stutts et al., 2002), and one study found no differences (Johnson et al., 2001). Significant differences i n performance between adults with A D H D and n o n - A D H D controls on the C O W A T are likely due to the identified deficits i n the functioning o f frontal systems i n A D H D that are tapped by the C O W A T ' s demands on sustained attention to stimuli, organization, and retrieval o f verbal information (Woods, Lovejoy, & B a l l , 2002). Similar to the poor discriminatory power o f other tests o f executive function in differentiating A D H D performance from the performance o f psychiatric groups (e.g., W C S T , Stroop test), Walker et al. (2000) reported that performance on the C O W A T did not distinguish adults with A D H D from psychiatric controls. Thus, as suggested in Table 2, results o f studies examining differences between A D H D and non A D H D individuals using the C O W A T have yielded rather equivocal results, with some studies showing significant difference and some not. Learning and Memory Tasks. Verbal list learning difficulties are commonly identified in adults with A D H D . A s a result, list learning tests are the most widely used measures i n studies o f learning and memory i n the A D H D population (Seidman et al., 1997; Seidman et al., 1998; Woods, Lovejoy, Stutts et al., 2002). The California Verbal Learning Tests ( C V L T , C V L T - I I , C V L T - C ) are the most popular memory tests used with this population. The C V L T is  27  constructed to provide an assessment o f the strategies and processes involved in learning and remembering verbal material. The 16 items included in the C V L T (e.g., items from a shopping list) are presented five times to the examinee. A distractor list is then administered once, after which short delay free and cued recall, long-delay free and cued recall, and recognition memory trials are administered (Woods, Lovejoy, Stutts et al., 2002). Both Seidman et al. (1998) and Woods, Lovejoy, Stutts et al. (2002) reported that adults with A D H D performed significantly more poorly than n o n - A D H D controls on aspects o f the C V L T , including the total words learned after five learning trials and in their use o f semantic clustering. However, although they learned fewer words initially, they retained the same percentage o f the total words they learned after a long delay. One possible interpretation for the above findings is that adults with A D H D lack the ability to discern and/or use the inherent semantic structure o f the groups o f words i n the list (e.g., tools, articles o f clothing) to aid i n the organization o f material to be learned (Woods, Lovejoy, & B a l l , 2002). A s a result, adults with A D H D appear to have deficits in the encoding o f verbal information, but not with the storage or retrieval o f the material. This profile o f impairment is evident in the children's literature as well. The poor use o f efficient semantic clustering learning strategies is proposed . to reflect the frontal-subcortical impairment believed to underpin the deficits o f individuals with A D H D (Woods, Lovejoy, & B a l l , 2002). This pattern o f performance does not seem to be reflected in tests o f visual learning and memory (Kovner et al., 1998; Murphy, 2002a). Only one o f the reviewed studies, using the Visual Reproduction subtest o f the W M S - R , found that adults with A D H D performed more poorly than a control group (Johnson et al., 2001). In contrast, other studies using different tests of visual memory (e.g., Benton Test, Rey-Osterrieth Complex Figure Test) did not find any  28  differences between adults with A D H D and n o n - A D H D controls (Kovner et al., 1998; Murphy, 2002a; Seidman et al., 1998). This may reflect the fact that visual tests, unlike the verbal list learning paradigm, do not appear to have an obvious advantageous learning strategy. Tests of Intelligence. A s illustrated in Table 2, tests o f intelligence (IQ) have not been successful in discriminating between adults with A D H D and n o n - A D H D controls (Seidman et al., 1998; Walker et al., 2000). However, most o f the studies used only estimates o f intelligence based on either oral reading tests (e.g., Shipley test) or short-forms o f intelligence tests (e.g., Kovner et al., 1998; Walker et al., 2000), thus reducing the possibility o f finding differences.. However, Murphy and colleagues (2001) found that, after controlling for IQ, differences found on tests o f executive functioning between young adults with A D H D and n o n - A D H D controls did not retain their significance. Similarly, Woods et al. (2002) applied an alternative method o f neuropsychological test interpretation by using an intra-individual discrepancy analysis. They examined the differences between adults with A D H D and n o n - A D H D controls in terms o f their intellectual functioning and performance on a battery o f six tests measuring executive functioning. Significant discrepancies between the adults with A D H D and n o n - A D H D controls were found between their IQ estimates and multiple tests o f executive functioning. The Freedom from Distractibility Index (i.e., Arithmetic and Digit Span subtests) from the W A I S - R and the WAIS-III has been used successfully to distinguish between adults with A D H D and n o n - A D H D controls (e.g., Kovner et al., 1998; Woods, Lovejoy, Stutts et al., 2002). Moreover, the Digit Symbol Subtest from the W A I S - R and the WAIS-III has also shown success i n identifying differences in adult A D H D research (e.g., Murphy et al., 2001; Walker et al., 2000). However these findings are not consistent (e.g., Seidman et al., 1998).  29  The use o f intellectual measures for identifying individuals with A D H D is a contentious issue (Woods, Lovejoy, & B a l l , 2002). M a n y researchers question the utility o f studies reporting significant differences on measures o f intelligence due to the fact that many measures of IQ are composed o f tasks that are sensitive to attentional deficits and executive functions. A s a result, these findings could potentially be explained by impairments in attention, and or frontal/executive functions, rather than differences i n IQ (Woods, Lovejoy, & B a l l , 2002). Summary  In summary, research has produced variable results i n terms o f the utility o f neuropsychological measures for differentiating individuals with A D H D from n o n - A D H D controls. A detailed review o f the literature indicates that the most success to date has been found in discriminating  children with A D H D  from healthy controls. Studies o f adolescents and  young adults are somewhat weaker, with the most variable findings reported i n the adult A D H D literature. Even greater difficulty has been encountered when neuropsychological tests are used to discriminate persons with A D H D from other clinical populations such as psychiatric patients. This is likely a result o f the overlapping deficits in attention and executive dysfunction, as is seen, for example, i n schizophrenia, and the fact that the poorly defined construct o f executive functioning reflects a number o f higher-order cognitive abilities which are predicated on more basic cognitive functions such as attention and memory abilities. Further, the fact that the neuropsychological literature continues to reflect poor general agreement as to what abilities constitute the executive functions compounds the difficulty faced by researchers. Existing tests o f executive functioning are often confounded to some degree by the need to assess the executive functions in association with tasks that utilize other nonexecutive cognitive abilities (for example, set shifting on the Trails B task is assessed v i a visual  30  scanning and graphomotor ability). Further, many o f the tests used by researchers lack good psychometric data (Lezak, 1995). This is perhaps one o f the most serious weaknesses i n the rapidly growing field o f clinical neuropsychology, and is also attributed to the lack o f consensus on the definition o f executive functions. The literature also reflects a number o f additional significant methodological limitations. Specifically, poor research design, small sample sizes (no more than 20 participants), poor control for medications, poor gender control, poor age control, lack o f IQ control, and very limited investigation o f the impact o f the subtypes o f A D H D on neuropsychological performance. One trend that clearly emerges from the overall literature is that neuropsychological batteries composed o f tests o f a number o f different cognitive abilities, with executive functioning components, appear to be more successful at discriminating the cognitive effects o f A D H D from the performance o f n o n - A D H D controls and o f other clinical populations. However, battery approaches tend to be time consuming, expensive and burdensome, and as a result the cost-benefit ratio for large-scale screening and diagnosis o f A D H D tends to be poor. Research in this area is ongoing, but there appears to be a clear need for a rapid, objective, and cost effective screening approach that can reliably identify the cognitive profile associated with A D H D from n o n - A D H D controls and other clinical populations. Rationale for the Current Study Due to the multiple cognitive deficits associated with A D H D , there is a need for tests that cover a broad array o f attentional and executive functions. A s many authors have identified, neuropsychological