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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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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 |
format | Online Article Text |
id | pubmed-7495711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
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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