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The relationship between lab measures and rating scales of executive function in a clinical sample

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The relationship between lab measures and rating scales of executive function in a clinical sample
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Hassara, Kathleen Elizabeth ( author )
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The Behavior Rating Inventory of Executive Function (BRIEF) claims to measure executive function (EF); however, there is little research to support this. The present study sought to evaluate the relationship between lab measures of EF, the BRIEF, and the ADHD Rating Scale, Fourth Edition (ARS-IV). It was hypothesized that lab measures of EF would correlate more highly with one another than they would with the BRIEF, and that the BRIEF would correlate more highly with the ARS-IV than with lab measures of EF. It was also hypothesized that performance on lab measures of EF and scores on the ARS-IV would significantly predict variance in BRIEF scores. Results of correlation and regression analyses revealed significant correlations between lab measures of EF and between the BRIEF and ARS-IV, but not between the BRIEF and lab measures of EF. Scores on the WMI, commissions composite, and ADHD composite accounted for 45% of the variance in the BRIEF, although only the commissions and ADHD composites contributed significant unique variance. The same measures accounted for 52% of the variance in BRIEF scores when controlling for FSIQ, age, and grade, with the WMI remaining non-significant. Results of the present study were consistent with those of the existing literature base. It may be that the BRIEF is a better measure of impairment in ADHD, rather than a measure of executive function.
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Thesis (Ph. D.)--University of Colorado Denver ; 2018.
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by Kathleen Elizabeth Hassara.

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THE RELATIONSHIP BETWEEN LAB MEASURES AND RATING SCALES OF EXECUTIVE FUNCTION IN A CLINICAL SAMPLE by KATHLEEN ELIZABETH HASSARA B.A., Ohio University, 2011 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Psychology School Psychology Program 2018

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ii 201 8 KATHLEEN ELIZABETH HASSARA ALL RIGHTS RESERVED

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iii This thesis for the Doctor of Psychology degree by Kathleen Elizabeth Hassara has been approved for the School Psychology P rogram by Bryn Harris, Chair M. Franci Crepeau Hobson Lisa Geissler May 12, 2018

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iv Hassara Kathleen Elizabeth (PsyD, School Psychology Program) The Relationship Between Lab Measures and Rating Scales of Executive Function in a Clinical Sample Thesis directed by Associate Professor Bryn Harris ABSTRACT The Behavior Rating Inventory of Executive Function (BRIEF) claims to measure executive function (EF); however, there is little research t o support this. The present study sought to evaluate the relationship between lab measures of EF, the BRIEF, and the ADHD Rating Scale, Fourth Edition (ARS IV). It was hy pothesized that lab measures of EF would correlate more highly with one another than they would with the BRIEF, and that the BRIEF would correlate more highly with the ARS IV than with lab measures of EF. It was also hypothesized that performance on lab me asures of EF and scores on the ARS IV would significantly predict variance in BRIEF scores. Results of correlation and regression analyses revealed significant correlations between lab measures of EF and between the BRIEF and ARS IV, but not between the BR IEF and lab meas ures of EF. Scores on the WMI, c ommissions composite, and ADHD composite accounted for 45% of the variance i n the BRIEF, although only the c ommissions and ADHD composites contributed significant unique variance. The same measures accounted for 52% of the variance in BRIEF scores when controlling for FSIQ, age, and grade, with the WMI remaining non significant. Results of the present study were consistent with those of the existing literature base. It may be that the BRIEF is a better measure of impairment in ADHD, rather than a measure of executive function. The form and content of this abstract are approved. I recommend its publication. Approved: Bryn Harris

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v This capstone project is dedicated to Bruce F. Pennington, PhD, without whose data and mentorship would not be possible. Thank you for your guidance, your expertise, and for helping me to fall in love with the field of neuropsychology.