assessment i n the adult A D H D population w i l l be most useful when multiple cognitive constructs are assessed (Alexander & Stuss, 2000; Barkley, 1997;  31  Johnson et al., 2001; Schmitz et al., 2002; Seidman et al., 1998). Most neuropsychological tests require specialized training to administer and score, and can be very time consuming to administer. Computerized testing has a number o f advantages over traditional pencil and paper tests, including greater reliability due to decreased variability in administration, and more precise response recording. Moreover, the administration o f standardized examineradministered neuropsychological tests requires a substantial amount o f training. Disadvantages of computerized testing include the absence o f behavioral observations (i.e., qualitative information) during the test process, and the poorly understood and investigated influence o f using a computer interface and administration method on performance characteristics. I m P A C T , the test used for this study, is a 20-25 minute computerized battery that is sensitive to subtle cognitive problems, such as those associated with concussions i n sports (Lovell et al., 2003;. Lovell, Collins, Iverson, Johnston, & Bradley, 2004). If I m P A C T could also be demonstrated to be sensitive to the problems associated with A D H D , it might be useful in clinical practice and research, and especially in clinical trials involving medications. Given its brevity, minimal practice effects, and multiple alternate forms, it also has the potential to be very useful in longitudinal A D H D research. This thesis w i l l contribute to the literature by examining whether I m P A C T is sensitive to cognitive problems i n young adults with A D H D . This study does not overcome all o f the noted methodological limitations associated with previous research. However, it does have an adequate sample size for the statistical analyses, samples across one age group, and compares young adults with A D H D with n o n - A D H D controls matched on several relevant demographic variables (i.e., age, gender, education). A s such, it takes significant steps towards overcoming some o f the methodological limitations that exist i n the extant A D H D literature.  32  Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT)  I m P A C T (Maroon et al., 2000) was developed to address the need for rapid screening of the large number o f athletes pre-season and after experiencing concussions. This battery was designed to address the limitations associated with traditional neuropsychological testing i n sports (e.g., administration time, expense, practice effects). Prior to 1998 there were few neuropsychological test batteries developed specifically for use with athletes. I m P A C T is composed o f a demographic questionnaire, injury evaluation form, symptom inventory, and a neuropsychological test battery (Collins et al., 2002; L o v e l l et al., 2003). The neuropsychological test battery consists o f seven individual test modules (word discrimination, symbol memory, color click, symbol matching, color word match, sequential digit tracking, and visual attention span) that measure aspects o f cognitive functioning including attention, memory, reaction time, processing speed, and impulse control. Composite scores for the test modules are computed by standardized formulas derived from the results o f seven cognitive tasks (Collins et al., 2003). The seven modules can be administered as a complete test battery, or can be administered individually (Maroon et al., 2000). Various indices o f performance are derived from these seven tasks, and can be combined to yield four composite scores, reflecting the individual's reaction time, memory, processing speed, and impulse control. The tasks involved in each module, and the indices included in each composite, are described in greater detail i n the methods section. The I m P A C T battery includes a Post-Concussion Scale that is frequently used i n both amateur and professional sports (Collins et al., 2003; Collins et al., 2002; Iverson, Gaetz, L o v e l l , & Collins, 2004a, 2004b). The Post-Concussion Scale asks each participant to report on 22 symptoms (e.g., headaches, dizziness, problems with sleep, irritability, sadness, feeling  33  slowed down, difficulties concentrating, poor memory, visual problems) using a 7-point Likert scale (i.e., 0-6). The present study examined whether young adults with A D H D endorse more symptoms with greater severity in total than a group o f matched n o n - A D H D controls. Symptoms included on the questionnaire that are known to be associated with A D H D (e.g., difficulty concentrating) are o f particular interest to the present study. ' I m P A C T was designed as a rapid screening tool to permit the evaluation o f a large numbers o f athletes in a limited time. A s such, the I m P A C T test battery is brief (approximately 20 to 25 minutes for baseline evaluations) and does not evaluate all cognitive functions (e.g., it does not include tests o f intelligence, achievement, or language). I m P A C T was initially constructed to evaluate the areas o f cognitive functioning most likely to be affected after cerebral concussions. When an individual experiences a concussion, cognitive functioning is disrupted. Immediately following the concussion, individuals are found to have difficulties i n the areas o f orientation, attention, executive functioning, information processing, mental set shifting, concentration, and memory (Delaney, Lacroix, Gagne, & Antoniou, 2001; Erlanger, Kutner, Barth, & Barnes, 1999). Although I m P A C T was not specifically designed to screen for cognitive functioning in A D H D , it evaluates areas o f cognitive functioning with tests that have been demonstrated to discriminate between individuals with A D H D and n o n - A D H D controls (e.g., verbal list learning, response inhibition, sustained attention; Johnson et al., 2001; Walker et al., 2000; Woods, Lovejoy, Stutts et al., 2002). I m P A C T is automatically computer scored. The test stimuli are randomized from one testing session to another. This allows for the test battery to be used repeatedly over short intervals, while controlling for practice effects (Iverson, Lovell, Collins, & N o r w i g , 2002;  34  Maroon et al., 2000). Most examiners can administer the battery after a few hours o f instruction and review o f materials, and little supervision o f the test-taker is required (Maroon et al., 2000). I m P A C T has been used in several studies o f concussion i n amateur athletes, and has been shown to be sensitive to the immediate effects o f concussion, and to reliably identify rapid improvement i n functioning (Collins et al., 2003; Collins et al., 2002; Iverson et al., 2004a, 2004b; L o v e l l et al., 2003; L o v e l l et al., 2004). Several aspects o f the reliability (e.g., test-retest reliability) and validity o f I m P A C T have been investigated (Iverson, L o v e l l , & Collins, 2002; Iverson, L o v e l l , Collins et al., 2002; Iverson, L o v e l l , Podell, & Collins, 2003). Iverson, L o v e l l , Podell, and Collins (2003) summarized the reliability and validity data for version 1.0 o f I m P A C T . The reliability studies have addressed test-retest reliability and the determination o f reliable change. It is not possible to assess internal consistency on the individual subtests or the composite scores because individual subtest responses cannot be downloaded from the program, and the composite scores are composed o f a small number o f subtest scores (thus, they are not amenable to reliability analyses). The test-retest reliability and estimates o f reliable change have been presented for version 1 and version 2 o f I m P A C T (Collins et al., 2003; Iverson, Lovell, & Collins, 2002, 2003). Reliable Change methodology uses statistical formulae to identify whether change in an individual's performance on a measure with repeated testing is the result o f a "true" change in their performance, or remains within the confidence interval associated with the instrument's measurement error. In contrast, test-retest reliability provides an index o f the consistency with which a measure evaluates a given function on repeat testing (i.e., how well results from testing at time 1 relate to testing at time 2; Hageman & Arrindell, 1993; Heaton et al., 2001; Jacobson & Truax, 1991; Temkin, Heaton, Grant, & Dikmen, 1999).  35  Test-retest reliability and reliable change estimates were derived from 49 amateur athletes tested over three occasions. The second administration o f the test was given an average o f 14 days (Range = 7-21 days) after baseline testing. The correlation coefficients from Time 1 to Time 2 ranged from .54 - .76 for the composite scores. The third administration was given approximately 4.5 days (Range = 2-7 days) after the second testing, and the correlation coefficients from Time 2 to Time 3 ranged from .48 - .68 for the composite scores. Iverson, L o v e l l , and Collins (2005) conducted a study on the construct validity o f I m P A C T . They compared I m P A C T (version 2.0) to a traditional neuropsychological measure, the Symbol Digit Modalities Test ( S D M T ) . The S D M T is a test o f visual scanning, visuomotor ability, attention, and speed o f processing. It has similar task demands as the Trail M a k i n g Test Part A , and the Digit Symbol (Coding) Test (Spreen & Strauss, 1998). The authors hypothesized that the Processing Speed and Reaction Time Composites o f I m P A C T would correlate most highly with the Symbol Digit Modalities Test. Results from the analyses suggested that the S D M T , Reaction Time Composite, and Processing Speed Composite from I m P A C T were measuring similar constructs, demonstrating some preliminary convergent validity (Iverson et al., 2005). Because the Processing Speed and Reaction Time Composites from Version 1.0 o f I m P A C T are identical to that o f Version 2.0, the results o f this research are relevant to the current study. The ongoing validation o f a new test is a lengthy and timeconsuming process (Lezak, 1995). Future validity research on I m P A C T needs to examine its convergent and discriminant validity with other tests (Iverson et al., 2005). The validity o f I m P A C T as a battery that measures sports-related concussion has been examined (e.g., Iverson, L o v e l l , & Collins, 2002). Amateur athletes (N= 120) who had completed pre-season testing were re-evaluated within three days o f having a concussion.  