Are psychological measures and actuarial data equally effective in discriminating among the prison population? Analysis by crimes

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Title: Are psychological measures and actuarial data equally effective in discriminating among the prison population? Analysis by crimes
Authors: Burneo-Garcés, Carlos | Fernández-Alcántara, Manuel | Marín-Morales, Agar | Pérez-García, Miguel
Research Group/s: Psicología Aplicada a la Salud y Comportamiento Humano (PSYBHE)
Center, Department or Service: Universidad de Alicante. Departamento de Psicología de la Salud
Keywords: Psychological measures | Actuarial data | Discriminating | Prison population | Crimes
Knowledge Area: Personalidad, Evaluación y Tratamiento Psicológico
Issue Date: 6-Jun-2018
Publisher: Public Library of Science (PLoS)
Citation: Burneo-Garcés C, Fernández-Alcántara M, Marín-Morales A, Pérez-García M (2018) Are psychological measures and actuarial data equally effective in discriminating among the prison population? Analysis by crimes. PLoS ONE 13(6): e0198251. https://doi.org/10.1371/journal.pone.0198251
Abstract: The ability of a wide range of psychological and actuarial measures to characterize crimes in the prison population has not yet been compared in a single study. Our main objective was to determine if the discriminant capacity of psychological measures (PM) and actuarial data (AD) varies according to the crime. An Ecuadorian sample of 576 men convicted of Robbery, Murder, Rape and Drug Possession crimes was evaluated through an ad hoc questionnaire, prison files and the Spanish adaptation of the Personality Assessment Inventory. Discriminant analysis was used to establish, for each crime, the discriminant capacity and the classification accuracy of a model composed of AD (socio-demographic and judicial measures) and a second model incorporating PM. The AD showed a superior discriminant capacity, whilst the contribution of both types of measures varied according to the crime. The PM generated some increase in the correct classification percentages for Murder, Rape and Drug Possession, but their contribution was zero for the crime of Robbery. Specific profiles of each crime were obtained from the strongest significant correlations between the value of each explanatory variable and the probability of belonging to the crime. The AD model is more robust when these four crimes are characterized. The contribution of AD and PM depends on the crime, and the inclusion of PM in actuarial models moderately optimizes the classification accuracy of Murder, Rape, and Drug Possession crimes.
Sponsor: The authors would like to thank the Health Coordination Zone 8 (Ministry of Public Health of Ecuador, MSP) for supporting and partially funding this study, along with the Sub-secretary of Rehabilitation, Reintegration, and Precautionary Measures for Adults (Ministry of Justice, Human Rights, and Cults of Ecuador, MJDHC) for issuing permits; the authorities of the Guayaquil Social Rehabilitation Center and Regional Guayas Social Rehabilitation Center for the facilities offered to develop the fieldwork; and the team of psychologists from the Health Coordination Zone 8 and Health Coordination Zone 5 (MSP) for the fieldwork conducted. In addition, this work was partially supported by the Regional Ministry of Economy, Innovation and Science from Andalusian Government (Project: P2012-SEJ1723) and the Spanish Ministry of Science and Innovation (Project: PSI2013-42792-R).
URI: http://hdl.handle.net/10045/76631
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0198251
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2018 Burneo-Garcés et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Peer Review: si
Publisher version: https://doi.org/10.1371/journal.pone.0198251
Appears in Collections:INV - PSYBHE - Artículos de Revistas

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