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International Journal of Psychology Sciences

Vol. 2, Issue 1, Part A (2020)

Meta-analysis ofscale cutoffs in the Structured Inventory ofMalingered Symptomatology


Zack Cernovsky, Milad Fattahi


Objective: Using various published data, we estimated the rates of false positives in samples of normal controls when the usual diagnostic cutoffs of the Structured Inventory of Malingered Symptomatology (SIMS) are applied as stipulated in the SIMS manual for all of its 5 scales and for the total score. Method: The original normative data (means and SDs) by Glenn Smith published in SIMS manual for all of its 5 scales and for the total score were used to calculate z scores of each recommended cutoff stipulated in the SIMS manual and thus to estimate, via the assumption of normal distribution, proportions of normal persons that would exceed these cutoffs. The same procedure was then used on meta-analytically combined data from 9 published samples of normal controls. Results: The proportions of 34 normal controls (non-malingerers) in Smith’s original normative sample of presumably healthy undergraduates exceeding the cutoffs for the 5 SIMS scales were 42.1% for the Psychosis (P) scale, 30.9% for Low Intelligence (LI), 29.8% for Amnestic Disorders (AM), 19.8% for the Affective Disorders (AF) scale, and 15.9% for Neurologic Impairment (NI): these persons are misclassified by the cutoffs as “malingerers.” In the meta-analytic sample of controls, the highest proportions of normal controls misdiagnosed as malingerers were 41.7% for Low Intelligence (LI) scale, 28.8% for Psychosis (P), 24.8% for Affective Disorders (AF), 17.9% for Amnestic Disorders (AM), and 15.9% for Neurologic Impairment (NI). The lowest proportions of misdiagnosed normal persons were on the SIMS total score: 4.5% in Smith’s normative sample and 4.6% of persons in the meta-analytically combined sample of 500 normal controls. Conclusion: SIMS cutoffs for its scales misclassify too many normal persons as malingerers. These normal controls were presumably young healthy persons. Since the SIMS items list mainly legitimate medical symptoms (i.e., not items with a reasonable capacity to differentiate legitimate patients from malingerers), the proportions of legitimately injured or otherwise ill persons misclassified as malingerers are likely to be much higher than those reported here for normal controls.

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How to cite this article:
Zack Cernovsky, Milad Fattahi. Meta-analysis ofscale cutoffs in the Structured Inventory ofMalingered Symptomatology. Int. J. Psychol. Sci. 2020;2(1):01-07. DOI: 10.33545/26648377.2020.v2.i1a.19