Validation of alternative dot counting test E-score cutoffs based on degree of cognitive impairment in veteran and civilian clinical samples.

OBJECTIVE: This study examined Dot Counting Test (DCT) performance among patient populations with no/minimal impairment and mild impairment in an attempt to cross-validate a more parsimonious interpretative strategy and to derive optimal E-Score cutoffs. METHOD: Participants included clinically-referred patients from VA (n = 101) and academic medical center (AMC, n = 183) settings. Patients were separated by validity status (valid/invalid), and subsequently two comparison groups were formed from each sample's valid group. Namely, Group 1 included patients with no to minimal cognitive impairment, and Group 2 included those with mild neurocognitive disorder. Analysis of variance tested for differences between rounded and unrounded DCT E-Scores across both comparison groups and the invalid group. Receiver operating characteristic curve analyses identified optimal validity cut-scores for each sample and stratified by comparison groups. RESULTS: In the VA sample, cut scores of ≥13 (rounded) and ≥12.58 (unrounded) differentiated Group 1 from the invalid performers (87% sensitivity/88% specificity), and cut scores of ≥17 (rounded; 58% sensitivity/90% specificity) and ≥16.49 (unrounded; 61% sensitivity/90% specificity) differentiated Group 2 from the invalid group. Similarly, in the AMC group, a cut score of ≥13 (rounded and unrounded; 75% sensitivity/90% specificity) differentiated Group 1 from the invalid group, whereas cut scores of ≥18 (rounded; 43% sensitivity/94% specificity) and ≥16.94 (unrounded; 46% sensitivity/90% specificity) differentiated Group 2 from the invalid performers. CONCLUSIONS: Different cut scores were indicated based on degree of cognitive impairment, and provide proof-of-concept for a more parsimonious interpretative paradigm than using individual cut scores derived for specific diagnostic groups.

Cognitive Performance and Psychiatric Self-Reports Across Adult Cognitive Disengagement Syndrome and ADHD Diagnostic Groups.

OBJECTIVE: Cognitive disengagement syndrome (CDS) is characterized by inattention, under-arousal, and fatigue and frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD). Although CDS is associated with cognitive complaints, its association with objective cognitive performance is less well understood. METHOD: This study investigated neuropsychological correlates of CDS symptoms among 169 adults (Mage = 29.4) referred for outpatient neuropsychological evaluation following inattention complaints. We evaluated cognitive and self-report differences across four high/low CDS and positive/negative ADHD groups, and cognitive and self-report correlates of CDS symptomology. RESULTS: There were no differences in cognitive performance, significant differences in self-reported psychiatric symptoms (greater CDS symptomatology, impulsivity among the high CDS groups; greater inattention among the positive ADHD/high CDS groups; greater hyperactivity among the positive ADHD groups), significant intercorrelations within cognitive and self-report measures, nonsignificant correlations between cognitive measures and self-report measures. CONCLUSION: Findings support prior work demonstrating weak to null associations between ADHD and CDS symptoms and cognitive performance among adults.

Comparing the Independent and Aggregated Accuracy of Trial 1 and the First 10 TOMM Items for Detecting Invalid Neuropsychological Test Performance Across Civilian and Veteran Clinical Samples.

Previous studies support using two abbreviated tests of the Test of Memory Malingering (TOMM), including (a) Trial 1 (T1) and (b) the number of errors on the first 10 items of T1 (T1e10), as performance validity tests (PVTs). In this study, we examined the independent and aggregated predictive utility of TOMM T1 and T1e10 for identifying invalid neuropsychological test performance across two clinical samples. We employed cross-sectional research to examine two independent and demographically diverse mixed samples of military veterans and civilians (VA = 108; academic medical center = 234) of patients who underwent neuropsychological evaluations. We determined validity groups by patient performance on four independent criterion PVTs. We established concordances between passing/failing the TOMM T1e10 and T1, followed by logistic regression to determine individual and aggregated accuracy of T1e10 and T1 for predicting validity group membership. Concordance between passing T1e10 and T1 was high, as was overall validity (87-98%) across samples. By contrast, T1e10 failure was more highly concordant with T1 failure (69-77%) than with overall invalidity status (59-60%) per criterion PVTs, whereas T1 failure was more highly concordant with invalidity status (72-88%) per criterion PVTs. Logistic regression analyses demonstrated similar results, with T1 accounting for more variance than T1e10. However, combining T1e10 and T1 accounted for the most variance of any model, with T1e10 and T1 each emerging as significant predictors. TOMM T1 and, to a lesser extent, T1e10 were significant predictors of independent criterion-derived validity status across two distinct clinical samples, but they did not offer improved classification accuracy when aggregated.