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Using a Genetic Algorithm to Abbreviate the Psychopathic Personality Inventory–Revised (PPI-R)

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Hedwig Eisenbarth at Victoria University of Wellington
Hedwig Eisenbarth
Scott O. Lilienfeld
Scott O. Lilienfeld
Scott O. Lilienfeld
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Tal Yarkoni
Tal Yarkoni
Tal Yarkoni
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Some self-report measures of personality and personality disorders, including the widely used Psychopathic Personality Inventory-Revised (PPI-R), are lengthy and time-intensive. In recent work, we introduced an automated genetic algorithm (GA)-based method for abbreviating psychometric measures. In Study 1, we used this approach to generate a short (40-item) version of the PPI-R using 3 large-N German student samples (total N = 1,590). The abbreviated measure displayed high convergent correlations with the original PPI-R, and outperformed an alternative measure constructed using a conventional approach. Study 2 tested the convergent and discriminant validity of this short version in a fourth student sample (N = 206) using sensation-seeking and sensitivity to reward and punishment scales, again demonstrating similar convergent and discriminant validity for the PPI-R-40 compared with the full version. In a fifth community sample of North American participants acquired using Amazon Mechanical Turk, the PPI-R-40 showed similarly high convergent correlations, demonstrating stability across language, culture, and data-collection method. Taken together, these studies suggest that the GA approach is a viable method for abbreviating measures of psychopathy, and perhaps personality measures in general. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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