ArticleDialogues in health2026
Predicting nurse burnout: A logistic regression approach to workplace and demographic factors.
Article in Dialogues in health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: This study aimed to identify key occupational and demographic factors associated with nurse burnout in a major public hospital in Albania. Methods: A descriptive cross-sectional survey was conducted among nurses in a regional hospital. Nursing management invited all units to participate. Nurses completed the questionnaire voluntarily and anonymously during breaks. The survey included job satisfaction, burnout risk, working conditions, supervisor and colleague support, workload, shift duration, career opportunities, and demographic variables. Cluster analysis was used to categorize nurses, and exploratory factor analysis examined the structure of job satisfaction factors. Results: Data from 345 nurses showed that high workload and long shifts significantly increased burnout risk. Strong supervisor support and greater job satisfaction were associated with reduced burnout. Nurses in rural settings had 1.57 times higher odds of burnout compared to urban nurses. Female nurses had 1.25 times greater odds of burnout than male nurses. Advanced education and better career advancement opportunities were linked to lower burnout levels. Conclusion: Burnout is more prevalent among rural nurses and, to a lesser extent, among female nurses, suggesting the need for context-sensitive and inclusive interventions. Burnout stems from systemic challenges such as excessive workload, insufficient managerial support, and role misalignment. Addressing these issues requires organizational changes including staffing improvements, supportive leadership, and professional development. Future research should apply standardized burnout measures and longitudinal approaches to better understand nurse well-being.
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