Escape and absconding among offenders with schizophrenia spectrum disorder - an explorative analysis of characteristics.

ABSTRACT:

Background

Escape and absconding, especially in forensic settings, can have serious consequences for patients, staff and institutions. Several characteristics of affected patients could be identified so far, albeit based on heterogeneous patient populations, a limited number of possible factors and basal statistical analyses. The aim of this study was to determine the most important characteristics among a large number of possible variables and to describe the best statistical model using machine learning in a homogeneous group of offender patients with schizophrenia spectrum disorder.

Methods

A database of 370 offender patients suffering from schizophrenia spectrum disorder and 507 possible predictor variables was explored by machine learning. To counteract overfitting, the

SUBMITTER: Kirchebner J 

PROVIDER: S-EPMC7931588 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature