Use of the Wisconsin Card Sorting Test in the Detection of Malingering in Student Simulator and Patient Samples

Abstract

We analyzed the ability of the Wisconsin Card Sorting Test to distinguish between 41 malingering and 31 normal undergraduates, and 17 probable malingering and 16 brain injured patients. A logistic regression consisting of number of categories (CAT) and failure to maintain set (FMS) distinguished malingering and normal undergraduates with 70.7% sensitivity, 87.1% specificity, and 77.8% overall classification, and distinguished patients suspected of malingering from brain injured controls with 82.4% sensitivity, 93. 3% specificity, and 87.5% overall classification.

Wisconsin Card Sorting Test in chronic severe traumatic brain injury: factor structure and performance subgroups

“…High FMS has been observed in patients with known or suspected orbitofrontal pathology [13] and, thus, may be a negative outcome indicator similar to the presence of anosmia [16]. Further, this study indicates that high FMS does reflect a valid WCST profile and is not indicative of poor motivation or malingering, as has been argued [17]. Cluster 2 was characterized by poor problem-solving, which could indicate the need for a special focus on problem-solving, hypothesis testing and critical/flexible thinking during rehabilitation.…”

Executive dysfunction in traumatic brain injury: The effects of injury severity and effort on the Wisconsin Card Sorting Test

“…However, effort during testing has a direct impact on WCST performance (Bernard, McGrath, & Houston, 1996;Greve, Bianchini, Mathias, Houston, & Crouch, 2002a;Greve, Heinly, Bianchini, & Love, 2009;King et al, 2002;Suhr & Boyer, 1999) and should be considered as a possible explanation for observed impairments. Binder, Kelly, Villanueva, and Winslow (2003) reported that mild TBI had no significant impact on WCST perseverative responses when motivation during testing was controlled for using a measure of cognitive performance validity.…”

The BDAE Complex Ideational Material—a Measure of Receptive Language or Performance Validity?

“…Against the Suhr and Boyer (1999) equation, all CIM cutoffs cleared the lower threshold for specificity. The ≤9 raw score cutoff had .36 sensitivity.…”

“…To maximize the purity of the reference groups used to calibrate the target PVT, Borderline cases were excluded from (Heinly et al, 2005;Spencer et al, 2013); LM Logical Memory (Bortnik et al, 2010;Pearson, 2009), CVLT-II recognition hits (RH CVLT-II ; Wolfe et al, 2010), and Forced Choice Recognition (FCR CVLT-II ; Moore & Donders, 2004;Bauer et al, 2005) cross-validation analyses, following recommendations by Greve and Bianchini (2004). Finally, the logistical regression equations developed by Suhr and Boyer (1999) and King et al (2002) were used as alternative reference PVTs. They were selected because they are based on WCST variables that are not verbally mediated (like the EI-5) or recognition based (like the TOMM).…”