This study was designed to expand on a recent meta-analysis that identified ≤42 as the optimal cutoff on the Word Choice Test (WCT). We examined the base rate of failure and the classification accuracy of various WCT cutoffs in four independent clinical samples ( N = 252) against various psychometrically defined criterion groups. WCT ≤ 47 achieved acceptable combinations of specificity (.86–.89) at .49 to .54 sensitivity. Lowering the cutoff to ≤45 improved specificity (.91–.98) at a reasonable cost to sensitivity (.39–.50). Making the cutoff even more conservative (≤42) disproportionately sacrificed sensitivity (.30–.38) for specificity (.98–1.00), while still classifying 26.7% of patients with genuine and severe deficits as non-credible. Critical item (.23–.45 sensitivity at .89–1.00 specificity) and time-to-completion cutoffs (.48–.71 sensitivity at .87–.96 specificity) were effective alternative/complementary detection methods. Although WCT ≤ 45 produced the best overall classification accuracy, scores in the 43 to 47 range provide comparable objective psychometric evidence of non-credible responding. Results question the need for designating a single cutoff as “optimal,” given the heterogeneity of signal detection environments in which individual assessors operate. As meta-analyses often fail to replicate, ongoing research is needed on the classification accuracy of various WCT cutoffs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.