36  Divergent validity was studied through an intercorrelation matrix o f the composite scores at preseason and post injury. A t preseason the only statistically significant correlation was between the Reaction Time and Processing Speed (r =.35). A t post injury, there were significant, but small, correlations between Memory and Reaction Time (r =-.27), Memory and Processing Speed (r = .35), and Reaction Time and Processing Speed (r = .32). These results suggest that the composite scores do not share a great amount o f variance, and are therefore capturing predominately different aspects o f cognitive functioning. To date, the psychometric data available for I m P A C T is quite limited. M u c h additional research is needed. The battery appears to have adequate test-retest reliability, solid estimates of reliable change, and it is sensitive to the acute effects o f concussions i n high school and university students. In young people with A D H D , there is a substantial overlap i n terms o f the identified areas o f compromised cognitive functioning evaluated by I m P A C T ; thus, there might be potential utility o f the I m P A C T battery in the A D H D population. I m P A C T measures several areas o f cognitive functioning that adults with A D H D appear to show deficits (e.g., attention, memory, reaction time, and processing speed; Epstein et al., 2001; Kovner et al., 1998; Murphy et al., 2001; Murphy, 2002b; Seidman et al., 1998; Walker et al., 2000; Woods, Lovejoy, Stutts et al., 2002). The sensitivity o f this computerized battery to the subtle effects o f concussion suggests that the battery may also be useful for identifying cognitive problems associated with A D H D . One study has been conducted with adolescents with A D H D . Iverson and Strangway (2004) examined I m P A C T version 2.0 performance in a sample o f 38 adolescents with A D H D and 38 n o n - A D H D students matched for age, education, gender, and history o f head injury. The average age o f the students was 15.5 years (Range = 13-19) and their average education was 9.1 years (all were i n grades 8-12). The  37  majority o f the participants were boys (92%). A l l participants were derived from the I m P A C T normative sample. The students with suspected A D H D were not diagnosed through structured interviewing or testing; a psychologist did not evaluate them. Each individual i n the A D H D group was identified from their self-reported responses on the demographic questionnaire, which asked them to identify (yes/no) whether or not they had ever been diagnosed with attention deficit hyperactivity disorder ( A D H D ) or attention deficit disorder ( A D D ) . Results from the study revealed significant differences between the control and A D H D groups in terms of their performance on the visual memory, processing speed, and impulse control composite scores. The groups did not differ significantly i n terms o f their verbal memory or reaction time composites. The results are similar to those found by Seidman and colleagues (1997) who used a comparable sample, and investigated the cognitive task performance o f a group o f young A D H D males (aged 9 to 22) and n o n - A D H D controls using standard neuropsychological tests. The individuals with A D H D performed significantly more poorly on a task o f visual memory, and on tasks o f concentration/executive functioning primarily involving components o f impulse control (Stroop test), and problem solving, set shifting, and cognitive flexibility ( W C S T ) . N o differences were found between the two groups on a verbal list learning task ( C V L T ) or a reaction time task (CPT). Schmitz et al. (2002) reported similar findings when they compared a group o f adolescents with A D H D to n o n - A D H D controls on measures o f neuropsychological performance. These, and a number o f additional studies, suggest that neuropsychological impairments identified i n children with A D H D continue into adulthood (e.g., Halperin et al., 1990; Konrad et al., 2000; Kupietz, 1990; Loge et al., 1990; Seidel & Joschko, 1990; van der Meere & Sergeant, 1988).  38  Hypotheses  The purpose o f the study was to examine the potential utility o f I m P A C T for distinguishing A D H D and n o n - A D H D individuals in a sample o f young adults. The participants were matched on education, gender, and history o f head injury. The study investigated whether the A D H D and matched controls displayed cognitive differences i n terms of their concentration, memory, reaction time, processing speed, and impulse control as measured by I m P A C T . O f additional interest was whether self-reported cognitive difficulties, as reported on I m P A C T ' s Post-Concussion Scale, distinguished between A D H D and nonA D H D participants. The specific hypotheses for this study are listed below: 1) Young adults with A D H D w i l l perform significantly more poorly on the memory composite than matched n o n - A D H D controls. Adults with A D H D appear to have deficits in the encoding and retrieval o f verbal information, primarily related to executive aspects o f efficient memory strategy and verbal organization skills (e.g., semantic versus phonemic chunking o f information). Moreover, verbal memory deficits are one o f the most common difficulties identified i n adults with A D H D (e.g., Seidman et a l , 1997; Seidman et al., 1998; Woods, Lovejoy, Stutts et al., 2002). Some researchers have reported deficits on visual memory tests, too (Johnson et al., 2001). 2) The reaction time score for the young adults with A D H D w i l l not be significantly different than the normative comparison group. Reaction time tests have received little attention in the adult A D H D literature. However, Johnson et al. (2001) found that adults with A D H D performed more slowly than n o n - A D H D controls on a reaction time task (3RT) as the task became more complex. Only one other study (Murphy, 2002a) used a measure o f simple reaction time ( G S R T ) and found that the test did not  39  discriminate adults with A D H D from controls. The most commonly used test to assess reaction time in the adult A D H D literature is the Continuous Performance Test (CPT). However, the C P T is not an explicit test o f reaction time. Rather, reaction time is measured "incidentally" (i.e., the participant is not asked to solely respond to a stimulus as quickly as they can - because they are also required to monitor for " X ' s " to which they do not respond; Epstein et al., 1998; Epstein et al., 2001). For the purposes o f the C P T , variability i n reaction time over the duration of the task is used to identify inconsistent attentional patterns, or attention/arousal that diminishes over time. Further, the majority o f the studies using the C P T to evaluate reaction time have not demonstrated significant differences between adults with A D H D and controls (Fischer et al., 1990; Murphy et al., 2001; Seidman et al., 1997). Iverson and Strangway (2004) reported no differences between young people with A D H D and controls on version 2.0 o f I m P A C T . Because the literature does not appear to support reaction time differences between n o n - A D H D controls and individuals with A D H D , there is no empirical reason to expect that they would differ in terms o f reaction time on I m P A C T . Hence it is expected that they w i l l follow the pattern o f previous literature and perform similarly. 3) The processing speed composite w i l l be significantly slower for young adults with A D H D compared to n o n - A D H D controls. Tests o f psychomotor speed have shown limited utility in discriminating between adults with A D H D and n o n - A D H D controls (Seidman et al., 1998; Walker et al., 2000). However, because results from Iverson and Strangway (2004) using I m P A C T version 2.0 demonstrated differences on the processing speed composite score between adolescents with A D H D and nonA D H D controls, there is some reason to believe that the I m P A C T processing speed composite w i l l discriminate between young adults with A D H D and n o n - A D H D controls.  