TY - JOUR AU - Kirchebner, Johannes AU - Günther, Moritz Philipp AU - Sonnweber, Martina AU - King, Alice AU - Lau, Steffen PY - 2020 DA - 2020/05/06 TI - Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach JO - BMC Psychiatry SP - 201 VL - 20 IS - 1 AB - 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. SN - 1471-244X UR - https://doi.org/10.1186/s12888-020-02612-1 DO - 10.1186/s12888-020-02612-1 ID - Kirchebner2020 ER -