Behavioral Sciences and Education Assessing ADHD Diagnosis through Measures of Executive Function: A Clinical Control Comparison Ashley Gillmor, Thomas G. Bowers School of Behavioral Sciences and Education, The Pennsylvania State Harrisburg, Middletown, PA, United States School of Behavioral Sciences and Education Table 1 Digit Span, WCS, and Matrix Reasoning Scores of ADHD and Clinical Groups Variable   Group M SD WISC-IV Digit Span* ADHD 6.33 2.723 Clinical 7.46 3.144 WISC-IV Matrix Reasoning 8.00 3.388 8.46 3.155 WCS Categories Completed 4.49 1.631 4.59 1.774 WCS Perseverative Errors 21.20 19.085 18.28 16.27 *p < .05 Table 2 Demographics *(N = 131) Male 82 Female 40 ADHD 70 Fetal Alcohol Syndrome (FAS) 13 Pervasive Development Disorder (PDD) 8 Traumatic Brain Injury (TBI) 12 Learning Disorder (LD) 19 *Total does not match due to missing information Introduction The results showed that children presenting only with ADHD scored significantly lower than clinical control groups on a measure of executive functions that require attention and concentration, but not on higher level measures of executive function. Individuals presenting with ADHD have continually presented with prominent deficits in attention and concentration. Measures of executive function (EF) have been proposed to be the most useful in detecting ADHD(1, 3, 5). Previous research has focused on comparing children with ADHD to normal controls or children with learning disorders. The current study attempts to compare children with ADHD to children with specific cognitive and neurological deficits. Discussion Significant differences were found on measures of alertness and concentration between ADHD children and clinical control children, but not on other measures of EF. Despite the limited findings on EF measures, the data suggested that ADHD children demonstrate relatively weak scores on EF measures when compared to a normal control sample, rather than a clinical sample. However, the problem of differentiating ADHD groups from other cognitive disorders persists. Emch (2014) has pointed out that on subjective appraisals by professionals, teachers have shown to be more accurate than objective tests in identifying ADHD in individuals. However, objective measures are still desirable for the diagnosis of clinical disorders. Attentional control processes are still developing in children, often making a diagnosis of ADHD through clinical testing difficult at an early age(2). As research continues to develop in this direction, it may be useful to more fully and specifically sample executive processing to be able to better understand ADHD. Objectives To accurately classify and diagnose ADHD, through measures of executive functioning. To distinguish classifications of ADHD from other neurological disorders hbg.psu.edu Method Existing WISC-IV data from over a span of 10 years was utilized. WISC-IV scores from children, aged 6—16 years, presenting with ADHD were compared to scores from children presenting with other neurological disorders, but not ADHD. Executive functioning scores from the WISC-IV subtests (Digit Span, and Matrix Reasoning), as well as The Wisconsin Card Sorting task (Categories Completed and Perseverative Errors) were used in the analysis. Results Children in the ADHD group scored more poorly than clinical controls in all of the subtests measuring EF. However, only the results on the Digit Span subtest differed significantly between the comparison conditions. All of the other differences were not significant. The results indicated that Digit Span scores for children presenting with ADHD (M = 6.33, SD = 2.72) and those not presenting with ADHD (M = 7.46, SD =3.144) were significantly different F (1, 129) = 4.87, p = .029. No other measures were found to be significantly different. Scores from categories completed on the WCS subtest between the ADHD group (M = 4.49, SD = 1.631) and the clinical group (M = 4.59, SD = 1.774) was not significant at F (1, 129) = .12, p = .73. These scores, as well as perseverative error scores, and Matrix Reasoning scores were not significantly different at F (1, 129) = .875, p = .351 and F (1, 129) = .64, p = .43, respectively. References 1. Barkley, R. A. (2003). Issues in the diagnosis of attention-deficit/hyperactivity disorder in children. Brain and Development, 25(2), p. 77-83. 2. Bowers, T. G., Risser, M. G., Suchanec, J. F., Tinker, D. E., Ramer, J. C., & Domoto, M. (1992). A developmental index using the Wechsler Intelligence Scale for Children: Implications for the diagnosis and nature of ADHD. Journal of Learning Disabilities, 25(3), p. 179-185, 195. 3. Bryce, D., Whitebread, D., Szucs, D. (2014). The relationships among executive functions, metacognitive skills, and educational achievement in 5 and 7 year-old children. Metacognition and Learning. doi: 10.1007/s11409-014-9120-4 3. Emch, M. L. (2014). Assessing executive functioning in schools: The utility of the BRIEF and D-KEFS in identifying ADHD. (Doctoral dissertation). Retrieved from Proquest Information and Learning. (AAI 3603284) 4. Rabinovitz, B. B. (2013). Temperament, executive control, and ADHD across development. (Doctoral dissertation). Retrieved from Proquest Information and Learning. (3541730) Requests for additional information can be send to: Thomas G. Bowers, Ph.D., Penn State Harrisburg, 777 W. Harrisburg Pike, Olmsted W311, Middletown, PA 17057. Email: dvo@psu.edu, 7171-948-6063  To cite: Gillmor, Ashley and Bowers, Thomas G. (2015, May). Assessing ADHD Diagnosis through Measures of Executive Function: A Clinical Control Comparison. Poster presented at the Association for Psychological Science (APS) Conference, New York, NY.