Cross-national exploration of nurse burnout: Predictors and consequences in eight countries

The recent decades of rapid change in the health care systems make nursing practice both rewarding and challenging. On one hand, advancements in science and technology make it possible to provide better care to patients, on the other hand rapid restructuring, significant budget cuts, and increasing job demands create complex working environments for hospital nursing staff which increases their risk of negative outcomes such as nurse burnout. Nurse burnout is an important phenomenon to investigate particularly in times of severe nurse shortage because it has been significantly linked to nurses' intention to leave jobs and to the quality of patient care. This study utilized a comprehensive approach to explore nurse burnout in eight countries. First, the study addressed burnout measurement issues in cross-national research and demonstrated that the Maslach Burnout Inventory (MBI) is a valid research tool to measure burnout cross-nationally. MBI has a three-factor structure and most its items loaded on the same factors across countries. Second, the study measured burnout in countries and demonstrated the organizational characteristics leading to nurse burnout. The levels of burnout vary in countries indicating high burnout among nurses in Japan and the United States and lower burnout in Germany, Russia, and Armenia. Despite the variable levels of burnout across all countries, nurse staffing and resource adequacy, support from nurse managers, and collegial relations in the work setting were significant predictors of burnout. Finally, the study investigated the consequences of burnout on patient care and nurse outcomes. The study found that controlling for nurse and job characteristics, burnout, particularly the emotional exhaustion dimension, significantly increases the risk of poor quality of care, job dissatisfaction, and nurses' intention to leave their jobs. Conclusions are drawn that controlled for country specific differences there are similar predictors and conseq