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Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients

In this study, growth trajectories (from admission until unconditional release) of crime-related dynamic risk factors were investigated in a sample of Dutch forensic patients (N = 317), using latent growth curve modeling. After testing the unconditional model, three predictors were added: first-time...

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Autores principales: Van der Linde, Robin, Bogaerts, Stefan, Garofalo, Carlo, Blaauw, Eric, De Caluwé, Elien, Billen, Eva, Spreen, Marinus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495711/
https://www.ncbi.nlm.nih.gov/pubmed/32114842
http://dx.doi.org/10.1177/0306624X20909219
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author Van der Linde, Robin
Bogaerts, Stefan
Garofalo, Carlo
Blaauw, Eric
De Caluwé, Elien
Billen, Eva
Spreen, Marinus
author_facet Van der Linde, Robin
Bogaerts, Stefan
Garofalo, Carlo
Blaauw, Eric
De Caluwé, Elien
Billen, Eva
Spreen, Marinus
author_sort Van der Linde, Robin
collection PubMed
description In this study, growth trajectories (from admission until unconditional release) of crime-related dynamic risk factors were investigated in a sample of Dutch forensic patients (N = 317), using latent growth curve modeling. After testing the unconditional model, three predictors were added: first-time offender versus recidivist, age, and treatment duration. Postanalyses were chi-square difference tests, t tests, and analyses of variance (ANOVAs) to assess differences in trajectories. Overall, on scale level, a decrease of risk factors over time was found. The predictors showed no significant slope differences although age and treatment duration differed significantly at some time points. The oldest age group performed worse, especially at later time points. Treatment duration effects were found at the second time point. Our results that forensic patients show a decrease in crime-related risk factors may indicate that treatment is effective. This study also found differences in growth rates, indicating the effect of individual differences
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spelling pubmed-74957112020-09-24 Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients Van der Linde, Robin Bogaerts, Stefan Garofalo, Carlo Blaauw, Eric De Caluwé, Elien Billen, Eva Spreen, Marinus Int J Offender Ther Comp Criminol Articles In this study, growth trajectories (from admission until unconditional release) of crime-related dynamic risk factors were investigated in a sample of Dutch forensic patients (N = 317), using latent growth curve modeling. After testing the unconditional model, three predictors were added: first-time offender versus recidivist, age, and treatment duration. Postanalyses were chi-square difference tests, t tests, and analyses of variance (ANOVAs) to assess differences in trajectories. Overall, on scale level, a decrease of risk factors over time was found. The predictors showed no significant slope differences although age and treatment duration differed significantly at some time points. The oldest age group performed worse, especially at later time points. Treatment duration effects were found at the second time point. Our results that forensic patients show a decrease in crime-related risk factors may indicate that treatment is effective. This study also found differences in growth rates, indicating the effect of individual differences SAGE Publications 2020-03-02 2020-11 /pmc/articles/PMC7495711/ /pubmed/32114842 http://dx.doi.org/10.1177/0306624X20909219 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Articles
Van der Linde, Robin
Bogaerts, Stefan
Garofalo, Carlo
Blaauw, Eric
De Caluwé, Elien
Billen, Eva
Spreen, Marinus
Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title_full Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title_fullStr Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title_full_unstemmed Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title_short Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients
title_sort trajectories of dynamic risk factors during forensic treatment: growth trajectory of clinical risk factors in a sample of dutch forensic patients
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495711/
https://www.ncbi.nlm.nih.gov/pubmed/32114842
http://dx.doi.org/10.1177/0306624X20909219
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