Olaf Lund

Objective: The Conners Continuous Performance Test-3 (CCPT-3) is a computerized test of attention frequently used in clinical neuropsychology. In the present factor analysis, we seek to assess the factor structure of the CCPT-3 and evaluate the suggested dimensions in the CCPT-3 Manual. Method: Data from a mixed clinical sample of 931 adults referred for neuropsychological assessment across four centers were analyzed. Nine standard and eight experimental measures were subjected to an exploratory factor analysis to evaluate factor models ranging from one to six factors. Results: The analysis supported a four-factor model with one overall attention factor and three factors of distinct mechanisms underlying inattention: impulsivity, vigilance, and sustained attention. This closely aligns with the four dimensions outlined in the CCPT-3 Technical Manual and the factor analyses from the CCPT-II. There were some differences between the four-factor model and the interpretations recommended in the Technical Manual. Perseverations were associated with the inattention factor rather than the impulsivity factor, and reaction time was exclusively linked to impulsivity. Incorporating error measures into the vigilance factor suggests that decreases in responsivity, rather than decreases in correct responses, underpin vigilance decrements. Including response bias by inter-stimulus interval (ISI) and by blocks in the analysis indicates that a decrease in arousal may also explain impairments in sustained attention. Conclusion: This study supports the notion in the Technical Manual that CCPT-3 measures both overall attention and three different mechanisms that mediate inattention: impulsivity, vigilance and sustained attention.

The Digit Span test has been part of the Wechsler tests from the first version. In the WAIS-IV the Digit Span Sequencing subtest (DSS) was introduced and in the forthcoming WAIS-5 working memory span will also be measured in the visual modality. The present study analyzes WAIS-IV Digit Span, Letter- Number Span (LNS) and WMS-III Spatial Span (SS) performance in a mixed clinical sample, expecting to find that Digit Span Forwards (DSF) lacks sensitivity to the Working Memory impairment evident in D-KEFS Trail Making Test-4 (TMT-4) scores ≤1 SD below normative means in the sample. The results showed DSF score above normative means, Digit Span Backwards (DSB) around mean, while SS and LNS was slightly impaired and DSS impaired at the same level as TMT- 4. A double dissociation was observed in DSF and SS performance between subjects with Language- and Non-verbal learning disorders. Most subjects scored in the average range on the LNS-span and high kurtosis reduced sensitivity. Taking LNS and TMT-4 as criterion measures of WM, regression analyses showed no unique contribution of DSF to the variance in these tests. The study supports prior critiques regarding the composite Digit Span measure and demonstrates that the DSS are more effective than the current version of LNS in identifying reduced Working Memory capacity.

The fifth version of Wechsler Intelligence Scale for Children is designed to measure five distinct aspects of intelligence, incorporating a new fluid reasoning index to the four indexes of the previous fourth version. Several factor analyses, however, have failed to support the fifth factor. The Scandinavian version is the only national version not showing clear superiority for the five‐factor solution in the Manual. In the present study, we analyze WISC‐V protocols from a clinical sample of 237 children tested with the new Scandinavian version. We perform six confirmatory factor analyses (CFA) testing three hierarchical‐, two bifactor‐, and one correlated candidate factor models. The study shows that the three‐factor model does not fit the data, and that all four‐ and five‐factor models showed good fit. The four‐factor bifactor model was somewhat better than the five‐bifactor and hierarchical models, but the correlated five‐factor model was the superior model. Finding support for five‐factors in a clinical sample representative of those most probable to be tested with the test, strengthen the claim that also the Scandinavian version measure a distinct fluid factor as intended by the test owners, and thus that clinicians may use the index scores as their main level of analysis. Review of previous CFAs show that the choice of statistical methods for CFA, bifactor or hierarchical/correlated, influence whether second order factor models are better than g‐factor models.