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Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

BACKGROUND: Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk. METH...

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Autores principales: Wu, Jing, Li, Husheng, Geng, Zhaohui, Wang, Yanmei, Wang, Xian, Zhang, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8532096/
https://www.ncbi.nlm.nih.gov/pubmed/34686177
http://dx.doi.org/10.1186/s12912-021-00726-9
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author Wu, Jing
Li, Husheng
Geng, Zhaohui
Wang, Yanmei
Wang, Xian
Zhang, Jie
author_facet Wu, Jing
Li, Husheng
Geng, Zhaohui
Wang, Yanmei
Wang, Xian
Zhang, Jie
author_sort Wu, Jing
collection PubMed
description BACKGROUND: Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk. METHODS: A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses’ mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups. RESULTS: Three latent classes were identified based on the responses to mental workload assessment: Class 1 – low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 – medium workload perception & medium self-evaluation group (n = 455, 34.0%); and Class 3 – high workload perception & low self-evaluation group (n = 841, `62.9%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels. CONCLUSIONS: The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies.
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spelling pubmed-85320962021-10-22 Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis Wu, Jing Li, Husheng Geng, Zhaohui Wang, Yanmei Wang, Xian Zhang, Jie BMC Nurs Research Article BACKGROUND: Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk. METHODS: A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses’ mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups. RESULTS: Three latent classes were identified based on the responses to mental workload assessment: Class 1 – low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 – medium workload perception & medium self-evaluation group (n = 455, 34.0%); and Class 3 – high workload perception & low self-evaluation group (n = 841, `62.9%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels. CONCLUSIONS: The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies. BioMed Central 2021-10-22 /pmc/articles/PMC8532096/ /pubmed/34686177 http://dx.doi.org/10.1186/s12912-021-00726-9 Text en © The Author(s) 2021 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 Article
Wu, Jing
Li, Husheng
Geng, Zhaohui
Wang, Yanmei
Wang, Xian
Zhang, Jie
Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title_full Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title_fullStr Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title_full_unstemmed Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title_short Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis
title_sort subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (covid-19) outbreak: a latent class analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8532096/
https://www.ncbi.nlm.nih.gov/pubmed/34686177
http://dx.doi.org/10.1186/s12912-021-00726-9
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