The prediction of criminal recidivism using routinely available file information

Objective. The aim of the present study was to cross-validate the investigation of Buchanan and Leese (2006) into the prediction of criminal recidivism. Method. The sample comprised offenders in the criminal justice system of the Canton of Zürich – Switzerland, who were discharged to the community....

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Autores principales:	Diana Fries, Astrid Rossegger, Jérôme Endrass, Jay P. Singh
Formato:	article
Lenguaje:	EN ES
Publicado:	Universidad de San Buenaventura 2013
Materias:	Risk Assessment Violence Forensic Recidivism. Psychology BF1-990
Acceso en línea:	https://doaj.org/article/e681b81f7bae470fb0d33bafc6d167bd
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spelling	oai:doaj.org-article:e681b81f7bae470fb0d33bafc6d167bd2021-11-25T02:22:40ZThe prediction of criminal recidivism using routinely available file information10.21500/20112084.6712011-20842011-7922https://doaj.org/article/e681b81f7bae470fb0d33bafc6d167bd2013-12-01T00:00:00Zhttps://revistas.usb.edu.co/index.php/IJPR/article/view/671https://doaj.org/toc/2011-2084https://doaj.org/toc/2011-7922Objective. The aim of the present study was to cross-validate the investigation of Buchanan and Leese (2006) into the prediction of criminal recidivism. Method. The sample comprised offenders in the criminal justice system of the Canton of Zürich – Switzerland, who were discharged to the community. Participants were followed, and evidence of subsequent charges and convictions for both general and serious recidivism was investigated at fixed periods of 2.5, 6.5, and 10.5 years. The predictive validity of socio-demographic, criminal history, and legal class information was assessed using logistic regression as well as log-likelihood, receiver operating characteristic curve, and contingency analyses. Results. A multivariable model including age and criminal history information was found to produce the highest rates of predictive validity for general and serious recidivism. Conclusion. Information regularly accessible in forensic practice may be able to guide clinicians as to the recidivism risk level of their patients.Diana FriesAstrid RosseggerJérôme EndrassJay P. SinghUniversidad de San BuenaventuraarticleRisk AssessmentViolenceForensicRecidivism.PsychologyBF1-990ENESInternational Journal of Psychological Research, Vol 6, Iss 2 (2013)
institution	DOAJ
collection	DOAJ
language	EN ES
topic	Risk Assessment Violence Forensic Recidivism. Psychology BF1-990
spellingShingle	Risk Assessment Violence Forensic Recidivism. Psychology BF1-990 Diana Fries Astrid Rossegger Jérôme Endrass Jay P. Singh The prediction of criminal recidivism using routinely available file information
description	Objective. The aim of the present study was to cross-validate the investigation of Buchanan and Leese (2006) into the prediction of criminal recidivism. Method. The sample comprised offenders in the criminal justice system of the Canton of Zürich – Switzerland, who were discharged to the community. Participants were followed, and evidence of subsequent charges and convictions for both general and serious recidivism was investigated at fixed periods of 2.5, 6.5, and 10.5 years. The predictive validity of socio-demographic, criminal history, and legal class information was assessed using logistic regression as well as log-likelihood, receiver operating characteristic curve, and contingency analyses. Results. A multivariable model including age and criminal history information was found to produce the highest rates of predictive validity for general and serious recidivism. Conclusion. Information regularly accessible in forensic practice may be able to guide clinicians as to the recidivism risk level of their patients.
format	article
author	Diana Fries Astrid Rossegger Jérôme Endrass Jay P. Singh
author_facet	Diana Fries Astrid Rossegger Jérôme Endrass Jay P. Singh
author_sort	Diana Fries
title	The prediction of criminal recidivism using routinely available file information
title_short	The prediction of criminal recidivism using routinely available file information
title_full	The prediction of criminal recidivism using routinely available file information
title_fullStr	The prediction of criminal recidivism using routinely available file information
title_full_unstemmed	The prediction of criminal recidivism using routinely available file information
title_sort	prediction of criminal recidivism using routinely available file information
publisher	Universidad de San Buenaventura
publishDate	2013
url	https://doaj.org/article/e681b81f7bae470fb0d33bafc6d167bd
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The prediction of criminal recidivism using routinely available file information

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