Identification of risk factors for involuntary psychiatric hospitalization: using environmental socioeconomic data and methods of machine learning to improve prediction

Identification of risk factors for involuntary psychiatric hospitalization: using environmental socioeconomic data and methods of machine learning to improve prediction

Abstract Background The purpose of this study was to identify factors associated with a high risk of involuntary psychiatric in-patient hospitalization both on the individual level and on the level of mental health services and the socioeconomic environment that patients live in. Methods The present...

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Bibliographic Details
Main Authors: O. Karasch, M. Schmitz-Buhl, R. Mennicken, J. Zielasek, E. Gouzoulis-Mayfrank
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Psychiatry
Subjects:
Mental health act
Involuntary admission
Machine learning
Decision-tree analysis
Environmental socioeconomic data
Urbanization
Online Access:http://link.springer.com/article/10.1186/s12888-020-02803-w

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http://link.springer.com/article/10.1186/s12888-020-02803-w

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