The relations between mental well-being and burnout in medical staff during the COVID-19 pandemic: A network analysis

Abstract

Background: 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.

Methods: 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 via network analysis. Bridge variables were identified via the bridge centrality index.

Results: 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.

Conclusion: 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.

Keywords: COVID-19; burnout; medical staff; mental well-being; network analysis.