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vi TABLE OF CONTENTS CHAPTER I. INTR Review of the Li Purpose and Hy II. METH Partici pa Proced Measur Wechsler Intellige nce Behavior Rating Inventory 6 ADHD Rating Scale Fo Gordon Diagnostic S ystem Model III Statistical An 7 III. RES 8 Preliminary Results 8 Participant Characteristics 8 Correlations 9 Correlation Matrix 9 BRIEF and Lab Measures BRIEF, ARS IV, and Lab Measures 10 Multiple and Hierarchical Regression s... .1 1

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vii IV. DISCUSSION 2 V. 1 5 REFERENCES 7

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viii LIST OF TABLES TABLE 1. Descriptive statistics of assessment m easures 9 2. Correlation matrix 3. Multiple regression predicting s cores on the BRIEF 11

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1 CHAPTER I I NTRODUCTION Rating scales of executive function (EF) such as the Behavior Rating Inventory of Executive Function (BRIEF; Gioia, Isquith, Guy, & Kenworthy, 2000), claim to measure the sa me construct as performance measures of EF yet there is little research to support this notion. A meta analysis of studie s that examined the relationship between neuropsychological measures of EF and EF rating scales indicat ed that a mere 24% of correlations were statistically significant and that the median correlation wa s weak ( r = .19; Toplak, West, & Stanovich, 2013). Th is may be problematic, as rating scales are often used to evaluate executive dysfunction when they may be instead measuring outward behaviors rather than cognitive processes (McAuley, Chen, Goos, Schachar, & Crosbie, 2010). It may be the case that these two types of measures offer more complementary types of data, rather than the same information in different forms (Anderson, 2002; Isquith, Roth, & Gioia, 2013). Review of the Literature Few studies that have examined the re lationship between cognitive measures and behavioral ratings of EF have obtained significant results and most of the significant correlations were weak (see Toplak et al., 2013). In a mixed clinical sample, analyses revealed weak, but significant correla tions between the BRIEF Inhibit scale and the Performance Test II (CPT II), as well as weak but significant correlations between BRIEF scales and the Tests of Variables of Attention Visual (TOVA; Bodnar, Prahme, Cutting, Denckla, & Mahone, 2007). The BRIEF Inhibit scale has also be en correlated with the Stroop interference task ( r = .32) and the amount of money won during a card playing task ( r = .20) P erformances

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2 on these tasks significantly predicted scores on the BRIEF Inhibit scale (Shuster & Toplak, 2009). Toplak, Bucciarel li, Jain, and Tannock (2009) discovered many significant correlations between various lab measures of EF and BRIEF parent and teacher ratings with correlation coefficients ranging from r = .41 to .39 These included s ignificant correlations between i nhibition tasks and teacher reports of Inhibit, Shift, and Working Memory; s et s hifting tasks and parent ratings of Inhibit, Work ing Memory, and Plan/Organize; set s hifting tasks and teac her ratings of Working Memory; w orking m emory tasks and parent rating s of Inhibit, Shift, Working Memory, and Plan/Organize; w orking m emory tasks and teacher ratings of Working Memory; and p lanning tasks and teacher ratings of Inhibit. P erformance on lab measures of EF has significantly predicted variance in the Global Executive Composite (GEC) and Metacognition Index (MI) of the BRIEF (Mangeot, Armstrong, Colvin, Yeates, & Taylor, 2002). Additional studies have found relationships between some performance measures of EF and BRIEF sub scales but no relationship among others In one study, t he MI of the BRIEF was weakly correlated with a working memory task, but no other significant correlations between performance measures of EF and the BRIEF scales emerged (McAuley et al., 2010) In another study, s ome scores on the Contingency Naming Test had moderate correlations with BRIEF subscales, ranging from r = .27 to .48 (Anderson, Anderson, Northam, Jacobs, & Mikiewicz, 2002). T he Controlled Oral Word Association Test was weakly correlated with BRIEF subscales ( r = .24 to .30), while the Rey Complex Figure and the Tower of London were not correlated with any of the BRIEF scales (Anderson et al., 2002). In a sample of children with ADHD and/or Tourette syndrome, t he BRIEF Inhibit scale was again correlated with the TOVA omissions and variability scores; however, all other EF

