Objective The current study compares performance on measures of executive functioning in individuals with a history of 2 or more mTBI versus those with a single documented mTBI. Specific interaction with emotional distress was explored. Method A database from neuropsychological assessment of individuals noting deficits following head injury including 273 individuals provided a sample of 174 males, 98 females (one case missing data); mean age = 21.82 years; mean education = 10.16 years. Executive functioning was measured using the Trails Making Test Form B (TMT-B), Delis-Kaplan Executive Function System (DKEFS) Design Fluency, and Semantic Fluency instruments. Emotional distress was assessed using the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). Results MANCOVA was employed to determine the effect of multiple head injuries versus one upon cognitive performance after controlling for depression and anxiety. Group differences between those with one versus 2 or more mTBI were present (Wilk’s η = 0.907, F (3, 125) = 4.256, p = 007, Partial η2 = 0.093). Significant differences were not noted with regard to emotional distress (BAI, p = 0.97 l BDI, p = 0.87). Between subject effects identified significant differences between groups in performance on DKEFS Design Fluency (p = 0.05) and Semantic Fluency (P = 0.04), while significant groups differences were not evident Trailmaking Test B performance (P = 0.20). Conclusion Overall, those who had previous concussions performed better on measures of executive functioning. Measures of emotional functioning were not a significant covariate of cognitive performance. Implications and limitations of the current study will be discussed.

Objective: The neurocognitive profile for individuals with ADHD reveals impaired processing speed scores (Kramer et al., 2020; Onandia-Hinchado, et al., 2021). Depression has been associated with impairment across cognitive domains, including processing speed, even after remission of depressive episodes (Ahern & Semkovska, 2017; Semkovska, et al., 2019). In addition, the co-occurrence of ADHD and Depression may result in impaired processing speed beyond the deficits typical for those with only one of these disorders (Larochette, et al., 2011). This study will further investigate the cumulative effects of comorbid ADHD and Depression by exploring if those with comorbid depression perform more poorly on processing speed measures than individuals with ADHD and no comorbid depression when controlling for intellectual ability. Method: This study used archival data from a private practice neuropsychology clinic in the Midwest. This study included 233 adult participants diagnosed with ADHD, including 92 with a diagnosed comorbid depressive disorder. Processing Speed was examined using the Processing Speed Index (PSI) from the Wechsler Adult Intelligence Scale- Fourth Edition (WAIS-IV). Participant intellectual functioning was controlled for using the VCI of the WAIS-IV. Results: An ANCOVA was used to examine the differences in PSI. The covariate VCI accounted for 19.9% of the variability in processing speed (ηp2 = .199; p = .000). Comorbid depression was non-significant and accounted for 0.1% of variability after controlling for VCI (ηp2 = 0.001; p = .640). Conclusion: There is a minimal relationship between co-morbid ADHD and depression and processing speed. Impaired processing speed in clients is likely attributable to effects of ADHD.

Objective: This study aims to clarify the relationship between self-report and performance-based measures of cognitive, behavioral, and emotional inhibition in diagnosing attention-deficit/hyperactivity disorder (ADHD) in adults. Current research states performance-based measures account for little unique variance in determining ADHD diagnoses; however, research is based mostly in pediatric populations. Method: 78 participants referred for outpatient neuropsychological evaluation for differential diagnosis of ADHD were used. Binomial logistic regressions were used to explore the predictive relationship of inhibition to ADHD as measured by the Trail Making Test—Part B (TMT-B), discriminability index of the Conners’ Continuous Performance Test—Second Edition (CPT-II), and Behavior Rating Inventory of Executive Function—Adult (BRIEF-A) Inhibition subscale. Pearson correlations were calculated to determine linear relationships between measures. Results: BRIEF-A Inhibition subscale was the sole variable of significance (p = .043) when predicting ADHD without co-morbid diagnoses, with the model accurately classifying 60.3% of standalone ADHD diagnoses. Conversely, TMT-B scores were the sole variable of significance (p = .044) when predicting ADHD with co-morbid depression and anxiety, with the model accurately classifying 68.9% of co-morbid diagnoses. No measures significantly predicted ADHD with co-morbid depression or anxiety. Only the BRIEF-A Inhibition subscale and the CPT-II discriminability index held a significant correlational relationship (r = -.225, p = .026). Conclusions: As is consistent with current literature, performance-based cognitive measures contributed little predictive power in diagnosing standalone ADHD in adults. However, TMT-B demonstrated significant predictive power when patients also demonstrated clinically significant depression and anxiety – perhaps suggesting a compound effect. Self-report and performance-based inhibition measures held minimal correlation.