Clarifying the relationship between mental illness and recidivism using machine learning: A retrospective study.

ABSTRACT:

Objective

There is currently inconclusive evidence regarding the relationship between recidivism and mental illness. This retrospective study aimed to use rigorous machine learning methods to understand the unique predictive utility of mental illness for recidivism in a general population (i.e.; not only those with mental illness) prison sample in the United States.

Method

Participants were adult men (n = 322) and women (n = 72) who were recruited from three prisons in the Midwest region of the United States. Three model comparisons using Bayesian correlated t-tests were conducted to understand the incremental predictive utility of mental illness, substance use, and crime and demographic variables for recidivism prediction. Three classification statistical algorithms were co

SUBMITTER: Cohen TR 

PROVIDER: S-EPMC10890739 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature