Predicting criminal and violent outcomes in psychiatry: a meta-analysis of diagnostic accuracy.

ABSTRACT: Although reducing criminal outcomes in individuals with mental illness have long been a priority for governments worldwide, there is still a lack of objective and highly accurate tools that can predict these events at an individual level. Predictive machine learning models may provide a unique opportunity to identify those at the highest risk of criminal activity and facilitate personalized rehabilitation strategies. Therefore, this systematic review and meta-analysis aims to describe the diagnostic accuracy of studies using machine learning techniques to predict criminal and violent outcomes in psychiatry. We performed meta-analyses using the mada, meta, and dmetatools packages in R to predict criminal and violent outcomes in psychiatric patients (n = 2428) (Registration Number: CRD420191

SUBMITTER: Watts D 

PROVIDER: S-EPMC9643469 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature