David W. Lovejoy

Neuropsychological Characteristics of Adults with ADHD: A Comprehensive Review of Initial Studies

The role of neuropsychological evaluation in the diagnosis of adults with Attention-Deficit/Hyperactivity Disorder (ADHD) is a growing area of research and clinical interest. Our review of the literature indicates that adults with ADHD demonstrate subtle impairments on select measures of attention and executive functions, auditory-verbal list learning, and complex information processing speed relative to normal controls. The validity of these findings is nonetheless hampered by several limitations, including methodological and sample variability, a restricted range of interpretive techniques, and uncertain discriminant validity. Recommendations are offered to advance the cognitive and neurobehavioral understanding of this disorder and to enhance the utility of neuropsychological methods for diagnosis and management of adults with ADHD.

Neuropsychological performance of adults with attention deficit hyperactivity disorder (ADHD): Diagnostic classification estimates for measures of frontal lobe/executive functioning

ADHD adults (N = 26) were compared to normal controls (N = 26) on 6 neuropsychological measures believed sensitive to frontal lobe-executive functioning. MANOVA analyses and subsequent univariate tests indicated that most of the neuropsychological measures discriminated between the two groups. To address clinical significance diagnostic classification rates were also generated for each measure individually, and for the battery as a whole. Levels of positive predictive power (PPP) for each of the 6 measures (83-100%) indicated that abnormal scores on these tests were good predictors of ADHD. However, estimates of negative predictive power (NPP) suggested that normal scores poorly predicted the absence of ADHD. When classification rates were calculated for the overall battery classification accuracy improved substantially. Thus, neuropsychological tests can differentiate adults suffering from ADHD from adults without ADHD, while also providing good classification accuracy. Finally, the pattern of neurobehavioral impairments exemplified through the Summary Index scores was interpreted as consistent with conceptualizations of ADHD depicting mild neurologic dysfunction in networks associated with the frontal lobes.

Are Classification Accuracy Statistics Underused in Neuropsychological Research

The prevalence of classification accuracy statistics was calculated in five prominent neuropsychology journals and five leading neurology journals for the years 2000 and 2001. Only 29% of neuropsychological articles judged to be appropriate for classification accuracy statistics presented sufficient data to calculate a full range of such analyses. Moreover, classification accuracy statistics were significantly less prevalent in neuropsychology journal articles than in studies published in neurology journals during the same time period. Various indices of sensitivity and/or specificity were present in 31% of neuropsychology articles, whereas fewer than 3% reported predictive values or risk ratios. These findings indicate that classification accuracy statistics, most notably predictive values and risk ratios, are potentially underused in neuropsychology. Investigators and research consumers are encouraged to consider the applicability of classification accuracy statistics as a means of evaluating the clinical relevance of neuropsychological research findings.

Understanding Index and Subtest Scatter in Healthy Adults

Clinicians use statistical data to identify patterns of cognitive strengths and weaknesses (e.g., statistical significance and base rates). The statistical data typically represent pairwise comparisons between specific cognitive abilities (e.g., intelligence versus memory). Therefore, the statistical data reflect a specific cognitive strength or weakness but not variability in cognitive functioning more generally. Most healthy individuals have cognitive strengths and weaknesses and variability is greater in individuals with above-average intelligence. Statistical and base rate criteria do not account for the large number of potential pairwise comparisons that can be evaluated. Therefore, healthy individuals may have some statistically significant pairwise comparisons but do not show a greater than expected level of cognitive variability. Normative and clinical data are presented to help the clinician identify normal and atypical variability. This represents a new approach to the interpretation of variability on the WAIS–IV and WMS–IV.