Impact of Professional Quality of Life on Turnover Intention among General Hospital Nurses: A Comparative Study Using Linear and Nonlinear Analysis Methods
10.11111/jkana.2025.31.1.132
- Author:
Mi-Jin PARK
1
;
Il-Ok KIM
Author Information
1. Graduate Student, Department of Nursing, Sahmyook University
- Publication Type:ORIGINAL ARTICLE
- From:Journal of Korean Academy of Nursing Administration
2025;31(1):132-141
- CountryRepublic of Korea
- Language:English
-
Abstract:
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.