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3 performance and rating scale correlations were non significant ( Mahone et al., 2002). A 2007 study by Parrish and colleagues revealed signific ant correlations between the BRIEF MI and the Delis Kaplan Executive Function System ( D KEFS ) F r ee Sorting description scores Category Switching accuracy scores and scores on the C olor Word I nhibition tasks but no relationships BRI While some studies have found significant correlations between the BRIEF and performance measure of EF many have reported finding no significant relationships. Two studies examining the relationsh ip between the BRIEF and Digit Span tasks suggest that there is no relatio nship between the two measures (Conklin Solario, & Slomine, 2008; Rosenthal, Riccio, Gsanger, & Pizzitola Jarratt, 2006). In a sample of pediatric epilepsy patients, no significant correlations emerged between any of the BRIEF indices ( MI, BRI, GEC ) and any of the scores on the Tower of London (total moves, total correct, rule viol ations, total time; MacAllister et al., 2012) Finally, t he BRIEF indices, Wechsler Intelligence Scales, Trail Making Part B, and Verbal Fluency tasks were not significantly related (Niendam, Horwitz, Bearden, & Cannon, 2007; Vriezen & Piggot, 2002). Although there is little evidence that supports the idea that the BRIEF and neuropsychological measures of EF measure the same construct, there is evidence that the BRIEF is quite useful for identifying individuals with ADHD. In one study, BRIEF scores appropriately identified individuals both with and without ADHD in 82% of cases (Reddy & Hale, 2011). A nother study determined that the BRIEF is also clinically useful for differentiating All three BRIEF indices, as well as the Inhibit scale, correlate highly with ratings on the ADHD Rating Scale, Fourth Edition (ARS IV; Mahone et al., 2002 ; Zarrabi, Shahrivar, Tehrani

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4 Doost, Khademi, & Nargari Nejad, 2015 ). T he BRI and MI of the BRIEF co rrelate moderately with teacher ratings and strongly with parent ratings of inattention, hyperactivity, and overall impairment (McAuley et al., 2010). Purpose and Hypotheses The current study seeks to add to the literature base by re examining the relationships between lab measures of EF the BRIEF, and the ARS IV using more recent data from a more diverse clinical sample as well as by using multiple and hierarchical regression models for analysis It is expected that lab measures of EF will correl ate more highly with one another than they do with the BRIEF Additionally, it is hypothesized that the BRIEF scales with correlate more highly with the ARS IV than they do with lab measures of EF Finally, it is hypothe sized that scores on the ARS IV, as well as lab measures of executive function, will uniquely predict variance of BRIEF scores.

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5 CHAPTER II M ETHODS Participants Data w ere collected from the files of 102 children and adolescents who received a neuropsychological evaluation at a university clinic and who we re between the ages of 6 and 16 years old at the time of testing The primary referral concerns that led these individuals and their families to seek neuropsychological testing were related to attentional and learning dif ficulties. Procedure All clients participated in a comprehensive neuropsychological evaluation that include d assessment of cognitive, academic phonological, language, EF attentional skills and motor skills as well as social emotional and behavioral functioning. While graduate students administered assessments to the clients, a supervising psychologist conducted a developmental history interview with parents/caregivers of the clients. A brief family history regarding learning, attent ion, and mental health problems was also obtained by the licensed psychologist. Clients who were not a dministered all of the following measures were not included in the study Additional exclusionary criteria include having a ful l s cale intelligence quotient (FSIQ) of 70 or below, and being younger than 6 years old or older than 16 years old at the time of testing. Measures Wechsler In telligence Scale for Children ( WISC; Wechsler, 2003, 2014) The WISC is an individually administered test of cognitive abilities. It is divided into composite indices, each of which taps a different set of abilities and which combine into an overall intel ligence quotient, or FSIQ score For the purposes of this study only the FSIQ and

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6 Working Memory Index (WMI) were used. S cores were obtained from either the fourth or fifth edition of the measure Behavior Rating Inventory of Executive Function (BRIEF; Gioia et al., 2000). The BRIEF is an 86 item questionnaire designed to capture the frequency with which a child displays behaviors that are associated with EF difficulties. The forms can be filled out by parents, teachers, or the individual child him or herself. T he parent and teacher forms each yie ld three global scales, as well as eight clinical subscales and two validity scales. Two of the three global scales, the Metacognition Index (MI) and the Behavior Regulation Index (BRI) were used in this study. Only parent report scores were used, and if an individual had more than one parent score, the average of the scores was used. ADHD Rating Scale Fourth Edition (ARS IV; DuPaul, Power, Anastopoulos, & Reid, 1998). The ARS IV is an 18 item questionnaire that measures the frequency with which children and adolescents exhibit symptoms of ADHD over a 6 mo nth time period. There are parent and teacher versions, each of which yields a score for symptoms of Inattention, Hyperactivity/Impulsivity, and Total ADHD symptoms T he Inattention and Hyperacti vity/Impulsivity scores from the parent report form for each client were used in this study. As with the BRIEF scores, if more than one parent report score was available, the average of the scores was used. Gordon Diagnostic System Model III R (GDS III; Go rdon, McClure, & Aylward, 1996). The GDS III is a n electronic series of continuous performance tasks designed to measure sustained attention, distractibility, and impulse control in order to differentiate individuals with and without ADHD. The two tasks that were used in the current study were the Vigilance and

