Abstract

Objective: To compare and update predictive models comprised of embedded measures from the Continuous Visual Memory Test (CVMT) in their ability to predict performance validity in personal injury litigants. Methods: Ninety-two personal injury litigants underwent a comprehensive neuropsychological examination. Criterion groups were formed, i.e. PVT-Pass and PVT-Fail, based upon their performance on stand-alone measures of performance validity (PVT). Independent-samples t-tests investigated group differences on dependent variables of interest while logistic regression analyses, as well as a decision tree classification procedure, were employed to identify the best predictive model. Results: The PVT-Fail group scored significantly lower on the 20-item Larrabee Index (LI), and three CVMT variables comprising the Henry-Enders Index (HEI) including Hits, Total Score, and Delayed Recall, but significantly higher on False Alarm Errors. Although the Total score was the best single predictor of PVT status, the addition of LI improved sensitivity. The best predictive model was derived via a classification and regression tree analysis which selected LI and CVMT-FA resulting in .91 specificity, .60 sensitivity, and ROC = 0.832. Conclusion: In the current study total CVMT scores < 70, and LI scores < 18 were rare for PI litigants with MTBI and not seen in litigants with moderate and severe brain injury who passed PVTs. Three predictive CVMT models were derived. When failure on one of the models is observed then concerns about the credibility of visual memory performance should be considered with particular attention to other stand-alone and embedded measures of performance validity.

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