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

Objective: 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. Hypothesis: 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. Method: 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: 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. Conclusion: 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.