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7 Distractibility tasks, each of which require an individual to press a button when he or she sees a certain combination of numbers and to not press it when they see others. Each of the se tasks yields a total correct score, as well as omissions and commissions scores. The total correct and commissions scores from the Vigilance and Distractibility tasks were used as cognitive measures of inhibition. Statistical Analyses The data were ana lyzed using bivariate correlations, as well multiple regression and hierarchical regression model s To determine the strength and nature of the relationship between measures, all variables were entered into a correlation matrix. The correlations between si milar measures were averaged to collapse the data as much as possible. The significance of these average correlation coefficients was determined using a table of Exact Test was used to determine whether these coefficients diff ered significantly from one another. Predictive utility of the ARS IV and lab measures of EF on BRIEF scores were analyzed using a s ingle multiple regression model. A hierarchical regression model was used to control for age, grade, and FSIQ when analyzing predictive utility of the ARS IV and lab measures of EF on BRIEF scores. Composite scores were created for the ARS IV and lab measure scores, and a composite BRIEF score served as the dependent variable.

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8 CHAPTER III R ESULTS Preliminary Results Participant Characteristics. Of the 102 files that the data were collected from, 62.7% of clients were male (n = 64), and 34.3% were female (n = 35) with a mean age of 9.88 years old at the time of testing (SD = 2. 82 years). Most clients were in or entering fourth grade at the time of testing (mode = 4. 00, SD = 2.77 ). 60.8% of participants were evaluated using the WISC IV (n = 62), and the remaining 3 8.2% were administered the WISC V (n = 39). 97.1% of clients (n = 99) received at least one diagnosis based on the results of their neuropsychological evaluation. Based on parent report ARS IV scores, 21.6 % of clients (n = 22) were endorsed as having six o r more of the symptoms of ADHD P redominately H yper active/ I mpulsive presentation and 53.9 % (n = 55) were endorsed as having six of more of the symptoms of ADHD P redominately I nattentive presentation It is important to note that these cases were not necessarily mutually exclusive, and that any given individual may have been endorsed as displayi ng six or more symptoms on each ADHD scale. Descriptive Statistics Descriptive statistics for each of the measures included in the study can be seen below in Table 1.

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9 Table 1 Descriptive Statistics of Assessment Measures Measure Mean Standard Deviation BRIEF Behavior Regulation Index (T Score ) Metacognition Index (T Score ) 57.22 65.10 12.71 10.71 ARS IV Hyperactive/Impulsive (Z Score ) Inattentive (Z Score ) 0.83 1.84 1.40 1.30 GDS III Distractibility Commissions (Z Score ) Distractibility Correct (Z Score ) Vigilance Commissions (Z Score ) Vigilance Correct (Z Score ) 1.72 0.52 1.45 0.69 4.89 1.30 3.73 1.85 WISC WMI (Standard Score) 98.35 13.74 FSIQ (Standard Score) 98.67 12.73 Correlation s Correlation Matrix. Results of the bivariate correlation analysis reveal several significant results. These findings include significant relationships between FSIQ and all lab measures of EF ( r = .290 to .736, p < .01). WMI scores were significantly correlated to GDS III scor es ( r = .243 to .323, p < .05). Both the BRI and MI scales of the BRIEF were significantly correlated with both the H yperactive/ I mpulsive and I nattention scales of the ARS IV ( r = .304 to .623, p < .01). Finally, scores on the BRI were significantly correl ated with c ommissions scores on both conditions of the GDS III ( r = .234 to .256, p < .05); however, no significant relationships between the BRI and Correct scores emerged. The only lab measure of EF that correlate d with the MI was the c ommissions score on the Vigilance condition of the GDS III ( r = .27, p < .01). Scores on the ARS IV were not significantly correlated with any lab measures of EF Full results of the correlation matrix can be seen below in Table 2.

