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Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study

BACKGROUND: A better understanding of the factors and their correlation with clinical first-line nurses’ sleep, fatigue and mental workload is of great significance to personnel scheduling strategies and rapid responses to anti-pandemic tasks in the post-COVID-19 pandemic era. OBJECTIVE: This multic...

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Autores principales: Liu, Yan, Xian, Ji Shu, Wang, Rui, Ma, Kang, Li, Fei, Wang, Fei Long, Yang, Xue, Mu, Ning, Xu, Kai, Quan, Yu Lian, Wang, Shi, Lai, Ying, Yang, Chuan Yan, Li, Teng, Zhang, Yanchun, Tan, Binbin, Feng, Hua, Chen, Tu Nan, Wang, Li Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452657/
https://www.ncbi.nlm.nih.gov/pubmed/36090368
http://dx.doi.org/10.3389/fpsyt.2022.963419
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author Liu, Yan
Xian, Ji Shu
Wang, Rui
Ma, Kang
Li, Fei
Wang, Fei Long
Yang, Xue
Mu, Ning
Xu, Kai
Quan, Yu Lian
Wang, Shi
Lai, Ying
Yang, Chuan Yan
Li, Teng
Zhang, Yanchun
Tan, Binbin
Feng, Hua
Chen, Tu Nan
Wang, Li Hua
author_facet Liu, Yan
Xian, Ji Shu
Wang, Rui
Ma, Kang
Li, Fei
Wang, Fei Long
Yang, Xue
Mu, Ning
Xu, Kai
Quan, Yu Lian
Wang, Shi
Lai, Ying
Yang, Chuan Yan
Li, Teng
Zhang, Yanchun
Tan, Binbin
Feng, Hua
Chen, Tu Nan
Wang, Li Hua
author_sort Liu, Yan
collection PubMed
description BACKGROUND: A better understanding of the factors and their correlation with clinical first-line nurses’ sleep, fatigue and mental workload is of great significance to personnel scheduling strategies and rapid responses to anti-pandemic tasks in the post-COVID-19 pandemic era. OBJECTIVE: This multicenter and cross-sectional study aimed to investigate the nurses’ sleep, fatigue and mental workload and contributing factors to each, and to determine the correlation among them. METHODS: A total of 1,004 eligible nurses (46 males, 958 females) from three tertiary hospitals participated in this cluster sampling survey. The Questionnaire Star online tool was used to collect the sociodemographic and study target data: Sleep quality, fatigue, and mental workload. Multi-statistical methods were used for data analysis using SPSS 25.0 and Amos 21.0. RESULTS: The average sleep quality score was 10.545 ± 3.399 (insomnia prevalence: 80.2%); the average fatigue score was 55.81 ± 10.405 (fatigue prevalence: 100%); and the weighted mental workload score was 56.772 ± 17.26. Poor sleep was associated with mental workload (r = 0.303, P < 0.05) and fatigue (r = 0.727, P < 0.01). Fatigue was associated with mental workload (r = 0.321, P < 0.05). COVID-19 has caused both fatigue and mental workload. As 49% of nurses claimed their mental workload has been severely affected by COVID-19, while it has done slight harm to 68.9% of nurses’ sleep quality. CONCLUSION: In the post-COVID-19 pandemic era, the high prevalence of sleep disorders and fatigue emphasizes the importance of paying enough attention to the mental health of nurses in first-class tertiary hospitals. Efficient nursing strategies should focus on the interaction of sleep, fatigue and mental workload in clinical nurses. In that case, further research on solutions to the phenomenon stated above proves to be of great significance and necessity. CLINICAL TRIAL REGISTRATION: [https://clinicaltrials.gov/], identifier [ChiCTR2100053133].
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spelling pubmed-94526572022-09-09 Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study Liu, Yan Xian, Ji Shu Wang, Rui Ma, Kang Li, Fei Wang, Fei Long Yang, Xue Mu, Ning Xu, Kai Quan, Yu Lian Wang, Shi Lai, Ying Yang, Chuan Yan Li, Teng Zhang, Yanchun Tan, Binbin Feng, Hua Chen, Tu Nan Wang, Li Hua Front Psychiatry Psychiatry BACKGROUND: A better understanding of the factors and their correlation with clinical first-line nurses’ sleep, fatigue and mental workload is of great significance to personnel scheduling strategies and rapid responses to anti-pandemic tasks in the post-COVID-19 pandemic era. OBJECTIVE: This multicenter and cross-sectional study aimed to investigate the nurses’ sleep, fatigue and mental workload and contributing factors to each, and to determine the correlation among them. METHODS: A total of 1,004 eligible nurses (46 males, 958 females) from three tertiary hospitals participated in this cluster sampling survey. The Questionnaire Star online tool was used to collect the sociodemographic and study target data: Sleep quality, fatigue, and mental workload. Multi-statistical methods were used for data analysis using SPSS 25.0 and Amos 21.0. RESULTS: The average sleep quality score was 10.545 ± 3.399 (insomnia prevalence: 80.2%); the average fatigue score was 55.81 ± 10.405 (fatigue prevalence: 100%); and the weighted mental workload score was 56.772 ± 17.26. Poor sleep was associated with mental workload (r = 0.303, P < 0.05) and fatigue (r = 0.727, P < 0.01). Fatigue was associated with mental workload (r = 0.321, P < 0.05). COVID-19 has caused both fatigue and mental workload. As 49% of nurses claimed their mental workload has been severely affected by COVID-19, while it has done slight harm to 68.9% of nurses’ sleep quality. CONCLUSION: In the post-COVID-19 pandemic era, the high prevalence of sleep disorders and fatigue emphasizes the importance of paying enough attention to the mental health of nurses in first-class tertiary hospitals. Efficient nursing strategies should focus on the interaction of sleep, fatigue and mental workload in clinical nurses. In that case, further research on solutions to the phenomenon stated above proves to be of great significance and necessity. CLINICAL TRIAL REGISTRATION: [https://clinicaltrials.gov/], identifier [ChiCTR2100053133]. Frontiers Media S.A. 2022-08-25 /pmc/articles/PMC9452657/ /pubmed/36090368 http://dx.doi.org/10.3389/fpsyt.2022.963419 Text en Copyright © 2022 Liu, Xian, Wang, Ma, Li, Wang, Yang, Mu, Xu, Quan, Wang, Lai, Yang, Li, Zhang, Tan, Feng, Chen and Wang. 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 Psychiatry
Liu, Yan
Xian, Ji Shu
Wang, Rui
Ma, Kang
Li, Fei
Wang, Fei Long
Yang, Xue
Mu, Ning
Xu, Kai
Quan, Yu Lian
Wang, Shi
Lai, Ying
Yang, Chuan Yan
Li, Teng
Zhang, Yanchun
Tan, Binbin
Feng, Hua
Chen, Tu Nan
Wang, Li Hua
Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title_full Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title_fullStr Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title_full_unstemmed Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title_short Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study
title_sort factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of covid-19: a multi-center cross-sectional study
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452657/
https://www.ncbi.nlm.nih.gov/pubmed/36090368
http://dx.doi.org/10.3389/fpsyt.2022.963419
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