| Mi-Jin Park | 1 Article |
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. Citations Citations to this article as recorded by
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