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Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis
BACKGROUND: Nurses during COVID-19 who face significant stress and high infection risk are prone to fatigue, affecting their health and quality of patient care. A cross- sectional study of 270 nurses who went to epidemic area to support anti-epidemic was carried out via online survey during the COVI...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10470039/ https://www.ncbi.nlm.nih.gov/pubmed/37663828 http://dx.doi.org/10.3389/fpubh.2023.1184702 |
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author | Zhang, Huanyu Liu, Zhixin Liu, Junping Feng, Yajie Zou, Dandan Zhao, Juan Wang, Chen Wang, Nan Liu, Xinru Wu, Lin Liu, Zhaoyue Liang, Libo Liu, Jie |
author_facet | Zhang, Huanyu Liu, Zhixin Liu, Junping Feng, Yajie Zou, Dandan Zhao, Juan Wang, Chen Wang, Nan Liu, Xinru Wu, Lin Liu, Zhaoyue Liang, Libo Liu, Jie |
author_sort | Zhang, Huanyu |
collection | PubMed |
description | BACKGROUND: Nurses during COVID-19 who face significant stress and high infection risk are prone to fatigue, affecting their health and quality of patient care. A cross- sectional study of 270 nurses who went to epidemic area to support anti-epidemic was carried out via online survey during the COVID-19 pandemic on November 2021. METHODS: A web-based cross-sectional survey of 270 nurses in China who traveled to Heihe City in Heilongjiang Province to combat the novel coronavirus epidemic. The researchers collected information on sociodemographic variables, anxiety, transition shock, professionalism, collaboration, hours of work per day, and fatigue. Regression and fuzzy-set Quality Comparative Analysis (fsQCA) evaluated the factors’ impact on the nurses’ fatigue. RESULTS: Regression analysis showed that the psychological variables significant for fatigue, transition shock (β = 0.687, p < 0.001) and anxiety (β = 0.757, p < 0.001) were positively associated with fatigue, professionalism (β = −0.216, p < 0.001) was negatively associated with fatigue, and among the work-related variables, cooperation (β = −0.262, p < 0.001) was negatively related to fatigue. FsQCA analysis showed that combined effects of work hours, anxiety, and nurses’ educational status caused most of the fatigue (raw coverage = 0.482, consistency = 0.896). CONCLUSION: This study provides two main findings, the one is the greater transition shock experienced during COVID-19 in a new environment, low levels of professionalism, anxiety, and poor nursing teamwork situations lead anti-epidemic nurses to increased fatigue. Second, the fsQCA results showed that anxiety is sufficient for fatigue and that nurses’ educational status, daily working hours, and anxiety are the most effective combination of factors. |
format | Online Article Text |
id | pubmed-10470039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104700392023-09-01 Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis Zhang, Huanyu Liu, Zhixin Liu, Junping Feng, Yajie Zou, Dandan Zhao, Juan Wang, Chen Wang, Nan Liu, Xinru Wu, Lin Liu, Zhaoyue Liang, Libo Liu, Jie Front Public Health Public Health BACKGROUND: Nurses during COVID-19 who face significant stress and high infection risk are prone to fatigue, affecting their health and quality of patient care. A cross- sectional study of 270 nurses who went to epidemic area to support anti-epidemic was carried out via online survey during the COVID-19 pandemic on November 2021. METHODS: A web-based cross-sectional survey of 270 nurses in China who traveled to Heihe City in Heilongjiang Province to combat the novel coronavirus epidemic. The researchers collected information on sociodemographic variables, anxiety, transition shock, professionalism, collaboration, hours of work per day, and fatigue. Regression and fuzzy-set Quality Comparative Analysis (fsQCA) evaluated the factors’ impact on the nurses’ fatigue. RESULTS: Regression analysis showed that the psychological variables significant for fatigue, transition shock (β = 0.687, p < 0.001) and anxiety (β = 0.757, p < 0.001) were positively associated with fatigue, professionalism (β = −0.216, p < 0.001) was negatively associated with fatigue, and among the work-related variables, cooperation (β = −0.262, p < 0.001) was negatively related to fatigue. FsQCA analysis showed that combined effects of work hours, anxiety, and nurses’ educational status caused most of the fatigue (raw coverage = 0.482, consistency = 0.896). CONCLUSION: This study provides two main findings, the one is the greater transition shock experienced during COVID-19 in a new environment, low levels of professionalism, anxiety, and poor nursing teamwork situations lead anti-epidemic nurses to increased fatigue. Second, the fsQCA results showed that anxiety is sufficient for fatigue and that nurses’ educational status, daily working hours, and anxiety are the most effective combination of factors. Frontiers Media S.A. 2023-08-17 /pmc/articles/PMC10470039/ /pubmed/37663828 http://dx.doi.org/10.3389/fpubh.2023.1184702 Text en Copyright © 2023 Zhang, Liu, Liu, Feng, Zou, Zhao, Wang, Wang, Liu, Wu, Liu, Liang and Liu. 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 | Public Health Zhang, Huanyu Liu, Zhixin Liu, Junping Feng, Yajie Zou, Dandan Zhao, Juan Wang, Chen Wang, Nan Liu, Xinru Wu, Lin Liu, Zhaoyue Liang, Libo Liu, Jie Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title | Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title_full | Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title_fullStr | Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title_full_unstemmed | Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title_short | Factors influencing nurse fatigue during COVID-19: regression vs. fuzzy-set qualitative comparative analysis |
title_sort | factors influencing nurse fatigue during covid-19: regression vs. fuzzy-set qualitative comparative analysis |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10470039/ https://www.ncbi.nlm.nih.gov/pubmed/37663828 http://dx.doi.org/10.3389/fpubh.2023.1184702 |
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