PDF(Pubmed)
Abstract：
BACKGROUND: The COVID-19 pandemic has significantly increased the risk of burnout among frontline nurses. However, the prevalence of burnout and its associated factors in the post-pandemic era remain unclear. This research aims to investigate burnout prevalence among frontline nurses in the post-pandemic period and pinpoint associated determinants in China.
METHODS: From April to July 2023, a cross-sectional study was carried out across multiple centers, focusing on frontline nurses who had been actively involved in the COVID-19 pandemic. The data collection was done via an online platform. The Maslach Burnout Inventory-Human Services Survey was utilized to evaluate symptoms of burnout. A multivariable logistic regression analysis was used to pinpoint factors associated with burnout.
RESULTS: Of the 2210 frontline nurses who participated, 75.38% scored over the cut-off for burnout. Multivariable logistic regression revealed that factors like being female [odds ratio (OR) = 0.41, 95%CI = 0.29-0.58] and exercising 1-2 times weekly[OR = 0.53, 95%CI = 0.42-0.67] were protective factors against burnout. Conversely, having 10 or more night shifts per month[OR = 1.99, 95%CI = 1.39-2.84], holding a master\'s degree or higher[OR = 2.86, 95% CI = 1.59-5.15], poor health status[OR = 2.43, 95% CI = 1.93-3.08] and [OR = 2.82, 95%CI = 1.80-4.43], under virus infection[OR = 7.12, 95%CI = 2.10-24.17], and elevated work-related stress[OR = 1.53, 95% CI = 1.17-2.00] were all associated with an elevated risk of burnout.
CONCLUSIONS: Our findings indicate that post-pandemic burnout among frontline nurses is influenced by several factors, including gender, monthly night shift frequency, academic qualifications, weekly exercise frequency, health condition, and viral infection history. These insights can inform interventions aimed at safeguarding the mental well-being of frontline nurses in the post-pandemic period.
METHODS: From April to July 2023, a cross-sectional study was carried out across multiple centers, focusing on frontline nurses who had been actively involved in the COVID-19 pandemic. The data collection was done via an online platform. The Maslach Burnout Inventory-Human Services Survey was utilized to evaluate symptoms of burnout. A multivariable logistic regression analysis was used to pinpoint factors associated with burnout.
RESULTS: Of the 2210 frontline nurses who participated, 75.38% scored over the cut-off for burnout. Multivariable logistic regression revealed that factors like being female [odds ratio (OR) = 0.41, 95%CI = 0.29-0.58] and exercising 1-2 times weekly[OR = 0.53, 95%CI = 0.42-0.67] were protective factors against burnout. Conversely, having 10 or more night shifts per month[OR = 1.99, 95%CI = 1.39-2.84], holding a master\'s degree or higher[OR = 2.86, 95% CI = 1.59-5.15], poor health status[OR = 2.43, 95% CI = 1.93-3.08] and [OR = 2.82, 95%CI = 1.80-4.43], under virus infection[OR = 7.12, 95%CI = 2.10-24.17], and elevated work-related stress[OR = 1.53, 95% CI = 1.17-2.00] were all associated with an elevated risk of burnout.
CONCLUSIONS: Our findings indicate that post-pandemic burnout among frontline nurses is influenced by several factors, including gender, monthly night shift frequency, academic qualifications, weekly exercise frequency, health condition, and viral infection history. These insights can inform interventions aimed at safeguarding the mental well-being of frontline nurses in the post-pandemic period.
摘要：
背景：COVID-19大流行显著增加了一线护士职业倦怠的风险。然而,大流行后时期职业倦怠的患病率及其相关因素尚不清楚.本研究旨在调查大流行后一线护士的职业倦怠患病率，并确定中国的相关决定因素。
方法：从2023年4月至7月，跨多个中心进行了横断面研究，重点关注积极参与COVID-19大流行的一线护士。数据收集是通过在线平台完成的。Maslach职业倦怠清单-人类服务调查用于评估职业倦怠的症状。使用多变量逻辑回归分析来确定与职业倦怠相关的因素。
结果：在参加的2210名前线护士中，75.38%的人得分超过了倦怠的界限。多变量logistic回归分析显示，女性[比值比（OR）=0.41，95CI=0.29-0.58]和每周锻炼1-2次[OR=0.53，95CI=0.42-0.67]是预防职业倦怠的保护因素。相反，每月有10个或更多的夜班[OR=1.99，95CI=1.39-2.84]，持有硕士或更高学位[OR=2.86，95%CI=1.59-5.15]，健康状况不佳[OR=2.43，95%CI=1.93-3.08]和[OR=2.82，95CI=1.80-4.43]，在病毒感染下[OR=7.12，95CI=2.10-24.17]，与工作相关的压力升高[OR=1.53,95%CI=1.17-2.00]均与倦怠风险升高相关。
结论：我们的研究结果表明，一线护士的大流行后倦怠受几个因素的影响，包括性别,每月夜班频率，学历,每周锻炼频率,健康状况,和病毒感染史。这些见解可以为旨在保护大流行后一线护士心理健康的干预措施提供信息。
方法：从2023年4月至7月，跨多个中心进行了横断面研究，重点关注积极参与COVID-19大流行的一线护士。数据收集是通过在线平台完成的。Maslach职业倦怠清单-人类服务调查用于评估职业倦怠的症状。使用多变量逻辑回归分析来确定与职业倦怠相关的因素。
结果：在参加的2210名前线护士中，75.38%的人得分超过了倦怠的界限。多变量logistic回归分析显示，女性[比值比（OR）=0.41，95CI=0.29-0.58]和每周锻炼1-2次[OR=0.53，95CI=0.42-0.67]是预防职业倦怠的保护因素。相反，每月有10个或更多的夜班[OR=1.99，95CI=1.39-2.84]，持有硕士或更高学位[OR=2.86，95%CI=1.59-5.15]，健康状况不佳[OR=2.43，95%CI=1.93-3.08]和[OR=2.82，95CI=1.80-4.43]，在病毒感染下[OR=7.12，95CI=2.10-24.17]，与工作相关的压力升高[OR=1.53,95%CI=1.17-2.00]均与倦怠风险升高相关。
结论：我们的研究结果表明，一线护士的大流行后倦怠受几个因素的影响，包括性别,每月夜班频率，学历,每周锻炼频率,健康状况,和病毒感染史。这些见解可以为旨在保护大流行后一线护士心理健康的干预措施提供信息。
