Literature DB >> 25436663

Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory-Revised (PPI-R).

Hedwig Eisenbarth1, Scott O Lilienfeld2, Tal Yarkoni3.   

Abstract

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. 2015 APA, all rights reserved

Entities:  

Mesh:

Year:  2014        PMID: 25436663     DOI: 10.1037/pas0000032

Source DB:  PubMed          Journal:  Psychol Assess        ISSN: 1040-3590


  12 in total

1.  A comparison of self-report measures of psychopathy among nonforensic samples using item response theory analyses.

Authors:  Siny Tsang; Randall T Salekin; C Adam Coffey; Jennifer Cox
Journal:  Psychol Assess       Date:  2017-04-13

2.  Children of parents with BED have more eating behavior disturbance than children of parents with obesity or healthy weight.

Authors:  Janet A Lydecker; Carlos M Grilo
Journal:  Int J Eat Disord       Date:  2016-11-12       Impact factor: 4.861

3.  Development of the Resident Wellness Scale for Measuring Resident Wellness.

Authors:  R Brent Stansfield; Dan Giang; Tsveti Markova
Journal:  J Patient Cent Res Rev       Date:  2019-01-28

4.  Triarchic Model Traits as Predictors of Bullying and Cyberbullying in Adolescence.

Authors:  Andrea Baroncelli; Emily R Perkins; Enrica Ciucci; Paul J Frick; Christopher J Patrick; Claudio Sica
Journal:  J Interpers Violence       Date:  2020-06-29

Review 5.  Psychometric and Machine Learning Approaches to Reduce the Length of Scales.

Authors:  Oscar Gonzalez
Journal:  Multivariate Behav Res       Date:  2020-08-04       Impact factor: 5.923

6.  Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

Authors:  Ulrich Schroeders; Oliver Wilhelm; Gabriel Olaru
Journal:  PLoS One       Date:  2016-11-28       Impact factor: 3.240

7.  The effect of psychopathy on cooperative strategies in an iterated Prisoner's Dilemma experiment with emotional feedback.

Authors:  Martina Testori; Thehela O A Harris; Rebecca B Hoyle; Hedwig Eisenbarth
Journal:  Sci Rep       Date:  2019-02-19       Impact factor: 4.379

8.  Using Genetic Algorithms in a Large Nationally Representative American Sample to Abbreviate the Multidimensional Experiential Avoidance Questionnaire.

Authors:  Baljinder K Sahdra; Joseph Ciarrochi; Philip Parker; Luca Scrucca
Journal:  Front Psychol       Date:  2016-02-24

9.  Designation and psychometric properties of the Short Form Postpartum Quality of Life Questionnaire (SF-PQOL): an application of multidimensional item response theory and genetic algorithm.

Authors:  Fariba Nikan; Mohammad Asghari Jafarabadi; Sakineh Mohammad-Alizadeh-Charandabi; Mojgan Mirghafourvand
Journal:  Health Promot Perspect       Date:  2018-07-07

10.  A genetic algorithm to find optimal reading test word subsets for estimating full-scale IQ.

Authors:  Ian van der Linde; Peter Bright
Journal:  PLoS One       Date:  2018-10-18       Impact factor: 3.240

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