Date of Award

8-31-2018

Publication Type

Doctoral Thesis

Degree Name

Ph.D.

Department

Psychology

Keywords

effort testing, malingering, neuropsychological assessment, neuropsychology, performance validity, symptom validity

Supervisor

Erdodi, Laszlo

Rights

info:eu-repo/semantics/openAccess

Abstract

In neuropsychological assessment, performance validity tests (PVTs) are used to assess whether patients’ performances on cognitive testing represent their true ability levels. Higher base rates of PVT failure (BRFail) have been consistently found in the context of external incentives to appear impaired (e.g., medical-legal settings) as compared to settings without such incentives (e.g., clinical referrals). Despite the exponential growth of interest and empirical research on PVTs within the past decades, most studies have had relatively limited sample sizes and focused on a small number of instruments and clinical populations. To address this void in large-scale research, this dissertation aimed to characterize performance on 14 PVTs of interest (3 free-standing PVTs and 11 embedded validity indicators) in a large sample of adults assessed in a predominantly medical-legal setting (N = 4,721). Specifically, BRFail were reported as a function of several patient characteristics (i.e., diagnosis, age, education, gender, and English language status) in the overall sample (Study 1) and in a subsample demonstrating valid performance on an external criterion PVT (the Word Memory Test [WMT], Study 2). Classification accuracies for various cutoffs on each PVT of interest were also investigated against the WMT (Study 3). In Studies 1 and 2, free-standing PVTs tended to be more robust to the effects of patient characteristics than embedded validity indicators. In Study 3, the majority of previously published cutoffs for PVTs of interest achieved acceptable specificity, with three isolated exceptions. Free-standing PVTs demonstrated better classification accuracy than embedded validity indicators, although no PVT achieved perfect classification accuracy. Taken together, the results of this dissertation highlight the importance of using multiple PVTs and interpreting individual PVT scores in the context of patient characteristics rather than by rigidly adhering to omnibus cutoffs.

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