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Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne
BACKGROUND: We aimed to identify differences in predictors of involuntary psychiatric hospitalisation depending on whether the inpatient stay was involuntary right from the beginning since admission or changed from voluntary to involuntary in the course of in-patient treatment. METHODS: We conducted...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284734/ https://www.ncbi.nlm.nih.gov/pubmed/35836146 http://dx.doi.org/10.1186/s12888-022-04107-7 |
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author | Peters, Sönke Johann Schmitz-Buhl, Mario Karasch, Olaf Zielasek, Jürgen Gouzoulis-Mayfrank, Euphrosyne |
author_facet | Peters, Sönke Johann Schmitz-Buhl, Mario Karasch, Olaf Zielasek, Jürgen Gouzoulis-Mayfrank, Euphrosyne |
author_sort | Peters, Sönke Johann |
collection | PubMed |
description | BACKGROUND: We aimed to identify differences in predictors of involuntary psychiatric hospitalisation depending on whether the inpatient stay was involuntary right from the beginning since admission or changed from voluntary to involuntary in the course of in-patient treatment. METHODS: We conducted an analysis of 1,773 mental health records of all cases treated under the Mental Health Act in the city of Cologne in the year 2011. 79.4% cases were admitted involuntarily and 20.6% were initially admitted on their own will and were detained later during the course of in-patient stay. We compared the clinical, sociodemographic, socioeconomic and environmental socioeconomic data (ESED) of the two groups. Finally, we employed two different machine learning decision-tree algorithms, Chi-squared Automatic Interaction Detection (CHAID) and Random Forest. RESULTS: Most of the investigated variables did not differ and those with significant differences showed consistently low effect sizes. In the CHAID analysis, the first node split was determined by the hospital the patient was treated at. The diagnosis of a psychotic disorder, an affective disorder, age, and previous outpatient treatment as well as the purchasing power per 100 inhabitants in the living area of the patients also played a role in the model. In the Random Forest, age and the treating hospital had the highest impact on the accuracy and decrease in Gini of the model. However, both models achieved a poor balanced accuracy. Overall, the decision-tree analyses did not yield a solid, causally interpretable prediction model. CONCLUSION: Cases with detention at admission and cases with detention in the course of in-patient treatment were largely similar in respect to the investigated variables. Our findings give no indication for possible differential preventive measures against coercion for the two subgroups. There is no need or rationale to differentiate the two subgroups in future studies. |
format | Online Article Text |
id | pubmed-9284734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92847342022-07-16 Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne Peters, Sönke Johann Schmitz-Buhl, Mario Karasch, Olaf Zielasek, Jürgen Gouzoulis-Mayfrank, Euphrosyne BMC Psychiatry Research BACKGROUND: We aimed to identify differences in predictors of involuntary psychiatric hospitalisation depending on whether the inpatient stay was involuntary right from the beginning since admission or changed from voluntary to involuntary in the course of in-patient treatment. METHODS: We conducted an analysis of 1,773 mental health records of all cases treated under the Mental Health Act in the city of Cologne in the year 2011. 79.4% cases were admitted involuntarily and 20.6% were initially admitted on their own will and were detained later during the course of in-patient stay. We compared the clinical, sociodemographic, socioeconomic and environmental socioeconomic data (ESED) of the two groups. Finally, we employed two different machine learning decision-tree algorithms, Chi-squared Automatic Interaction Detection (CHAID) and Random Forest. RESULTS: Most of the investigated variables did not differ and those with significant differences showed consistently low effect sizes. In the CHAID analysis, the first node split was determined by the hospital the patient was treated at. The diagnosis of a psychotic disorder, an affective disorder, age, and previous outpatient treatment as well as the purchasing power per 100 inhabitants in the living area of the patients also played a role in the model. In the Random Forest, age and the treating hospital had the highest impact on the accuracy and decrease in Gini of the model. However, both models achieved a poor balanced accuracy. Overall, the decision-tree analyses did not yield a solid, causally interpretable prediction model. CONCLUSION: Cases with detention at admission and cases with detention in the course of in-patient treatment were largely similar in respect to the investigated variables. Our findings give no indication for possible differential preventive measures against coercion for the two subgroups. There is no need or rationale to differentiate the two subgroups in future studies. BioMed Central 2022-07-14 /pmc/articles/PMC9284734/ /pubmed/35836146 http://dx.doi.org/10.1186/s12888-022-04107-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Peters, Sönke Johann Schmitz-Buhl, Mario Karasch, Olaf Zielasek, Jürgen Gouzoulis-Mayfrank, Euphrosyne Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title | Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title_full | Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title_fullStr | Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title_full_unstemmed | Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title_short | Determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of Cologne |
title_sort | determinants of compulsory hospitalisation at admission and in the course of inpatient treatment in people with mental disorders—a retrospective analysis of health records of the four psychiatric hospitals of the city of cologne |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284734/ https://www.ncbi.nlm.nih.gov/pubmed/35836146 http://dx.doi.org/10.1186/s12888-022-04107-7 |
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