40  4) Y o u n g adults with A D H D w i l l score significantly more poorly than the control group on the impulse control composite. Two traditional neuropsychological tests ( C P T and Stroop Test) have been typically used to measure impulse/inhibitory control, and have been frequently used to differentiate between children with A D H D and n o n - A D H D controls (Barkley et al., 1992; Loge et al., 1990; Pineda et al., 1998). The C P T has generally been successful at distinguishing adults with A D H D from N o n - A D H D controls by measuring impulse control through errors o f commission (i.e., responding to a target stimuli when withholding o f response is required; Epstein et al., 1998; Murphy et al., 2001; Walker et al., 2000). The Stroop task measures inhibition by requiring the participant to suppress their prepotent (overlearned) reading response. The most numerous significant results differentiating participants with A D H D from controls with Stroop-type tests are reported i n studies that include only adolescents and young adults with A D H D (Schmitz et al., 2002; Seidman et al., 1997). Similarly, using version 2.0 o f I m P A C T , Iverson and Strangway (2004) found significant differences between adolescents with A D H D and n o n - A D H D controls. These (  •  findings provide some empirical basis to believe that the I m P A C T Impulse Control composite score w i l l differentiate between the A D H D and control group. 5) Y o u n g adults with A D H D w i l l report significantly more symptoms on the Post-Concussion Scale than controls. Adults with A D H D self-report more psychiatric symptoms than N o n - A D H D controls (e.g., feeling down, feeling irritable, feeling depressed; Woods, Lovejoy, & B a l l , 2002), and other symptoms tapped by the Post-Concussion Scale overlap with common symptoms o f A D H D (e.g., trouble concentrating and trouble with memory). A s such, the Post-Concussion  41  Scale is likely to reflect elevated scores in A D H D because it is expected that they w i l l endorse many o f the symptoms with more frequency than N o n - A D H D controls. Methodology Participants From an initial database o f 2, 389 subjects, 84 were identified as having self-reported A D H D . O f these subjects, 68 had complete data (e.g., 9 were missing data on education). The normative database for I m P A C T ( N = 1, 746) was then used to select a matched group o f 68 n o n - A D H D controls. Participants were matched precisely on education, gender, and number o f previous concussions. Each group had 88% males and 12% females. The average number o f completed years o f education was 12.3 ( S D = 2.0) for the A D H D group and 12.3 ( S D = 2:0) for the control group. The average number of previous concussions was .68 ( S D = 1.3) for the A D H D group and .62 ( S D = 1.2) for the control group. The breakdown o f self-reported educational problems i n the A D H D group was as follows: repeated a grade = 7.4%, reading problem = 22.1%, spelling problem = 25.0%, math problem = 17.6%, and recipient o f special education services = 16.2%. The control subjects, by selection criteria, did not have any selfreported educational problems. For the total sample, 39% percent were i n high school and 6 1 % were in university. The breakdown of participants by highest grade completed was as follows: Grade 9 = 13.2%, Grade 10 = 18.4%, Grade 11 = 13.2 %, Grade 12 = 22.1%, 1 year university = 20.6%, 2 st  8.1%, 3 year = 13.2%, and 4 year = 4.4%. rd  th  42  n d  year =  Procedure  A l l participants completed Version 1.0 o f I m P A C T as part o f a larger collection o f normative data for I m P A C T . The testing was done i n group settings (e.g., computer labs i n schools). Each administration o f I m P A C T took approximately 20-25 minutes. The students with self-reported A D H D were not diagnosed through structured interviewing or testing; and a psychologist did not evaluate them. This is a sample o f convenience, derived from a normative database. The students were identified as having A D H D by their self-reports in the demographic questionnaire. Specifically, the students were asked whether or not they had ever had a diagnosis o f attention deficit hyperactivity disorder ( A D H D ) or attention deficit disorder (ADD).  .  Measures  The following section provides a detailed description o f I m P A C T . This program contains a demographic questionnaire, current symptoms questionnaire, and a neuropsychological screening battery. The first section o f I m P A C T is the Subject Profile and Health Questionnaire. It requires the participant to input basic demographic and descriptive information including their name, date o f birth, age, sex, grade level, and first language. It also requires the individual to report their height, weight, handedness, sport, and whether or not they have ever had a concussion. In addition, the questionnaire requires the test-taker to report whether or not they have received any speech therapy, attended special learning classes, repeated one or more years o f school, or been diagnosed with A D H D . Section two o f I m P A C T pertains to "Current Symptoms and Conditions", or what is referred to as the Post-Concussion Scale. The Post-Concussion Scale asks each participant to  43  report on 22 concussion-related symptoms on a 7-point Likert scale (i.e., 0-6) identifying the degree o f difficulty, i f any, they are having with each symptom (e.g., problems with sleep, irritability, sadness, feeling slowed down, difficulties concentrating, poor memory, visual problems). The Post-Concussion Scale is reprinted i n Table 3.  44  Table 3 Post-Concussion  Scale  Symptom  Minor  Severe  Moderate  Headache  1  2  3  4  5  6  Nausea  1  2  3  4  5  6  Vomiting  1  2  3  4  5  Balance Problems  1  2  3  4  5  6  Dizziness  1  2  3  4  5  6  Fatigue  1  2  3-  4  5  6  Trouble Falling Asleep  1  2  3  4  5  6  Sleeping M o r e Than Usual  1  2  3  4  5  6  Sleeping Less Than Usual  1  2  3  4  5  6  Drowsiness  1  2  3  4  5  6  Sensitivity to Light  1  2  3  4  5  6  Sensitivity to Noise  1  2  3  4  5  6  2  3  4  5  6  Irritability  K  •  6  Sadness  1  2  3  4  5  6  Nervousness  1  2  3  4  5  6  Feeling M o r e Emotional  1  2  3  4  5  6  Numbness or Tingling  1  2  3  4  5  6  Feeling Slowed D o w n  1  2  3  4  5  6  Feeling Mentally "Foggy"  1  2  3  4  5  6  Difficulty Concentrating  1  2  3  4  5  6  Difficulty Remembering  1  2  3  4  5  6  1  2  3  4  5  6  Visual Problems Note:  Participants checked a box i i "they wer e"not exp eriencing the sympl om." The sum o f all responses on the Post-Concussion Scale was used to create a total post-  concussion score (range = 22-132), with higher scores indicating a larger proportion o f symptoms present during the test administration. For each item, scores ranged from 0-6 with  45  higher scores indicating more severe difficulties. The internal consistency o f the entire scale as estimated with Cronbach's alpha was .92 (M =8.54, SD = 15.14) for the total sample, .93 (M= 11.47, SD = 16.09) for the A D H D group, and .90 ( M = 5.60, SD = 8.79) for the Control group. Section three o f I m P A C T is composed o f a battery o f seven neuropsychological tests, referred to as modules. Each module contributes scores that produce four different composites (i.e., memory, processing speed, reaction time, and impulse control) that were used to assess specific aspects o f cognitive functioning as described below. The breakdown o f the scores that comprise each composite is provided i n detail, after the descriptions o f all modules. It is not possible to conduct internal consistency reliability analyses on the individual tests or the composite scores. This is because individual test responses cannot be downloaded from the program, and the composite scores are composed o f a small number o f subtest scores (from the modules) and thus are not amenable to reliability analyses. Module I Word Discrimination. The first module evaluates attentional processes and verbal recognition memory by requiring the participant to discriminate between correct and incorrect words after two acquisition trials. Twelve target words are presented for 750 milliseconds each on the computer screen. The word list is presented twice in the same order at the same rate to facilitate learning. Immediately after the second presentation the participant is given a 24-word list that is composed o f the twelve target words previously presented, and twelve non-target words. The target words are matched to the non-target words semantically (e.g., i f "knife" represents a target word, "fork" represents a non-target word). The participant responds to the words by mouse-clicking the "yes and "no" buttons on the screen to specify whether the word presented was on the previously learned list. Subsequently, in a delayed condition that follows administration o f all other test modules (approximately 20 minutes), this  46  task is re-administered using the same procedures as described above. There is no time limit for the immediate and delayed recognition portions during this module. For both the immediate and delayed assessment, the sum o f correct and incorrect responses is computed. This module contributes to the memory composite (a total percent correct score is derived) with higher scores reflecting greater word learning and memory. The presentation o f a word list in a visual format is similar to the Consortium to Establish a Registry for Alzheimer's Disease battery ( C E R A D ; Morris et al., 1989). This task is also conceptually similar to verbal list learning tasks, such as the California Verbal Learning Test ( C V L T ; Delis, Kramer, Kaplan, & Ober, 1987; Delis, Kramer, Kaplan, & Ober, 2000) and the Rey Auditory Verbal Learning Test ( R A V L T ; Rey, 1964). Module II Symbol Memory & Module III Color Click (distractor task). Symbol M e m o r y  measures visual working memory and visual processing speed. The Color C l i c k module serves as a distracter task, and is also a measure o f focused attention, response inhibition, and reaction time. Prior to beginning the visual memory task (Symbol Memory), the participant is allowed to practice the distracter task (Color Click). Color C l i c k is a choice reaction time test during which the participant is asked to click the left mouse button i f a red circle is presented and the right mouse button i f a blue square is presented. Once the participant has completed the practice task, the Symbol Memory task begins. For each o f the trials o f the memory task, a screen is displayed for 1.5 seconds that has a computer generated random assortment o f X ' s and O ' s . Three o f the X ' s or O ' s are illuminated in yellow on the screen. The participant is asked to remember the location o f the illuminated objects. Immediately after the presentation o f the three X ' s or O ' s the distracter task re-appears on the screen and distracter items (i.e., red circle or blue square) are presented for 30 seconds. Following the distracter task, the memory  47  screen ( X ' s and O's) re-appears and the participant is asked to click to identify the location o f the previously illuminated 3 objects. The participant completes 4 trials involving presentation of the X ' s and O's, followed by the distracter task, followed by recall o f the location o f the X ' s and O's. Scores are provided for the memory composite (correct identification o f the X ' s and O's), reaction time composite (reaction time for the distracter task), impulse control composite  (number o f errors on the distracter task). The Symbol Memory component o f this module is conceptually similar to the Spatial Location subtest from the Kaplan Baycrest Neurocognitive Assessment ( K B N A ; Leach, Kaplan, Rewilak, Richards, & Proulx, 2000). The task requires visual attention and visualspatial working memory. The Color-Click task (distracter task) in this module is similar to the Connors' Continuous Performance Test ( C P T ; Conners, 2002), requiring speeded responding, impulse control, and sustained visual attention and vigilance. Module IV Symbol Match. The Symbol Match module evaluates visual processing speed, learning, and memory. Initially, the participant is presented with a screen that displays nine symbols (e.g., triangle, square, and arrow). Directly under each symbol is a number button from 1 to 9. B e l o w this grid, a symbol is presented. The participant is required to click the matching number as quickly as possible, and to remember the symbol/number pairings. Correct performance is reinforced through the illumination o f a correctly clicked number i n green. Incorrect performance illuminates the number button in red. Following the completion o f 27 trials, the symbols disappear from the top grid. The symbols again appear below the grid and the participant is asked to recall the correct symbol/number pairing by clicking the appropriate number button. This module provides an average processing speed score and a score for the memory condition.  48  The first part o f this module resembles the Digit Symbol task from the Wechsler Adult Intelligence Scale, Third Edition (WAIS-III; Wechsler, 1997), and the Symbol Digit Modalities Test (Smith, 1972). Both o f these tasks are underpinned by visual processing speed, visual scanning, and learning. The second part o f the module resembles the incidental learning portion •of the Digit Symbol task on the WAIS-III (Wechsler, 1997). Module V Color-Word Match. The Color-Word Match represents a choice reaction time task, and also measures impulse control and response inhibition. The first part o f this test, a practice task, presents the participant with three squares o f different colors (i.e, red, blue and green). The examinee is asked to click on either the red, blue, or green square as the word for that color appears on the screen. This process ensures that the participant can perform the basic task o f matching a word to a color (e.g., match the word red, to the red square) ruling out colorblindness and grossly impaired reading ability. The actual test requires the examinee to click on the word (e.g., green) inside the box when it is a correct match between color and word (e.g., green word i n a green ink). This is referred to as a congruent match. The examinee is required to inhibit or not respond when the word presented does not match the ink color. This is referred to as an incongruent match (e.g., the word green printed in red ink). A new stimulus (i.e., colored word in a box) is presented for two seconds with a one-second delay between the stimuli. In addition to providing a reaction time score, this task also contributes to the impulse control composite providing both omission (failing to click on a'congruent match) and commission error (clicking on an incongruent match) scores. This test measures impulse control and incidental reaction time. It relies on the examinee inhibiting an automatic word reading response in favor o f a more novel response (i.e., identifying the ink color). It is very similar to the traditional Stroop test (Golden, 1978).  49  Module VI Sequential Digit Tracking/Trigram  Memory. The Sequential Digit Tracking  module measures working memory and visual-motor response speed. First, the participant is allowed to practice the distractor task, which consists o f 25 numbered buttons ( 5 x 5 grid). The participant is instructed to click as quickly as possible on the numbered buttons in backward order starting with "25." Once the participant has completed this initial practice task, he/she is presented with three consonant letters that are displayed on the screen and instructed to remember them. Immediately following display o f the three letters, the numbered grid reappears and the participant is instructed to click the numbered buttons i n backward order as quickly as possible. After a period o f 18 seconds, the numbered grid disappears and the participant is asked to recall the three letters by typing them from the keyboard. Both the number placement on the grid and letters displayed are randomized for each trial.. Five trials o f this task are presented for each administration o f the test. This module yields a memory score (total number o f correctly identified letters) and a processing speed score (average number o f correctly clicked numbers per trial from the distractor test). The three-letter task is similar to the Brown-Peterson short-term memory paradigm (Brown, 1958; Peterson & Peterson, 1959); it is also called the Auditory Consonant Trigrams Test (Mitrushina, Boone, Razani, & D ' E l i a , 2005). The speeded distractor task is conceptually similar to the Trail M a k i n g Test-A ( T M T - A ; Reitan & Wolfson, 1993), which is a visual motor task involving scanning and graphomotor speed. Module VII Visual Attention Span. The Visual Attention Span module evaluates visual attention span under two conditions: forward span and backward span. During the forward span task, the examinee is presented with a 3 x 3 grid o f square buttons. The buttons are highlighted in random order. The examinee is required to remember the order and mouse click on the  50  correct sequence. Following a sample item, four trial sequences are presented. Each sequence involves more grid items to be repeated, with the final trial including nine squares. The backward span task is identical to the forward span condition, except that the participant is required to click on the presented sequence i n backward order. The task begins with a sequence of two highlighted squares within the grid, and progresses until the participant reaches a maximum o f eight squares to remember. Both the forward and backward component are discontinued once the participant fails two trials i n a row at any level. T w o scores from this module are calculated, which contribute to the memory and processing speed composites. This task is modeled on, and essentially identical in nature to, the W M S - I I I Spatial Span task. ImPACT Composite Scores. Performance across tasks on I m P A C T yielded four overall composite scores for each participant: Memory Composite, Reaction Time Composite, Processing Speed Composite, and Impulse Control Composite. The breakdown o f the module scores that contribute to each composite is provided below: 1. The Memory Composite is comprised o f the average o f the following scores: (a) Word Discrimination total percent correct, (b) Symbol Match-Total correct hidden symbols, (c) Sequential Digit Tracking total percent o f total letters correct, (d) V i s u a l Attention Span- Total percent o f numbers correct (forwards and backwards), and (e) Symbol Memory total percent o f X ' s and O ' s correct. 2. The Reaction Time Composite is comprised o f the average o f the following scores: (a) Symbol Memory X ' s and O's-Average correct R T (interference), (b) Symbol Match-Average correct RT/3 and, (c) Color Click-Average, correct R T .  51  3. The Processing Speed Composite is comprised o f the average o f following scores: (a) Symbol Memory-total correct (interference)/4, (b) Sequential Digit Tracking Three-lettersAverage counted correctly*3, and (c) Visual Attention Span. 4. The Impulse Control Composite is comprised o f the average o f the following scores: (a) Symbol Memory-total incorrect- (interference), and (b) Color Match total commissions. Analyses The dependent variables were first examined for skewness and kurtosis, and transformations were performed on any variables that violated the assumptions o f normality. Bivariate correlations (Pearson) among the composite variables o f I m P A C T were calculated to establish the degree o f association among the dependent variables. In order to evaluate whether the matched groups ( A D H D and n o n - A D H D ) differed across the six dependent variables evaluated i n this study, dependent t-tests were conducted for each o f the variables (i.e., Post-Concussion Scale, Memory Composite, Reaction Time Composite, Impulse Control, and Processing Speed Composites). The dependent t-test is the most appropriate (i.e., robust) calculation to test the null hypotheses i n a matched groups design. Statistically, the dependent t-test is almost identical to the independent t-test, except that it takes into account the degree o f correlation between the two groups. Large correlations between the two groups on the dependent measures reduces the size o f the error variance, making the t-test more powerful. Effect sizes for each comparison are reported using the original (untransformed) means and standard deviations for the A D H D and control group. In addition, analyses are conducted to determine whether self-reported academic problems or participation in special education was related to performance on I m P A C T (i.e., participants  52  taking special classes for reading). Lastly, for exploratory purposes, the three symptoms from the Post-Concussion Scale dealing with cognitive difficulties (feeling mentally foggy, poor concentration, and poor memory) were combined to examine whether or not the A D H D subjects endorse significantly greater cognitive difficulties than the control group.  Results  The descriptive statistics for the composite scores are presented i n Table 4. Several variables violated assumptions o f normality, and showed significant skewness and kurtosis including the Post-Concussion Scale, Memory Composite, and Impulse Control Composite. Variables were deemed to exhibit significant skewness and/or kurtosis i f the z-scores associated with these indices were outside the range o f +/-3. Variables with a significant KolmogorovSmirnov statistic (p < .05) were considered to violate assumptions o f normality. To correct for these violations o f normality, these variables were transformed using the square root method as an alternative to the logarithmic transformation because some o f the data points were 0, and therefore undefined in a logarithmic transformation. Instead o f adding a constant o f 1 to these variables, the more conservative square root method o f transformation was applied. Square root transformation o f the variables did not alter the significance o f any o f the relationships among the data on the dependent t-tests. A s a result, the means and standard deviations o f the untransformed data were used for all analyses. This is preferable, because the square root transformation o f the variables alters their natural distribution, general by artificially compressing high data points in a non-systematic way (e.g., a participant score might greatly exceed their matched control's score, resulting i n the scores being altered in a  53  non-systematic way). Furthermore the t-test is relatively robust to violations o f assumptions, especially when sample sizes are above twenty (Tabachnick & Fidell, 2001). Table 4 Descriptive statistics for the ImPACT  Mean  composite scores  Standard  Interquartile  Deviation  Range  Skewness  Kurtosis  KS  Symptoms  8.54  13.25  0.0-10.00  2.26  4.89  .00  Memory  86.24  10.84  79.53 - 95.49  -1.07  1.41  .00  .58  .07  .53-.62  .62  .37  .20*  Processing Speed  34.23  7.02  29.71 -38.80  .09  .29  .20*  Impulse Control  10.34  8.04  5.0-13.0  1.92  5.15  .00  Reaction Time  Note:  K S = Kolmogorov-Smirnov test of normality; * = Significant violations of normality. In assessing for univariate outliers i n the data, the standardized values revealed that  several cases were potential outliers (z > +/-3). These cases were further assessed by an examination o f the histograms, stem and leaf plots, box plots, and the raw data itself. A l l potential outliers appeared to be connected to their respective distributions, and were therefore retained as legitimate values. Intercorrelations among the dependent variables are presented in Table 5. Correlations greater than 0.9 violate assumptions related to multicollinearity and singularity. However, the bivariate correlations among the dependent measures i n the present sample were small to medium. Accordingly, each o f the six dependent measures was considered separately i n subsequent analyses.  54  Table 5 Pearson's correlation coefficients among the ImPACT composite scores  Symptoms  Memory  Reaction time  Impulse Control  Processing Speed  Symptoms Memory  -.24**  Reaction time  -.07  Impulse control Processing Speed  .15* -.15*  -.35** -.16*  -.08  .30**  -.50**  -.03  C o r r e l a t i o n is significant at the 0.01 level (1 -tailed). **Correlation is significant at the 0.05 level (1-tailed).  Dependent t-tests were conducted to evaluate differences between the adults with A D H D and the matched control group across all five dependent variables (Post-Concussion Scale, M e m o r y Composite, Processing Speed Composite, Impulse Control Composite, Reaction Time Composite. For exploration purposes, independent t-tests were also run, but not reported \ Results o f these analyses indicated that the individuals with A D H D and the control group differed significantly on the Post-Concussion Scale ( t (1, 33) = -2.46, p < .05), and the Memory Composite (t (1, 33) = 2.88, p < .05). The groups did not differ significantly on the Processing Speed Composite (t (1, 33) = .727, p > .05) or the Impulse Control Composite (t (1, 33) = -.866,/? > .05). Differences between A D H D and Control groups approached significance for the Reaction Time Composite (t (1, 33) = -.178,/? > .07). A s reported in Table 6, the effect sizes for the significant differences were medium. A n examination o f the means for these analyses (see Table 6) indicated that young adults with A D H D report more symptoms (PostConcussion Scale) and demonstrate a poorer ability across memory tasks. There was a  1 The same pattern of results were obtained when Independent t-tests were used rather than dependent t-tests.  55  nonsignificant trend for the individuals with A D H D to display slower reaction time than controls. Table 6 Descriptive statistics, significance tests, and effect sizes (Cohen's d)  ADHD  N o n - A D H D Controls  M  SD  M  SD  E  d  Symptoms  11.47  16.09  5.60  8.87  .010  .68  Memory  83.59  10.73  88.88  10.34  .004  .50  .06  .56  .06  .076  .33  Reaction Time  .58 ->  Processing Speed  33.79  7.37  34.65  6.67  .479  .12  Impulse Control  10.86  8.05  9.80  8.05  .445  .13  Given that a significant number o f individuals in the A D H D group reported academic difficulties, additional analyses were conducted to determine whether self-reports academic problems or participation i n special education systematically affected performance on I m P A C T . Due to small sample sizes for specific educational problems, participants with A D H D were sorted into binary groups: those with one or more academic problems (i.e., reading, spelling, math, repeated grade, learning assistance, or special education) versus those with no self-reported academic problems. There were 31 participants with academic problems and 37 without problems. The two groups did not differ on total symptoms, The Memory Composite, Processing Speed Composite, or the Impulse Control Composite. A D H D subjects with academic problems had slower reaction times, however [t (66) = -.26, p <.012, d = .64.].  56  For exploratory purposes, the three specific symptoms from the Post-Concussion Scale dealing with cognitive difficulties (feeling mentally foggy, poor concentration, and poor memory) were summed to create a single score (See Table 7). The A D H D subjects endorsed significantly greater cognitive problems ( M = 2.51, S D = 3.84) than the control subjects [ M = .88, S D = 2.0; t (67) = -2.98, p < ,005, d = .56]. Frequency distributions for the three scores that were significantly different between the A D H D group and the controls were examined and cutoff scores were selected. These cutoff scores represented the approximate 10 percentile for the control group. That is, 90% or more th  of the control group scored better than the cutoff. Specifically, the cutoff score for the PostConcussion Scale was > 15 points, the cognitive symptom total score was > 3 points, and the Memory Composite was < 76.9% correct. These three cutoff scores were then examined, in combination, to determine i f they could reasonably separate the two groups. These results are presented in Table 7. Notice that 82% o f the control subjects did not have a single unusual score, compared to 56% o f the A D H D sample. A p p l y i n g a decision rule o f one or more unusual scores would result i n a correct classification rate o f 44.1% o f the A D H D subjects and 82.4% of the controls. A p p l y i n g a decision rule o f two or more unusual scores would result in a correct classification rate o f 23.5% for the A D H D group and 92.6% for the controls. Table 7 Percent of subjects with unusual scores  Number o f Unusual Scores 0 1  A D H D Group Cumulative Percent Percent 55.9 55.9 20.6 76.5  ,  Control Group Cumulative Percent Percent 82.4 82.4 10.3 92.6  2 16.2 92.6 5.9 98.5 3 7/4 100.0 , 1.5 100.0 Note: "Unusual" scores occur in less than 10% of the control group for each of the three variables.  