Classification accuracy of the rare symptoms and symptom combinations scales of the Structured Inventory of Malingered Symptomatology in three archival samples.

Abstract

The Structured Inventory of Malingered Symptomatology (SIMS; Widows & Smith, 2005) is a 75-item self-report measure intended to screen for potentially feigned symptoms of mental illness and/or cognitive impairment. We investigated the classification accuracy of 2 new detection scales (Rare Symptoms [RS] and Symptom Combinations [SC]) developed by Rogers, Robinson, and Gillard (2014) that appeared useful in identifying simulated mental disorder in their derivation sample of psychiatric inpatients. We hypothesized that the rates of classification accuracy Rogers et al. reported for these 2 scales would generalize to other samples in which the utility of the SIMS previously has been investigated. We computed RS and SC scores from archival SIMS data collected as part of 3 research projects investigating malingering detection methods: (a) general population prison inmates and inmates in a prison psychiatric unit receiving treatment for mental disorder (N = 115), (b) college students (N = 196), and (3) community-dwelling adults (N = 48). Results supported the global classification accuracy of RS and SC but the suggested cut-score for both scales (>6) produced poor sensitivity. Lower potential cut-offs did, however, improve sensitivity to feigning somewhat while not excessively diminishing specificity. These results emphasize the importance of generalizability research when investigating the clinical utility of forensic mental health assessment methods, particularly specific decision rules used to classify individuals into discrete categories. (PsycInfo Database Record (c) 2020 APA, all rights reserved).