Applying Meta-Analytic Structural Equation Modeling to Examine the Relationships Among Work Stress, Job Burnout, and Turnover Intention in Taiwanese Nurses

Background/Objectives: Nursing staff are essential to healthcare delivery, yet Taiwan has experienced a significant rise in nurse turnover in recent years. Retention has thus become a critical concern for healthcare institutions. Identifying the factors influencing nurses’ turnover intentions (TIs) and improving workplace conditions may help to reduce attrition. This study investigates the relationships among TI, work stress (WS), and job burnout (JB), examining variations across healthcare settings and comparing the periods before and after the COVID-19 pandemic. Methods: This study systematically reviews 28 studies published between 2011 and 2025, retrieved from Taiwan’s Master’s and Doctoral Thesis Knowledge Value Added System, Airiti Library, and Google Scholar. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA) guidelines. The data were analyzed using a combined approach of meta-analysis and structural equation modeling. Results: The findings of this study indicate that WS has a statistically significant impact on TI (path coefficient = 0.281, 95% CI: 0.102 to 0.459, p = 0.002). Similarly, JB significantly influences TI (path coefficient = 0.342, 95% CI: 0.163 to 0.520, p < 0.001). WS also has a strong and significant effect on JB (path coefficient = 0.612, 95% CI: 0.485 to 0.739, p < 0.001). These results suggest that WS has a particularly strong effect on JB among nurses working in non-medical center hospitals in Taiwan. Additionally, no significant differences were found in the relationships among TI, WS, and JB before and after the COVID-19 pandemic. Conclusions: Based on the findings of this study, it is recommended that healthcare administrators closely monitor the stress experienced by nursing staff and identify the key factors that lead to WS and JB. Developing targeted policies for different healthcare settings may help to reduce nurses’ intentions to leave their jobs.