57  Discussion Increasingly there is recognition that many symptoms o f A D H D persist into adulthood (Epstein et al., 2001; Murphy, 2002a). However, because it is a diagnosis made based on childhood history, retrospective diagnosis in adulthood has proven challenging. N o "goldstandard" test exists that has been shown to reliably differentiate adults with A D H D from those without A D H D . Recently, research has examined the utility o f neuropsychological tests for identifying differences between persons with and without A D H D (Johnson et al., 2001; Murphy, 2002b; N i g g et al., 2002). The findings have tended to be mixed: The most consistent results have emerged from the childhood literature (e.g., Barkley et al., 1992; Snow, 1998); somewhat more variable results with adolescents (e.g., Schmitz et al., 2002; Seidman et al., 1997); and highly variable results with the adult A D H D population (e.g., Murphy et al., 2001; Seidman et al., 1998). Further complicating this literature is the fact that the construct "executive functioning" remains poorly operationalized in most o f the neuropsychological literature, and executive functions such as planning, organizational skills, judgment, and inhibitory control are difficult to separate from other cognitive functions that underpin them. There is little consistency in the neuropsychological tests used, although most fall under the general category o f tests o f executive functioning. Use o f a battery o f neuropsychological tests rather than individual measures increases the ability o f neuropsychological tests to discriminate persons with A D H D from those without A D H D (e.g., Woods, Lovejoy, Stutts et al., 2002). However, administration o f a test battery is both time consuming and expensive, and as a result generally not a viable or cost effective way of screening large numbers o f individuals. Research continues to investigate  58  neuropsychological measures with a continued focus on ways to, rapidly differentiate persons with ADHD from those without it. ImPACT version 1.0 is a brief, computer administered and scored, neuropsychological battery initially constructed for rapid evaluation of post-concussive cognitive problems and symptoms in athletes. Recently, ImPACT Version 2.0 demonstrated some promise in a preliminary study examining its utility in differentiating adolescents with ADHD from nonADHD controls (Iverson & Strangway, 2004). ImPACT is brief and easily administered. As a result, it represents a cost-effective solution for screening large numbers of adults for ADHD. The present study examined the utility of ImPACT Version 1.0 for differentiating young adults with ADHD from matched non-ADHD controls on four composite scores and the Post-Concussion Scale. There were significant differences between adults with ADHD and non-ADHD controls on two of the five variables considered, the Post-Concussion Scale and the Memory Composite, with a nonsignificant trend toward slower reaction times in the ADHD group. No significant differences were found on the Impulse Control Composite, or the Processing Speed Composite. Each of these is discussed below in light of relevant research. As predicted, young adults with ADHD were found to perform significantly more poorly on the ImPACT Memory Composite score than matched non-ADHD controls. The Memory Composite produced by ImPACT version 1.0 is composed of five subtest scores measuring different aspects of memory (e.g., verbal learning, visual learning, incidental learning, and working memory). Tasks of verbal learning and memory have been investigated in the adult ADHD literature, and have yielded the most consistent results in differentiating adults with ADHD from non-ADHD controls (e.g., Seidman et al., 1998; Woods, Lovejoy, Stutts et al., 2002). Adults with ADHD appear to have deficits in the encoding and retrieval of  59  verbal information, primarily related to executive aspects o f efficient memory strategy and verbal organization skills (e.g., semantic versus phonemic chunking o f information) (Woods, Lovejoy, & B a l l , 2002). Research on differentiating adults with A D H D has not demonstrated consistent results using visual memory tasks (e.g., Murphy, 2002a). Because individual memory subtests that comprise the Memory Composite, were not readily available, it was not possible to determine which aspects o f memory function contributed to the ability o f the Memory Composite to reliably distinguish participants with A D H D from the matched controls. A s predicted, the reaction time score for the young adults with A D H D was not significantly different than the normative comparison group. This prediction was based on previous findings that tests o f simple reaction time and incidental reaction time (e.g., extracted from the C P T ) have not proven useful in differentiating adults with A D H D from controls (Murphy, 2002a). Despite the fact that the literature does not appear to support reaction time differences between n o n - A D H D controls and individuals with A D H D , a trend toward a significant effect was observed i n the present study, with young adults with A D H D tending to show slower reaction times than their matched controls. Moreover, when the A D H D group was divided into those with versus without self-reported academic problems, those with academic problems had significantly slower reaction times. Similarily, Johnson et al. (2001) found that adults with A D H D performed more slowly than n o n - A D H D controls on a reaction time task (3RT), as the task became more complex. Results from Iverson and Strangway (2004) using I m P A C T version 2.0 revealed differences on the I m P A C T Processing Speed composite score between adolescents with A D H D and n o n - A D H D controls. Accordingly, it was expected that, i n the present study o f young adults, the I m P A C T processing speed composite might also discriminate between young  60  adults with A D H D and n o n - A D H D controls. However, the results did not reveal slower processing speed in the A D H D group. One possibility for the failure o f this study to discriminate adults with A D H D from controls on the basis o f processing speed is that, similar to many o f the investigations o f processing speed in the literature, only the child and adolescent groups differed significantly from n o n - A D H D controls, while young and middle aged adults with A D H D did not (Seidman et al., 1998; Walker et al., 2000). Adults with A D H D may have found ways to compensate or adapt to their cognitive deficits with age. This does not  •  necessarily mean that there are "real" cognitive improvements, but rather that the neuropsychological tests are unable to capture these subtle deficits in adults. Unexpectedly, the I m P A C T Impulse Control composite did not differentiate the adults with A D H D from the matched controls. However, Iverson and Strangway (2004) using I m P A C T version 2.0 reported significant differences between adolescents with A D H D and controls. T w o traditional neuropsychological tests, the C P T and Stroop test, have typically been used to measure impulse/inhibitory control i n the A D H D literature. I m P A C T contains tests almost identical to the Stroop and C P T (Color Word Match & Color Click, respectively). Both of these.tests have a large inhibitory control component, and have been frequently and successfully used to differentiate between children with A D H D and n o n - A D H D controls. Within the adult population, the C P T has also been generally successfully at distinguishing adults with A D H D from controls on the basis o f number o f commission errors (i.e., responding to a target stimuli when withholding o f a response is required) - an index o f inhibitory control (Epstein et al., 1998; Murphy et al., 2001). In comparison, the Stroop task has primarily been successful only with the adolescent population (Schmitz et al., 2002; Seidman et al., 1997). It is possible that a similar pattern o f results was found on the I m P A C T Impulse Control composite,  61  which is composed o f an average o f the two scores (i.e., commission errors on Color Word Match & total incorrect/interference on Color Click). It is possible that good differentiation between groups on one o f the scores was diluted to the point o f non-significance by a nondiscriminating result on the other score. A s mentioned i n the context o f the Memory Composite, the extraction and examination o f the individual test scores was not readily available for this study. More importantly, the test instructions and practice items for one or more o f the tasks that comprise the Impulse Control Composite were revised and clarified for Version 2.0 o f I m P A C T . This might have increased the usefulness o f this composite in the previous study. Finally, as predicted, young adults with A D H D in the present sample reported significantly more symptoms on the Post-Concussion Scale than matched controls. They also reported greater difficulty with the cognitive symptoms on that scale. This finding is consistent with the literature that adults with A D H D report more psychiatric symptoms than healthy controls (e.g., feeling down, feeling irritable, feeling depressed) (Woods, Lovejoy, & B a l l , 2002). Moreover, the scale includes items that specifically relate to A D H D symptomatology (e.g., trouble concentrating). Throughout this thesis, I have discussed the "differentiation" o f people with A D H D from n o n - A D H D control subjects. It is important to emphasize that this means statistical differentiation, not practical differentiation. Indeed, as emphasized throughout this thesis, the practical differentiation o f people with A D H D based on neuropsychological tests has been difficult and elusive. Finding a statistically significant difference between two groups on a test does not, o f course, mean that the test can differentiate individuals on a case-by-case basis. This is illustrated i n Figure 1.  