Analysis of the mediating effect of occupational burnout on the relationship between emotional labor and turnover intention among obstetric nurses - Lv, Xueling; Ding, Zhifang; Wang, Tingting; Zhang, Meixue (Frontiers in Public Health, 2025)
ObjectiveThis study aimed to examine the mediating role of occupational burnout in the relationship between emotional labor and turnover intention among obstetric nurses in China.MethodsA cross-sectional survey was conducted among 205 obstetric nurses from six tertiary hospitals in Fuyang City, China. Validated scales were used to assess emotional labor (Emotional Labor Scale, ELS), occupational burnout (Maslach Burnout Inventory, MBI), and turnover intention (Turnover Intention Scale, TIS). Data were analyzed using Pearson correlation, univariate analysis, multiple linear regression, and structural equation modeling (SEM) with Bootstrap mediation analysis.ResultsSignificant associations were found between nurses' emotional labor and occupational burnout (r = 0.292, P < 0.01), occupational burnout and turnover intention (r = 0.152, P < 0.01), and emotional labor and turnover intention (r = 0.291, P < 0.01). The SEM demonstrated good fit indices (χ2/df = 2.032, RMSEA = 0.071, CFI = 0.957). Occupational burnout substantially mediated the relationship, accounting for 54.2% of the total effect of emotional labor on turnover intention (indirect effect: 0.110, 95% CI [0.069, 0.169], P < 0.001). Additionally, monthly night shifts (β = 0.35, P < 0.001) and professional title (β = 0.28, P < 0.01) emerged as significant predictors of turnover intention.ConclusionOccupational burnout serves as a critical mediator between emotional labor and turnover intention among obstetric nurses. These findings highlight the urgent need for healthcare organizations to implement targeted interventions, including workload optimization, adaptive emotional labor training, and comprehensive psychological support programs. Such strategies are essential for reducing nurse turnover, ensuring adequate staffing levels, and ultimately improving maternal and neonatal care quality in healthcare systems.