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

Journal: BMC psychiatry
PMID:

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.

Authors

  • Johannes Kirchebner
    University Hospital of Psychiatry Zurich, Department of Forensic Psychiatry, Zurich, Switzerland. johannes.kirchebner@puk.zh.ch.
  • Moritz Philipp Günther
    University Hospital of Psychiatry Zurich, Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland.
  • Martina Sonnweber
    University Hospital of Psychiatry Zurich, Department of Forensic Psychiatry, Zurich, Switzerland.
  • Alice King
    University Hospital of Psychiatry Zurich, Department of Forensic Psychiatry, Zurich, Switzerland.
  • Steffen Lau
    University Hospital of Psychiatry Zurich, Department of Forensic Psychiatry, Zurich, Switzerland.