Network Dynamics of Risk and Protective Factors in Forensic Psychiatric Patients: Exploring Substance Use Disorder and Treatment Motivation

This study investigated longitudinal networks of risk and protective factors and treatment motivation among forensic psychiatric patients (FPPs) with and without substance use disorder (SUD) at admission (T1) and unconditional release (T2). The sample consisted of 468 FPP ( Mage = 53.97, SDage = 9.99, 86.5% male, 34.6% SUD), and networks were estimated using the Gaussian Graphical Model. The most central network factors were impulsivity, treatment motivation, and treatment violation. For the protective factors, the strongest correlations emerged between problem insight and treatment motivation at T1, and between social and coping skills at T2. For risk factors this was between hostility and treatment violation at T1, and antisocial behavior and treatment violation at T2. While larger sample sizes and stability issues should be considered in future studies, the networks approach provides important implications for tailored inpatient forensic treatment.

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Publication Details

Journal
Criminal Justice and Behavior
Published
2024-11-18
DOI
https://doi.org/10.1177/00938548241296491
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
1.52
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article

Network Dynamics of Risk and Protective Factors in Forensic Psychiatric Patients: Exploring Substance Use Disorder and Treatment Motivation

Stefan Bogaerts, Lotte Bant
3 citations
Criminal Justice and Behavior
Mental Health Research Topics
1.52
article

Network Dynamics of Risk and Protective Factors in Forensic Psychiatric Patients: Exploring Substance Use Disorder and Treatment Motivation

Stefan Bogaerts, Lotte Bant
article en
3 citations

Abstract

This study investigated longitudinal networks of risk and protective factors and treatment motivation among forensic psychiatric patients (FPPs) with and without substance use disorder (SUD) at admission (T1) and unconditional release (T2). The sample consisted of 468 FPP ( Mage = 53.97, SDage = 9.99, 86.5% male, 34.6% SUD), and networks were estimated using the Gaussian Graphical Model. The most central network factors were impulsivity, treatment motivation, and treatment violation. For the protective factors, the strongest correlations emerged between problem insight and treatment motivation at T1, and between social and coping skills at T2. For risk factors this was between hostility and treatment violation at T1, and antisocial behavior and treatment violation at T2. While larger sample sizes and stability issues should be considered in future studies, the networks approach provides important implications for tailored inpatient forensic treatment.

Criminal Justice and BehaviorVol. 52(3)
Tilburg University (NL)
Good health and well-being
Openalex Percentile: Top 15%
Mental Health Research Topics
1.52
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