Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach.

ABSTRACT:

Background

Prolonged forensic psychiatric hospitalizations have raised ethical, economic, and clinical concerns. Due to the confounded nature of factors affecting length of stay of psychiatric offender patients, prior research has called for the application of a new statistical methodology better accommodating this data structure. The present study attempts to investigate factors contributing to long-term hospitalization of schizophrenic offenders referred to a Swiss forensic institution, using machine learning algorithms that are better suited than conventional methods to detect nonlinear dependencies between variables.

Methods

In this retrospective file and registry study, multidisciplinary notes of 143 schizophrenic offenders were reviewed using a structured protocol on p

SUBMITTER: Kirchebner J 

PROVIDER: S-EPMC7201968 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature