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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| Veröffentlicht in: | International journal of offender therapy and comparative criminology 2020-11, Vol.64 (15), p.1491-1513 |
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| container_title | International journal of offender therapy and comparative criminology |
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| creator | Van der Linde, Robin Bogaerts, Stefan Garofalo, Carlo Blaauw, Eric De Caluwé, Elien Billen, Eva Spreen, Marinus |
| 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 |
| doi_str_mv | 10.1177/0306624X20909219 |
| format | Article |
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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</description><identifier>ISSN: 0306-624X</identifier><identifier>EISSN: 1552-6933</identifier><identifier>DOI: 10.1177/0306624X20909219</identifier><identifier>PMID: 32114842</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Age ; Age differences ; Age groups ; Chi-square test ; Crime ; Forensic psychiatry ; Individual differences ; Latent growth curve models ; Patients ; Recidivists ; Risk factors ; Time</subject><ispartof>International journal of offender therapy and comparative criminology, 2020-11, Vol.64 (15), p.1491-1513</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020 2020 SAGE Publications</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c509t-5d36064da8af4b1f795cdfae2ebd08dc8d403f2f75a17484747e93102b65b3ef3</citedby><cites>FETCH-LOGICAL-c509t-5d36064da8af4b1f795cdfae2ebd08dc8d403f2f75a17484747e93102b65b3ef3</cites><orcidid>0000-0003-4491-9492 ; 0000-0003-2306-6961 ; 0000-0001-6639-6739</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0306624X20909219$$EPDF$$P50$$Gsage$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0306624X20909219$$EHTML$$P50$$Gsage$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,21818,27923,27924,30998,33773,43620,43621</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32114842$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Van der Linde, Robin</creatorcontrib><creatorcontrib>Bogaerts, Stefan</creatorcontrib><creatorcontrib>Garofalo, Carlo</creatorcontrib><creatorcontrib>Blaauw, Eric</creatorcontrib><creatorcontrib>De Caluwé, Elien</creatorcontrib><creatorcontrib>Billen, Eva</creatorcontrib><creatorcontrib>Spreen, Marinus</creatorcontrib><title>Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients</title><title>International journal of offender therapy and comparative criminology</title><addtitle>Int J Offender Ther Comp Criminol</addtitle><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. 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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. 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| subjects | Age Age differences Age groups Chi-square test Crime Forensic psychiatry Individual differences Latent growth curve models Patients Recidivists Risk factors Time |
| title | Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients |
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