62  Using IQ scores as the metric o f interest, average scores are 100 with a standard deviation o f 15. Therefore, the vast majority o f subjects would score within two SDs from the mean (30 points). Differences between a clinical group and a "normal" group are illustrated using effect sizes ranging from .2 (small) to 1.5 (large). A s seen i n this figure, even a "large" effect size o f .8 results in tremendous overlap between a clinical group and a "normal" distribution. This, o f course, makes it very difficult to accurately differentiate individuals within groups based on a test score. Figure 1. Overlapping distributions based on effect sizes (using the IQ metric). 140 130 120 110 100 90 80 70 60 50 40 Average  0.2  0.5  0.8  1  1.5  Note: This figure illustrates the theoretical overlap between clinical groups that differ from "normal" by certain magnitudes o f effect sizes.  Conclusions The pattern o f results produced by this investigation o f I m P A C T is consistent with the adult A D H D literature in that the I m P A C T test battery did not consistently demonstrate differences across all neuropsychological tests between individuals with A D H D compared to controls (e.g., Corbett & Stanczak, 1999; Kovner et al., 1998; Walker et al., 2000). Adults with A D H D performed significantly more poorly than controls on the M e m o r y Composite, and  63  showed a nonsignificant trend towards slower reaction times on the Reaction Time Composite, but did not differ on the Processing Speed or Impulse Control Composites. The nature o f these results is similar to the reviewed literature that has found the most promising results on memory tasks (e.g., Seidman et al., 1998; Woods, Lovejoy, Stutts et al., 2002). The lack o f , consistent results across the I m P A C T composites likely results from a number o f factors. The biggest factor appears to be problems with the test itself. Iverson and Strangway (2004) reported much stronger findings using version 2.0 o f the test, especially for the Impulse Control Composite (the effect size was large, d = .93). Improvements to the administration instructions and practice items from version 1.0 to version 2.0 might account for the different results. Another major factor relating to the lesser differences between groups i n this study was the nature o f the sample. Most o f the subjects were in university, whereas i n Iverson and Strangway (2004) all were i n high school. It stands to reason that those people with A D H D who go to university have less pronounced cognitive difficulty, as a group, than those who do not. Another factor is that as adults with A D H D age, they find strategies to compensate for potential attentional deficits, and therefore some tests become less able to discriminatetheir performance as they get older and adapt better. This does not suggest that attention deficits necessarily disappear with age, but rather that they become more difficult to identify with cognitive measures. Further, the disorder is variable by nature, and adults with A D H D do not manifest cognitive deficits equally under all conditions. One o f the noted hallmarks o f A D H D is poorer performance as extraneous distractions increase (Woods, Lovejoy, & B a l l , 2002). Completing a test battery under quiet and controlled conditions is likely not a good algorithm for functional  64  performance under "real world" conditions. Thus, it is not reasonable to assume that these deficits can always be reliably identified in the testing environment. Further, ADHD is associated with day-to-day variability in performance so one testing session during one period of time may also not capture the full nature of their deficits. Limitations  There were a number of limitations to the current study. First, the self-report method of identifying the ADHD group introduces retrospective bias and although the literature appears to support self-report by individuals with ADHD, the bias associated with self-report could not be determined. Using a single diagnostic indicator such as a self-report with no cross-validation of history or symptoms from multiple settings or informants is not ideal. However, given the lack of a gold standard method for diagnosing ADHD, this study, like many others (Epstein et al., 1998; Epstein et al., 2001; Murphy, 2002a, 2002b; Nigg et al., 2002) relied by necessity on self-reported ADHD symptoms for group classification. In the present study, this problem was slightly mitigated because of the young age of the sample. It is reasonable to suppose that young adults aged 15-22 would have been diagnosed more recently than those in other studies where participants were up to 89 years of age. Further, some of the older participants might not have been diagnosed at all in childhood, because the diagnosis might not have been identified or have become well-known to clinicians, given its recent inclusion in the DSM. In contrast, there is a strong likelihood that the present sample of young adults would have received a diagnosis of ADHD within the past 10 years (i.e., in the 1990's). Further, this sample received no obvious gain from participating in this study, and they had no reason to mislead the researcher.  65  Because this was a sample o f convenience, derived from a normative database, the individuals with A D H D were not classified or separated according to D S M - I V - T R subtypes. The majority o f previous studies have not differentiated their samples on this basis, and research to date has not consistently identified different cognitive profiles among the A D H D subtypes (e.g., Epstein et al., 2001; Kovner et al., 1998; N i g g et al., 2002; Walker et al., 2000). However, further investigation o f the subtypes in terms o f identifying whether their I m P A C T performance profiles differed might be interesting. A contentious issue is whether or not to control for intelligence. In the present study, this variable could not be analyzed because it was not collected in the normative database. Further, many researchers have suggested that controlling for intelligence might remove meaningful variance associated with A D H D (Seidman et al., 1997). Seidman et al. (1997) contend that using intelligence as a covariate constitutes "overcontrol," thereby limiting the possibility o f finding significant differences between adults with A D H D and controls. In the studies reviewed, the majority that controlled for intelligence found no differences on neuropsychological tests between adults with A D H D and controls (Kovner et al., 1998; Walker et al., 2000). A final limitation o f the present study relates to the participants' use o f medication. In most o f the reviewed studies, adults with A D H D were either not taking medication, were taken off stimulant medications prior to testing, or the studies implemented statistical procedures to control for the possible cognitive effects o f medication (e.g., Corbett & Stanczak, 1999; Epstein et al., 2001; Seidman et al., 1998). In the present study, the effects o f medication (stimulant or other) could not be examined because specific medication information was not collected i n the normative database. However, researchers exploring the use o f stimulant medications on  66  cognitive performance have found conflicting results. Schmitz et al. (2002) found that unmedicated participants with A D H D performed more poorly than those on stimulant medications. In contrast, Seidman et al. (1997) found no performance differences on cognitive measures between unmedicated and medicated participants with A D H D . Future research investigating whether the profiles o f individuals with A D H D differ according to whether they are using stimulant medications would be valuable. Future Directions  I m P A C T is a new test. Developing a new test takes time, money, and most importantly feedback from both clinicians and researchers. V i a such feedback the test has undergone revisions resulting in I m P A C T version 2.0. Future researchers using this test should examine the individual subtests, not just the composite scores. Moreover, the ease o f administration including time, cost-efficiency, and limited examiner training requirements, suggests that a large number o f individuals with A D H D or other disorders could be tested rapidly. W i t h larger samples some o f the current methodological limitations o f the reviewed literature could be addressed with ease. Future research could examine the differential neuropsychological performance o f individuals within constrained age ranges in order to identify i f there are primary cognitive differences between the age groups. Longitudinal studies are needed with repeated evaluation over time to improve on the cross-sectional literature that currently dominates the research i n this area. One o f the advantages o f I m P A C T is its automatic randomization o f stimuli to allow for repeated testing with minimal practice effects. 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