ArticleBMC nursing2025
Predicting turnover intention among newly graduated nurses in South Korea: a decision tree analysis.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe high turnover intention of newly graduated nurses has a multifaceted impact on the healthcare system. Analyzing large datasets using the machine learning methods can more accurately predict influencing factors of turnover intention in this population. This study aims to identify predictors of turnover intention among newly graduated nurses with less than one year of experience in current workplaces, using a decision tree model by analyzing 2016-2020 Graduate Occupational Mobility Survey conducted in South Korea.
methodsThis is a secondary data analysis using a national large dataset. The data of 492 new nursing graduates were included in the analysis. Predictive variables for modeling were grouped into four categories: personal factors, workplace factors, college factors, and physical and mental health factors. Among these, the variables identified through univariate analysis were selected for the final analysis. The Chi-square Automatic Interaction Detection decision tree algorithm was implemented using SPSS Modeler.
results23.6% (N = 116) of participants reported turnover intention. The key predictors of turnover intention included lower levels of job satisfaction concerning personal development and social reputation related to the job, as well as the absence of incentive payments. Factors associated with a high intention for retention included greater satisfaction with personal growth and promotion systems, employment in permanent positions, holding full-time jobs, and experiencing fewer feelings of listlessness.
conclusionThe findings of this study identified key predictors of turnover intention among newly graduated nurses, providing insights for strategies to enhance nurse retention. Promoting opportunities for self-development and career advancement, strengthening institutional reputation, ensuring job security, and supporting mental health may reduce early turnover intentions. Furthermore, implementing educational strategies that prepare nursing students for organizational expectations and enhance clinical competence could contribute to long-term workforce retention in this population. CLINICAL TRIAL NUMBER: Not applicable.
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