Chen Chen, Li Fengzhan, Liu Chang, Li Kuiliang, Yang Qun, Ren Lei
Military Medical Psychology School, Air Force Medical University, Xi'an, China.
Brain Park, Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Clayton, VIC, Australia.
Front Public Health. 2022 Aug 10;10:919692. doi: 10.3389/fpubh.2022.919692. eCollection 2022.
Although poor mental well-being (MW) has been documented among individuals experiencing burnout during the coronavirus-19 (COVID-19) pandemic, little is known about the complex interrelationship between different components of MW and burnout. This study investigates this relationship among medical staff during the COVID-19 pandemic through network analysis.
A total of 420 medical staff were recruited for this study. Components of MW were measured by the 14-item Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and components of burnout were measured by a 15-item Maslach Burnout Inventory-General Survey (MBI-GS) Questionnaire. Network structure was constructed network analysis. Bridge variables were identified the bridge centrality index.
The edges across two communities (i.e., MW community and burnout community) are almost negative, such as edge MW2 ("Useful") - B14 ("Worthwhile") and edge MW1 ("Optimistic about future") - B13 ("Happy"). The edges within each community are nearly positive. In the MW community, components MW1 ("Optimistic about future") and MW6 ("Dealing with problems") have the lowest bridge centrality. And in the community of burnout, components B13 ("Happy") and B14 ("Worthwhile") have the lowest bridge expected influence.
We present the first study to apply the network approach to model the potential pathways between distinct components of MW and burnout. Our findings suggest that promoting optimistic attitudes and problem-solving skills may help reduce burnout among medical staff during the pandemic.
尽管在冠状病毒病（COVID-19）大流行期间，经历职业倦怠的个体存在心理健康状况不佳的情况，但对于心理健康不同组成部分与职业倦怠之间复杂的相互关系，我们知之甚少。本研究通过网络分析调查COVID-19大流行期间医护人员中的这种关系。
本研究共招募了420名医护人员。心理健康的组成部分通过14项沃里克-爱丁堡心理健康量表（WEMWBS）进行测量，职业倦怠的组成部分通过15项马氏职业倦怠量表通用版（MBI-GS）问卷进行测量。通过网络分析构建网络结构。利用桥接中心性指数识别桥接变量。
两个社区（即心理健康社区和职业倦怠社区）之间的边几乎都是负的，例如边MW2（“有用”）-B14（“有价值”）和边MW1（“对未来乐观”）-B13（“快乐”）。每个社区内部的边几乎都是正的。在心理健康社区中，组成部分MW1（“对未来乐观”）和MW6（“处理问题”）的桥接中心性最低。而在职业倦怠社区中，组成部分B13（“快乐”）和B14（“有价值”）的桥接预期影响最低。
我们首次进行研究，应用网络方法对心理健康和职业倦怠不同组成部分之间的潜在路径进行建模。我们的研究结果表明，在大流行期间，培养乐观态度和解决问题的能力可能有助于降低医护人员的职业倦怠。
