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A comprehensive model for predicting burnout in Korean nurses


  • Haejung Lee PhD RN,

  • Rhayun Song PhD RN,

  • Young Suk Cho MA RN,

  • Gil Za Lee PhD RN,

  • Barbara Daly PhD RN

Haejung Lee, Department of Nursing, College of Medicine, Pusan National University, 10 Ami 1ga, Suh-Gu, Pusan 602-739, Korea.


Background.  Although burnout among nurses has been studied in a great deal, this work has not included Korean nurses. Furthermore, the role of personal resources such as empathy and empowerment in predicting the variance in burnout has never been examined.

Aim.  The purpose of this study was to understand the phenomenon of burnout among Korean nurses. A comprehensive model of burnout was examined to identify significant predictors among individual characteristics, job stress and personal resource, with the intention of providing a basis for individual and organizational interventions to reduce levels of burnout experienced by Korean nurses.

Methods.  A cross-sectional correlational design was used. A sample of 178 nurses from general hospitals in southern Korea was surveyed from May 1999 to March 2000. The data were collected using paper and pencil self-rating questionnaires and analysed using descriptive statistics, Pearson correlations, and hierarchical multiple regression.

Results.  Korean nurses reported higher levels of burnout than nurses in western countries such as Germany, Canada, the United Kingdom and the United States of America. Nurses who experienced higher job stress, showed lower cognitive empathy and empowerment, and worked in night shifts at tertiary hospitals were more likely to experience burnout.

Conclusions.  Identifying a comprehensive model of burnout among Korean nurses is an essential step to develop effective managerial strategies to reduce the problem. Suggestions to reduce the level of burnout include enhancing nurses’ cognitive empathy and perceived power, providing clear job descriptions and work expectations, and exploring nurses’ shift preferences, especially at tertiary hospitals. In future research we recommend recruiting nurses from broader geographical areas using random selection in order to increase the generalizability of the findings.