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10 Table 2 Correlation Matrix FSIQ BRI MI H/I I/A WMI D.Co D.C. V.Co V.C. FSIQ 1 BRI .169 1 MI .104 .474** 1 H/I .146 .527** .304** 1 I/A .110 .461** .623** .491** 1 WMI .736** .143 .097 .183 .201 1 D.Co .290** .234* .175 .087 .135 .251* 1 D.C. .335** .025 .083 .056 .155 .243* .388** 1 V.Co .340** .256* .271** .152 .189 .323** .834** .377** 1 V.C. .345** .072 .055 .054 .032 .266** .318** .482** .461** 1 Note. = statistically significant at p < .05, ** = statistically significant at p < .01 ; D.Co = Distractibility Commissions, D.C. = Distractibility Correct, V.Co = Vigilance Commissions, V.C. = Vigilance Correct BRIEF and Lab Measures Correlations between lab measures of EF were averaged and a significant mean correlation coefficient of r = .271, p < .05 emerged The correlations between BRIEF scores and lab measures of EF were also averaged, resulting in a mean correlation coefficient of r = .177; however, this correlation did not reach significance ( p > .05). these two correlations were significantly different from one another ( p < .01), indicating that lab measures of EF do correlate more highly with one another than they do with the BRIEF measure of EF BRIEF, ARS IV, and Lab Measures. The average correlation between the BRIEF and lab measures of EF was not significant ( r = .177, p > .05 ); however the average correlation between the BRIEF scales and the scales of the ARS IV was significant ( r = .479, p < .01 indicated that these average correlations were significantly different from one another ( p < .01), revealing that the BRIEF and ARS IV correlate more highly with one another than the BRIEF does with lab measures of EF Interesti ngly, the individual scales of the BRIEF correlate as well with one another ( r = .474, p < .01), as the ARS IV correlates with itself ( r = .491, p < .01) and with the BRIEF ( r = .474, p < .01).

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11 Multiple and Hierarchical Regression s A linear multiple regression predicting BRIEF scores was conducted. This analysis resulted in a significant R 2 of 0.451, F = 25.19, p < .01; however, only the c ommissions composite and ADHD composite accounted for significant unique variance. Regression results a re summarized below in Table 3. A hierarchical regression was conducted to control for factors that may influence BRIEF scores including FSIQ, age at the time of testing, and grade in school. When controlling for these factors, a significant R 2 of .519, F = 15.45, p < .01 emerged. The c ommissions and ADHD composite scores continued to be the only significant unique predictors of variance in BRIEF scores. Results of the hierarchical regression are presented below in Table 4. Table 3 Multiple Regress ion Predicting Scores on the BRIEF Variable R 2 Adjusted R 2 F Beta p value .451 .433 25.19 0.000 ** Commissions Composite .476 0.020 ** ADHD Composite 5.333 0.000 ** WMI .107 .377 Note. ** = statistically significant at p < .01 Table 4 Hierarchical Regression Predicting Scores on the BRIEF Variable R 2 Adjusted R 2 F Beta p value Step 1 .058 .027 1.84 0.146 FSIQ .139 0.183 Grade .437 0.445 Age .596 0.299 Step 2 .519 .485 15.45 0.000** Commissions Composite .206 .012* ADHD Composite .643 0.000** WMI .093 0.422 Note. = statistically significant at p < .05, ** = statistically significant at p < .01

