The University of Southampton
University of Southampton Institutional Repository

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

Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory–Revised (PPI-R)
Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory–Revised (PPI-R)
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.
psychopathy, genetic algorithm, abbreviation, personality
1040-3590
194-202
Eisenbarth, Hedwig
41af3dcb-da48-402b-a488-49de88e64f0c
Lilienfeld, Scott O.
1191d50f-7cb5-4d26-b489-8a79e9f162d1
Yarkoni, Tal
4b94d9cc-6985-4778-b3af-e980beb11cb6
Eisenbarth, Hedwig
41af3dcb-da48-402b-a488-49de88e64f0c
Lilienfeld, Scott O.
1191d50f-7cb5-4d26-b489-8a79e9f162d1
Yarkoni, Tal
4b94d9cc-6985-4778-b3af-e980beb11cb6

Eisenbarth, Hedwig, Lilienfeld, Scott O. and Yarkoni, Tal (2015) Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory–Revised (PPI-R). Psychological Assessment, 27 (1), 194-202. (doi:10.1037/pas0000032). (PMID:25436663)

Record type: Article

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.

Text
7F2D410F-C708-4004-9999-1B4C94B9C1A8.pdf - Version of Record
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 30 September 2014
Published date: March 2015
Keywords: psychopathy, genetic algorithm, abbreviation, personality
Organisations: Psychology

Identifiers

Local EPrints ID: 384794
URI: http://eprints.soton.ac.uk/id/eprint/384794
ISSN: 1040-3590
PURE UUID: 17e55d5f-24fb-477f-8094-b15bdd1455bf
ORCID for Hedwig Eisenbarth: ORCID iD orcid.org/0000-0002-0521-2630

Catalogue record

Date deposited: 11 Jan 2016 11:54
Last modified: 15 Mar 2024 03:51

Export record

Altmetrics

Contributors

Author: Hedwig Eisenbarth ORCID iD
Author: Scott O. Lilienfeld
Author: Tal Yarkoni

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×