Abstract
In this study, we investigated network configurations of 14 Clinical risk and protective factors in a sample of 317 male forensic psychiatric patients across two time points: at the time of admission to the forensic psychiatric centers (T1) and at the time of unconditional release (T2). In terms of network structure, the strongest risk edge was between “hostility–violation of terms” at T1, and between “hostility–impulsivity” at T2. “Problem insight–crime responsibility” was the strongest protective edge, and “impulsivity–coping skills” was the strongest between-cluster edge, at both time points, respectively. In terms of strength centrality, “cooperation with treatment” had the highest strength centrality at both measurement occasions. This study expands the risk assessment field toward a better understanding of dynamic relationships between individual clinical risk and protective factors and points to the highly central risk and protective factors, which would be the best for future treatment targets.
Highlights
A large amount of research has been done on dynamic risk factors (DRFs) that are related to criminal behavior and reoffending
Supported by general personality models, cognitive social learning perspectives, and the risk–need– responsivity model (RNR: Andrews & Bonta, 2006; Andrews et al, 2012), eight risk factors (Central Eight) were identified, which are prominent in the explanation and prediction of criminal behavior, treatment outcome, and reoffending
Consistent with the RNR and good lives model (GLM) model, we found that protective factors were more influential than crime-related risk factors at T2
Summary
A large amount of research has been done on dynamic risk factors (DRFs) that are related to criminal behavior and reoffending. Supported by general personality models, cognitive social learning perspectives, and the risk–need– responsivity model (RNR: Andrews & Bonta, 2006; Andrews et al, 2012), eight risk factors (Central Eight) were identified, which are prominent in the explanation and prediction of criminal behavior, treatment outcome, and reoffending. The Central Eight risk factors have played subsequently a crucial role in the development of various risk assessment tools and are aimed to predict the likelihood that a prisoner or forensic psychiatric patient will reoffend in the same offense or another one after release These tools are used to investigate the treatment progress of forensic patients during their stay in the institution and to estimate the likelihood of future inpatient violence (Jeandarme et al, 2019). Networks with more strongly connected risk factors are more prone to future inpatient violence and/or reoffending (Fried et al, 2017)
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