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12 CHAPTER IV D ISCUSSION average correlation between BRIEF scores and those of lab measures of EF was weak and did not reach significance ( r = .177, p meta analysis, which reveale d that approximately three quarters of published correlations between these two types of measures were not significant, and that the median correlation was weak (20 13). Other studies have also found no significant relationship between the BRIEF and various lab measures of EF ( Conklin et al., 2008; MacAllister et al., 2012; Niendam et al., 2007; Rosenthal et al., 2006; Vriezen & Piggot, 2002). L ab measures of EF corre lated weakly, but significantly more highly with one another than they do with BRIEF scores (lab measures r = .271, p < .01; BRIEF and lab measures r = .177, p > .05). This may be because the BRIEF measures behavior, rather than underlying executive dysfunction, thus measuring different constructs than lab measures of EF (McAuley et al., 2010) and offering complementary, rather than consistent, data (Anderson, 2002; Isquith et al., 2013). While the average correlation between the BRIEF an d lab measures was not significant, individual BRIEF scales correlate d with certain lab measures of EF The BRI was weakly, but significantly correlated with c ommissions scores on both conditions of the GDS III ( r = .234 to .256, p < .05), and the MI was weakly correlated with the c ommissions score on the Vigilance condition of the GDS III ( r = .271, p < .01). N either of the BRIEF scales correlate d with WMI scores. These findings replicate those of past studies between the BRIEF and measures of sustained attention ( Bodnar et al., 2007 ; Mahone et al., 2002 ). The results of the current study as well as those of past studies suggest that scores in the individual BRIEF subscales and indices

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13 may be bett er indicators of performance on lab measures of EF than an overall BRIEF score. Additionally, this relationship appears to be limited to measures certain performance measures of EF such as those of sustained attention, rather than to all lab measures including working memory (Anderson et al., 2002; McAuley e t al., 2010). The BRIEF correlate d significantly better with the ARS IV than with lab measures of EF (BRIEF and ARS IV r = .479, p < .01; BRIEF and lab measures r = .177, p > .05). This finding that the BRIEF and ARS IV are significantly correlated also replicates what is known based on existing literature. Multiple studies indicate that all three BRIEF indices correlate with the ARS IV, especially with parent ratings (Mahone, et al., 20 02; McAuley et al ., 2010; Zarrabi et al., 2015). T he BRIEF is able to identify individuals with ADHD (Red dy & Hale, 2011), as well as It may be the case that the BRIEF and the ARS IV correlate more highly with one another than the BRIEF does with lab measures of EF because both the BRIEF and ARS IV are subjective ratings of outward behavior, rather than objective measures of the underlying cognitive processes. An interesting finding of this study is that the BRIEF and ARS IV correlate as well with one another ( r = .479, p < .01) as they do internally (BRIEF MI and BRI r = .474, p < .01; ARS IV Inattention and Hyperactive/I mpulsive r = .491, p < .01). Again, this may be because both measures reflect similar types of observable behaviors. It may also be the case that the BRIEF and the ARS IV are measuring the same construct. This notion brings into question the clinical utility of using both tools as part of an ass essment battery, particularly when parsimony is the goal; however, it could be argued that the ARS IV provides additional valuable information in the form of ADHD symptom coun ts, not just level of executive dysfunction

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14 Results of the multiple regressio n revealed that lab measures of EF and the ARS IV predicted 45% of the variance in BRIEF scores ( R 2 = 0.451, F = 25.19, p < .01). The c ommissions composite score and the ADHD composite score were both unique predictors of BRIEF scores; however, WMI scores were not. When the analyses were re run controlling for FSIQ, grade in school and age at time of testing, t he amount of variance in BR IEF scored predicted by lab measures and the ARS IV increased to 52% ( R 2 = .519, F = 15.445, p < .01), and the ADHD and c ommissions composites continued to be the only significant unique predictors. These results are also consistent with those o f past studies, which have reported that performance on various lab measures of EF to significantly predict scores on the BRIEF Inhibit scale (Shuster & Toplak, 2009), as well as on the GEC AND MI (Mangeot et al., 2002); however, the amount of variance ten ded to be small, as in the current study. The increase in variance when controlling for individual factors suggests that BRIEF scores are also influenced by characteristics such as FSIQ, schooling, and age.

