Demographic Factors and Job Characteristics Associated With Burnout in Chinese Female Nurses During Controlled COVID-19 Period: A Cross-Sectional Study

Background: To investigate the prevalence of burnout syndrome among Chinese female nurses during the controlled coronavirus disease 2019 (COVID-19) period and explore its associated socio-demographic factors and job characteristics. Methods: With the multistage, stratified sampling method, a cross-sectional online survey was conducted from September to October 2020 in China. The survey tool included revised Maslach Burnout Inventory (MBI) with 15 items, socio-demographic and job characteristics. Univariate logistic regression analysis and multivariate factor logistic regression analysis were used to identify the risk factors for burnout of female nurses. Results: During controlled COVID-19 period in China, the overall prevalence of burnout symptoms among Chinese female nurses was 60.2% with a breakdown in severity as follows: 451 (39.8 %) mild, 163 (14.4%) moderate, and 68 (6.0%) severe burnout. Little variance was reported for burnout symptoms according to job tenure (Waldχ(2) = 14.828, P < 0.05,odds ratio [OR] <1), monthly salary income (Waldχ(2) = 12.460, P < 0.05, OR <1), and night shift (Waldχ(2) = 3.821, P < 0.05, OR > 1). Conclusion: Burnout symptoms among Chinese female nurses were prevalent and associated with job tenure, monthly salary income, and night shift. Female nurses who were with shorter job tenure, worked at night shifts, and had lower monthly salaries tended to exhibit increasing high-level burnout than their counterparts. This study serves as an implication for administrators and policy-makers to improve the work conditions of nurses for promoting overall healthcare service quality.