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Title: Using the biopsychosocial model for identifying subgroups of detained juveniles at diferent risk of re-ofending in practice: a latent class regression analysis approach
Author(s): E. L. de Ruigh, S. Bouwmeester, A. Popma, R.R.J.M. Vermeiren, L. van Domburg and L.M.C. Jansen
Journal: Child and Adolescent Psychiatry and Mental Health
Year: 2021
Volume: 15
Issue: 1
Pages: 1-15
File URL: /vuams-pubs/s13034-021-00379-1.pdf
Keywords: Juvenile ofenders, Reofending, Latent class regression, Subgroups, Neurobiology, Risk assessment
Abstract: Background: Juvenile delinquents constitute a heterogeneous group, which complicates decision-making based on risk assessment. Various psychosocial factors have been used to defne clinically relevant subgroups of juvenile ofenders, while neurobiological variables have not yet been integrated in this context. Moreover, translation of neurobiological group diferences to individual risk assessment has proven difcult. We aimed to identify clinically relevant subgroups associated with diferential youth ofending outcomes, based on psychosocial and neurobiological characteristics, and to test whether the resulting model can be used for risk assessment of individual cases. Methods: A group of 223 detained juveniles from juvenile justice institutions was studied. Latent class regression analysis was used to detect subgroups associated with diferential ofending outcome (recidivism at 12 month followup). As a proof of principle, it was tested in a separate group of 76 participants whether individual cases could be assigned to the identifed subgroups, using a prototype ‘tool’ for calculating class membership. Results: Three subgroups were identifed: a ‘high risk—externalizing’ subgroup, a ‘medium risk—adverse environment’ subgroup, and a ‘low risk—psychopathic traits’ subgroup. Within these subgroups, both autonomic nervous system and neuroendocrinological measures added diferentially to the prediction of subtypes of reofending (no, non-violent, violent). The ‘tool’ for calculating class membership correctly assigned 92.1% of participants to a class and reofending risk. Conclusions: The LCRA approach appears to be a useful approach to integrate neurobiological and psychosocial risk factors to identify subgroups with diferent re-ofending risk within juvenile justice institutions. This approach may be useful in the development of a biopsychosocial assessment tool and may eventually help clinicians to assign individuals to those subgroups and subsequently tailor intervention based on their re-ofending risk.

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