Cargando…

Identifying the risk features for occupational stress in medical workers: a cross-sectional study

OBJECTIVE: Occupational stress is considered a worldwide epidemic experienced by a large proportion of the working population. The identification of characteristics that place people at high risk for occupational stress is the basis of managing and intervening in this condition. In this study, we ai...

Descripción completa

Detalles Bibliográficos
Autores principales: Sun, Ruican, Zhang, Cailin, Lv, Keyao, Lan, Yajia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486163/
https://www.ncbi.nlm.nih.gov/pubmed/34599409
http://dx.doi.org/10.1007/s00420-021-01762-3
_version_ 1784577687806803968
author Sun, Ruican
Zhang, Cailin
Lv, Keyao
Lan, Yajia
author_facet Sun, Ruican
Zhang, Cailin
Lv, Keyao
Lan, Yajia
author_sort Sun, Ruican
collection PubMed
description OBJECTIVE: Occupational stress is considered a worldwide epidemic experienced by a large proportion of the working population. The identification of characteristics that place people at high risk for occupational stress is the basis of managing and intervening in this condition. In this study, we aimed to identify and validate the risk features for occupational stress among medical workers using a risk model and nomogram. METHODS: This cross-sectional study included 1988 eligible participants from Henan Province in China. Occupational stress and worker-occupation fit were measured with the Depression, Anxiety and Stress Scales (DASS-21) and Worker-Occupation Fit Inventory (WOFI). The identification of risk features was achieved through constructing multiple logistic regression model, and the risk features were used to develop the risk model and nomogram. Receiver operating characteristic (ROC) curves and calibration plots were generated to assess the effectiveness and calibration of the risk model. RESULTS: Among 1988 participants in our study, there were 42.5% (845/1988) medical workers experienced occupational stress. The risk features for occupational stress included poor work-occupation fit (WOF score < 25, expected risk: 77.3%), nurse population (expected risk: 63.1%), male sex (expected risk: 67.2%), work experience duration of 11–19 years (expected risk: 54.5%), experience of a traumatic event (expected risk: 65.3%) and the lack of a regular exercise habit (expected risk: 60.2%). For medical workers who have these risk features, the expected risk probability of occupational stress would be 90.2%. CONCLUSION: The current data can be used to identify medical workers at risk of developing occupational stress. Identifying risk features for occupational stress and the work-occupation fit can support hierarchical stress management in hospitals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00420-021-01762-3.
format Online
Article
Text
id pubmed-8486163
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-84861632021-10-04 Identifying the risk features for occupational stress in medical workers: a cross-sectional study Sun, Ruican Zhang, Cailin Lv, Keyao Lan, Yajia Int Arch Occup Environ Health Original Article OBJECTIVE: Occupational stress is considered a worldwide epidemic experienced by a large proportion of the working population. The identification of characteristics that place people at high risk for occupational stress is the basis of managing and intervening in this condition. In this study, we aimed to identify and validate the risk features for occupational stress among medical workers using a risk model and nomogram. METHODS: This cross-sectional study included 1988 eligible participants from Henan Province in China. Occupational stress and worker-occupation fit were measured with the Depression, Anxiety and Stress Scales (DASS-21) and Worker-Occupation Fit Inventory (WOFI). The identification of risk features was achieved through constructing multiple logistic regression model, and the risk features were used to develop the risk model and nomogram. Receiver operating characteristic (ROC) curves and calibration plots were generated to assess the effectiveness and calibration of the risk model. RESULTS: Among 1988 participants in our study, there were 42.5% (845/1988) medical workers experienced occupational stress. The risk features for occupational stress included poor work-occupation fit (WOF score < 25, expected risk: 77.3%), nurse population (expected risk: 63.1%), male sex (expected risk: 67.2%), work experience duration of 11–19 years (expected risk: 54.5%), experience of a traumatic event (expected risk: 65.3%) and the lack of a regular exercise habit (expected risk: 60.2%). For medical workers who have these risk features, the expected risk probability of occupational stress would be 90.2%. CONCLUSION: The current data can be used to identify medical workers at risk of developing occupational stress. Identifying risk features for occupational stress and the work-occupation fit can support hierarchical stress management in hospitals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00420-021-01762-3. Springer Berlin Heidelberg 2021-10-01 2022 /pmc/articles/PMC8486163/ /pubmed/34599409 http://dx.doi.org/10.1007/s00420-021-01762-3 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Sun, Ruican
Zhang, Cailin
Lv, Keyao
Lan, Yajia
Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title_full Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title_fullStr Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title_full_unstemmed Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title_short Identifying the risk features for occupational stress in medical workers: a cross-sectional study
title_sort identifying the risk features for occupational stress in medical workers: a cross-sectional study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486163/
https://www.ncbi.nlm.nih.gov/pubmed/34599409
http://dx.doi.org/10.1007/s00420-021-01762-3
work_keys_str_mv AT sunruican identifyingtheriskfeaturesforoccupationalstressinmedicalworkersacrosssectionalstudy
AT zhangcailin identifyingtheriskfeaturesforoccupationalstressinmedicalworkersacrosssectionalstudy
AT lvkeyao identifyingtheriskfeaturesforoccupationalstressinmedicalworkersacrosssectionalstudy
AT lanyajia identifyingtheriskfeaturesforoccupationalstressinmedicalworkersacrosssectionalstudy