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Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study

Background: Public health workers are essential to responding to the coronavirus disease 2019 (COVID-19) epidemic, but research on anxiety and stress among public health workers during the epidemic is limited. This study aimed to evaluate related factors affecting mental health among public health w...

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Autores principales: Peng, Xin, Pu, Yangyang, Jiang, Xiaoyong, Zheng, Qingmei, Gu, Jing, Zhou, Huan, Deng, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8702525/
https://www.ncbi.nlm.nih.gov/pubmed/34955975
http://dx.doi.org/10.3389/fpsyg.2021.755347
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author Peng, Xin
Pu, Yangyang
Jiang, Xiaoyong
Zheng, Qingmei
Gu, Jing
Zhou, Huan
Deng, Dan
author_facet Peng, Xin
Pu, Yangyang
Jiang, Xiaoyong
Zheng, Qingmei
Gu, Jing
Zhou, Huan
Deng, Dan
author_sort Peng, Xin
collection PubMed
description Background: Public health workers are essential to responding to the coronavirus disease 2019 (COVID-19) epidemic, but research on anxiety and stress among public health workers during the epidemic is limited. This study aimed to evaluate related factors affecting mental health among public health workers during the epidemic. Methods: Between February 19 and 25, 2020, an online, cross-sectional study was conducted among public health workers in a city in China. Mental health status was assessed using the Chinese versions of the Generalized Anxiety Disorder-7 (GAD-7) scale and Patient Health Questionnaire-9 (PHQ-9), both with a cutoff score of 5. Work-related variables, workloads and sacrifices, and personal perceptions were also assessed. Results: The prevalence of anxiety and depression were 49.2% and 45.7%, respectively, among public health workers. Three risk factors and one protective factor, namely, overcommitment (OR = 1.10∼1.20, p < 0.001), perceived troubles at work (OR = 1.14∼1.18, p < 0.001), perceived tension (OR = 1.11, p < 0.001) and the capability to persist for more than 1 month at the current work intensity (OR = 0.41∼0.42, p < 0.001) were found to be independently associated with anxiety and depression in the multivariable logistic regression analyses after propensity score matching. But the Bayesian networks analysis found that the last three factors directly affect anxiety and depression. Conclusion: Psychological responses to COVID-19 were dramatic among public health workers during the severe phase of the outbreak. To minimize the impact of the epidemic, working conditions should be improved, and easily accessible psychological support services should be implemented.
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spelling pubmed-87025252021-12-25 Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study Peng, Xin Pu, Yangyang Jiang, Xiaoyong Zheng, Qingmei Gu, Jing Zhou, Huan Deng, Dan Front Psychol Psychology Background: Public health workers are essential to responding to the coronavirus disease 2019 (COVID-19) epidemic, but research on anxiety and stress among public health workers during the epidemic is limited. This study aimed to evaluate related factors affecting mental health among public health workers during the epidemic. Methods: Between February 19 and 25, 2020, an online, cross-sectional study was conducted among public health workers in a city in China. Mental health status was assessed using the Chinese versions of the Generalized Anxiety Disorder-7 (GAD-7) scale and Patient Health Questionnaire-9 (PHQ-9), both with a cutoff score of 5. Work-related variables, workloads and sacrifices, and personal perceptions were also assessed. Results: The prevalence of anxiety and depression were 49.2% and 45.7%, respectively, among public health workers. Three risk factors and one protective factor, namely, overcommitment (OR = 1.10∼1.20, p < 0.001), perceived troubles at work (OR = 1.14∼1.18, p < 0.001), perceived tension (OR = 1.11, p < 0.001) and the capability to persist for more than 1 month at the current work intensity (OR = 0.41∼0.42, p < 0.001) were found to be independently associated with anxiety and depression in the multivariable logistic regression analyses after propensity score matching. But the Bayesian networks analysis found that the last three factors directly affect anxiety and depression. Conclusion: Psychological responses to COVID-19 were dramatic among public health workers during the severe phase of the outbreak. To minimize the impact of the epidemic, working conditions should be improved, and easily accessible psychological support services should be implemented. Frontiers Media S.A. 2021-12-10 /pmc/articles/PMC8702525/ /pubmed/34955975 http://dx.doi.org/10.3389/fpsyg.2021.755347 Text en Copyright © 2021 Peng, Pu, Jiang, Zheng, Gu, Zhou and Deng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Peng, Xin
Pu, Yangyang
Jiang, Xiaoyong
Zheng, Qingmei
Gu, Jing
Zhou, Huan
Deng, Dan
Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title_full Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title_fullStr Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title_full_unstemmed Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title_short Analysis of Factors That Influenced the Mental Health Status of Public Health Workers During the COVID-19 Epidemic Based on Bayesian Networks: A Cross-Sectional Study
title_sort analysis of factors that influenced the mental health status of public health workers during the covid-19 epidemic based on bayesian networks: a cross-sectional study
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8702525/
https://www.ncbi.nlm.nih.gov/pubmed/34955975
http://dx.doi.org/10.3389/fpsyg.2021.755347
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