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Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study
BACKGROUND: Schizophrenia patients have increased risks of adverse outcomes, including violent crime, aggressiveness, and suicide. However, studies of different adverse outcomes in schizophrenia patients are limited and the influencing factors for these outcomes need clarification by appropriate mod...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284775/ https://www.ncbi.nlm.nih.gov/pubmed/35840915 http://dx.doi.org/10.1186/s12888-022-04070-3 |
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author | Chen, Lichang Tan, Wenyan Lin, Xiao Lin, Haicheng Xi, Junyan Zhang, Yuqin Jia, Fujun Hao, Yuantao |
author_facet | Chen, Lichang Tan, Wenyan Lin, Xiao Lin, Haicheng Xi, Junyan Zhang, Yuqin Jia, Fujun Hao, Yuantao |
author_sort | Chen, Lichang |
collection | PubMed |
description | BACKGROUND: Schizophrenia patients have increased risks of adverse outcomes, including violent crime, aggressiveness, and suicide. However, studies of different adverse outcomes in schizophrenia patients are limited and the influencing factors for these outcomes need clarification by appropriate models. This study aimed to identify influencing factors of these adverse outcomes by examining and comparing different count regression models. METHODS: This study included schizophrenia patients who had at least one follow-up record in the Guangdong Mental Health Center Network Medical System during 2020. Three types of adverse outcomes were included: a) aggressiveness with police dispatch or violent crime, b) aggressiveness without police dispatch, and c) self-harm or suicide attempts. The incidence density of these adverse outcomes was investigated using the Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models, accordingly. The best model was chosen based on goodness-of-fit tests. We further analyzed associations between the number of occurrences of adverse outcomes and sociodemographic, clinical factors with the best model. RESULTS: A total of 130,474 schizophrenia patients were enrolled. Adverse outcomes rates were reported to be less than 1% for schizophrenia patients in 2020, in Guangdong. The NB model performed the best in terms of goodness-of-fit and interpretation when fitting for the number of occurrences of aggressiveness without police dispatch, whereas the ZINB models performed better for the other two outcomes. Age, sex, and history of adverse outcomes were influencing factors shared across these adverse outcomes. Higher education and employment were protective factors for aggressive and violent behaviors. Disease onset aged ≥ 18 years served as a significant risk factor for aggressiveness without police dispatch, and self-harm or suicide attempts. Family history of mental diseases was a risk factor for self-harm or suicide attempts individually. CONCLUSIONS: NB and ZINB models were selected for fitting the number of occurrences of adverse outcomes among schizophrenia patients in our studies. Influencing factors for the incidence density of adverse outcomes included both those shared across different types and those individual to specific types. Therefore, comprehensive and customized tools in risk assessment and intervention might be necessary. |
format | Online Article Text |
id | pubmed-9284775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92847752022-07-16 Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study Chen, Lichang Tan, Wenyan Lin, Xiao Lin, Haicheng Xi, Junyan Zhang, Yuqin Jia, Fujun Hao, Yuantao BMC Psychiatry Research BACKGROUND: Schizophrenia patients have increased risks of adverse outcomes, including violent crime, aggressiveness, and suicide. However, studies of different adverse outcomes in schizophrenia patients are limited and the influencing factors for these outcomes need clarification by appropriate models. This study aimed to identify influencing factors of these adverse outcomes by examining and comparing different count regression models. METHODS: This study included schizophrenia patients who had at least one follow-up record in the Guangdong Mental Health Center Network Medical System during 2020. Three types of adverse outcomes were included: a) aggressiveness with police dispatch or violent crime, b) aggressiveness without police dispatch, and c) self-harm or suicide attempts. The incidence density of these adverse outcomes was investigated using the Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models, accordingly. The best model was chosen based on goodness-of-fit tests. We further analyzed associations between the number of occurrences of adverse outcomes and sociodemographic, clinical factors with the best model. RESULTS: A total of 130,474 schizophrenia patients were enrolled. Adverse outcomes rates were reported to be less than 1% for schizophrenia patients in 2020, in Guangdong. The NB model performed the best in terms of goodness-of-fit and interpretation when fitting for the number of occurrences of aggressiveness without police dispatch, whereas the ZINB models performed better for the other two outcomes. Age, sex, and history of adverse outcomes were influencing factors shared across these adverse outcomes. Higher education and employment were protective factors for aggressive and violent behaviors. Disease onset aged ≥ 18 years served as a significant risk factor for aggressiveness without police dispatch, and self-harm or suicide attempts. Family history of mental diseases was a risk factor for self-harm or suicide attempts individually. CONCLUSIONS: NB and ZINB models were selected for fitting the number of occurrences of adverse outcomes among schizophrenia patients in our studies. Influencing factors for the incidence density of adverse outcomes included both those shared across different types and those individual to specific types. Therefore, comprehensive and customized tools in risk assessment and intervention might be necessary. BioMed Central 2022-07-15 /pmc/articles/PMC9284775/ /pubmed/35840915 http://dx.doi.org/10.1186/s12888-022-04070-3 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 Chen, Lichang Tan, Wenyan Lin, Xiao Lin, Haicheng Xi, Junyan Zhang, Yuqin Jia, Fujun Hao, Yuantao Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title | Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title_full | Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title_fullStr | Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title_full_unstemmed | Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title_short | Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
title_sort | influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284775/ https://www.ncbi.nlm.nih.gov/pubmed/35840915 http://dx.doi.org/10.1186/s12888-022-04070-3 |
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