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Impact of Professional Quality of Life on Turnover Intention among General Hospital Nurses: A Comparative Study Using Linear and Nonlinear Analysis Methods

Mi-Jin Park, Il-Ok Kim
J Korean Acad Nurs Adm 2025;31(1):132-141. Published online: January 31, 2025
1Graduate Student, Department of Nursing, Sahmyook University
2Professor, College of Nursing, Sahmyook University
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Purpose
This study examined the impact of professional Quality of life (QoL) on turnover intention among general hospital nurses using linear and nonlinear analytical techniques.
Methods
Data were collected from 159 general hospital nurses and analyzed using SPSS, t-test, ANOVA, Pearson's correlation coefficients, multiple linear regression, and nonlinear machine learning models (Bootstrap Forest and Boosted Tree).
Results
Significant correlations were observed between turnover intention and both compassion satisfaction (r=-.26, p<.001) and burnout (r=.27, p=.001). Compassion satisfaction, burnout, and compassion fatigue were identified as the key variables influencing turnover intention. The explanatory power of multiple linear regression analysis was 6.9%, whereas the nonlinear machine learning models demonstrated an explanatory power of 50.5% for Bootstrap Forest and 45.1% for Boosted Tree.
Conclusion
Continuous investment in human resource management, within nursing organizations, is essential to promote the long-term retention of general hospital nurses. This investment should focus on enhancing compassion satisfaction and reducing burnout and compassion fatigue by fostering a sense of vocation and positive job satisfaction.

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Impact of Professional Quality of Life on Turnover Intention among General Hospital Nurses: A Comparative Study Using Linear and Nonlinear Analysis Methods
J Korean Acad Nurs Adm. 2025;31(1):132-141.   Published online January 31, 2025
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Impact of Professional Quality of Life on Turnover Intention among General Hospital Nurses: A Comparative Study Using Linear and Nonlinear Analysis Methods
J Korean Acad Nurs Adm. 2025;31(1):132-141.   Published online January 31, 2025
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