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Published online by Cambridge University Press: 21 December 2023
As neuropsychologists aim to collect valid data, maximize the utility of assessments, make effective use of time, and best serve patient populations, measurement of performance validity is considered a critical issue for the field. As effort may vary across an evaluation, including performance validity tests (PVTs) throughout the assessment is important. Incorporating embedded PVTs in addition to free standing PVTs can be particularly useful in this regard. COWAT and animal naming are commonly administered verbal fluency measures. While there have been past investigations into their potential for detecting invalid performance, they are limited, and more research is needed. Perhaps most promising, Sugarman and Axelrod (2015) described a logistic regression derived formula utilizing the combined raw scores of COWAT and animal naming. The current study aimed to investigate the use of embedded PVTs within COWAT and animal naming to provide further support for the use of embedded PVTs in these measures.
All subjects were from a mixed clinical sample comprising military veterans from two VA Medical Centers in the northeast U.S., who were referred for neuropsychological evaluation. Subjects deemed credible had zero PVT failures. Subjects were considered non-credible performers if they failed at least two out of a possible eight PVTs administered. Subjects who failed one PVT were excluded from the study (n = 53). The final sample consisted of 116 individuals with credible performance (Mean Age = 35.5, SD = 8.8; Mean Edu = 13.6, SD = 2; Mean Est. IQ = 106, SD = 7.9) and 94 individuals with psychometrically determined non-credible performance (Mean Age = 38.5, SD = 9.4; Mean Edu = 113, SD = 2.1; Mean Est. IQ = 101, SD = 8.7). Performance of COWAT and animals in detecting non-credible performances was evaluated through calculation of classification accuracy statistics and use of the logistic regression formulas reported in Sugarman and Axelrod (2015).
For COWAT, the optimal cutoff was a raw score of <27 (specificity = 89%; sensitivity = 31%), and a T-score of <35 (specificity = 92%; sensitivity = 31%). For animal naming, optimal cutoffs were <16 for raw score (specificity = 92%, sensitivity = 38%) and <37 for T-score (specificity = 91%; sensitivity = 33%). The logistic regression formula based on raw scores for both COWAT and animal naming was inadequately sensitive at the recommended cutoff in this sample, but a coefficient of > .28 was revealed to be optimal (91% specificity; 42% sensitivity). When the formula for T-scores was used, a coefficient of > .38 was optimal (91% specificity; 28% sensitivity).
Results of the current research suggest that PVTs embedded within the commonly administered COWAT and animal naming verbal fluency tests can effectively detect low effort, in concordance with generally accepted standards. A logistic regression formula using raw scores in particular appears to be most effective, consistent with findings reported by Sugarman and Axelrod (2015).
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