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15 CHAPTER V CONCLUSIONS Results of the present study indicate that lab measures of EF correlate more highly with one another than they do with the BRIEF, which did not correlate with lab measures. Furthermore, the BRIEF correlated significantly with the ARS IV, and in fact, the B RIEF and ARS IV correlate as highly with one another as they do internally. Scores on the ARS IV and the c ommissions composite predicted 45% of the significant unique variance in BRIEF scores. This increased to 52% when controlling for individual traits in cluding FSIQ grade, and age. These results suggest that there is little to no relationship between at least two lab measures of EF (measures of sustained attention and working memory) and the BRIEF. This is problematic, as the BRIEF claims to measure bot h attention and working memory, but as previously discussed, the BRIEF may measure behavior rather than cognition. It is possible that these results would differ if other or more lab measures of EF were used in the analyses, as one limitation of this study is a small assessment battery. The moderate relationship between the BRIEF and ARS IV suggests that the BRIEF may be measuring symptoms and level of impairment in ADHD, rather than truly measurin g EF The correlation that resulted from this study may be due to using the ARS IV z score, as opposed to the ADHD symptom count that the measure also produces. Future research should analyze this relationship using both z scores and symptom counts from th e ARS IV. These measures may also be highly correlated due to the use of a clinical sample which is an additional limitation of the study It is possible that scores on both the ARS IV and the BRIEF are reflecting a level of parental distress, as their ch mpairment to warrant their seeking a neuropsychological evaluation.

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16 Approximately half of the variance in BRIEF scores was attributed to the c ommissions composite score and scores on the ARS IV. It appears that much of th is variance is in the ARS IV scores. A hierarchical regression using more models would confirm this hypothesis. Results of the present study are consistent with the existing literature on the topic. It is unclear, but appears to be unlikely, that the BRIEF is a true measure of EF It is more likely that the BRIEF, like the ARS IV, measures level of impairment associated with executive dysfunction, rather than EF itself. T herefore, it is important to continue to use the BRIEF in conjunction with formal lab measures of EF Although there is considerable overlap between the BRIEF and ARS IV, it may be clinically useful to use both tools when completing an evaluation, as the A RS IV offers additional data regarding ADHD symptoms, rather than pure EF related behaviors, which may be impacted by a multitude of etiologies apart from ADHD Future research on the topic should use both clinical and control participants, a larger assess ment battery, and the most current version of the BRIEF.

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17 REFERENCES Anderson, P. (2002). Assessment and development of executive function (EF) during childhood. Child Neuropsychology, 8 (2), 71 82. Anderson, V. A., Anderson, P., Northam, E., Jacobs, R., & Mikiewicz, O. (2002). Relationships between cognitive and behavioral measures of executive function in children with brain disease. Child Neuropsychology, 8 (4), 231 240. Bodnar, L. E., Prahme, M. C., Cuttin g, L. E., Denckla, M. B., & Mahone, E. M. (2007). Construct validity of parent ratings of inhibitory control. Child Neuropsychology, 13 345 362. doi: 10.1080/09297040600899867 Conklin, H. M., Salorio, C. F., & Slomine, B. S. (2008). Working memory perfor mance following paediatric traumatic brain injury. Brain Injury, 22 (11), 847 857. doi: 10.1080/02699050802403565 DuPaul, G. J., Power, T. J., Anastopoulos, A. D., & Reid, R. (1998). ADHD rating scale IV: Checklists, norms, and clinical interpretation. New York NY : Guilford. Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Behavior rating inventory of executive function: Professional manual. Lutz, FL: Psychological Assessment Resources, Inc. Gordon, M., McClure, F. D., & Aylward, G. P. (1996). The Gordon diagnostic system interpretive guide, third edition. DeWitt, NY: GSI Publications. Isquith, P. K., Roth, R. M., & Gioia, G. (2013). Contribution of rating scales to the assessment of executi ve functions. Applied Neuropsychology: Child, 2 125 132. doi: 10.1080/21622965.2013.748389 MacAllister, W. S., Bender, H. A., Whitman, L., Welsh, A., Keller, S., Granader, Y., & Sherman, E. M. S. (2012). Assessment of executive functioning in childhood e pilepsy: The tower of London and BRIEF. Child Neuropsychology, 18 (4), 404 415. doi: 10.1080/09297049.2011.613812 Mahone, E. M., Cirino, P. T., Cutting, L. E., Cerrone, P. M., Hagelthorn, K. M., Hiemenz, J. R., vior rating inventory of executive function in children with ADHD and/or Tourette syndrome. Archives of Clinical Neuropsychology, 17, 643 662. Mangeot, S., Armstrong, K., Colvin, A. N., Yeates, K. O., & Taylor, H. G. (2002). Long term executive function deficits in children with traumatic brain injuries: Assessment using the behavior rating inventory of executive function (BRIEF). Child Neuropsychology, 8 (4), 271 284.

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