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Stressors, emotions, and social support systems among respiratory nurses during the Omicron outbreak in China: a qualitative study.

Authors :
Yu, Wenzhen
Zhang, Ying
Xianyu, Yunyan
Cheng, Dan
Source :
BMC Nursing. 3/21/2024, Vol. 23 Issue 1, p1-11. 11p.
Publication Year :
2024

Abstract

Background: Respiratory nurses faced tremendous challenges when the Omicron variant spread rapidly in China from late 2022 to early 2023. An in-depth understanding of respiratory nurses' experiences during challenging times can help to develop better management and support strategies. The present study was conducted to explore and describe the work experiences of nurses working in the Department of Pulmonary and Critical Care Medicine (PCCM) during the Omicron outbreak in China. Methods: This study utilized a descriptive phenomenological method. Between January 9 and 22, 2023, semistructured and individual in-depth interviews were conducted with 11 respiratory nurses at a tertiary hospital in Wuhan, Hubei Province. A purposive sampling method was used to select the participants, and the sample size was determined based on data saturation. The data analysis was carried out using Colaizzi's method. Results: Three themes with ten subthemes emerged: (a) multiple stressors (intense workload due to high variability in COVID patients; worry about not having enough ability and energy to care for critically ill patients; fighting for anxious clients, colleagues, and selves); (b) mixed emotions (feelings of loss and responsibility; feelings of frustration and achievement; feelings of nervousness and security); and (c) a perceived social support system (team cohesion; family support; head nurse leadership; and the impact of social media). Conclusion: Nursing managers should be attentive to frontline nurses' needs and occupational stress during novel coronavirus disease 2019 (COVID-19) outbreaks. Management should strengthen psychological and social support systems, optimize nursing leadership styles, and proactively consider the application of artificial intelligence (AI) technologies and products in clinical care to improve the ability of nurses to effectively respond to future public health crises. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14726955
Volume :
23
Issue :
1
Database :
Academic Search Index
Journal :
BMC Nursing
Publication Type :
Academic Journal
Accession number :
176220073
Full Text :
https://doi.org/10.1186/s12912-024-01856-6