Predicting Turnover Intention Among Newly Graduated Nurses in South Korea: A Decision Tree Analysis

Background. The 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. Methods. This 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. Results. 23.6% (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. Conclusion: Nursing administrators must endeavor to develop effective human resource management strategies that offer opportunities for self-development and career advancement, improve the social reputation of the institution, and ensure job security to mitigate early turnover intentions among newly graduated nurses. Additionally, integrating mental health management is crucial for enhancing workforce stability. In nursing colleges, developing educational strategies to prepare nursing students for organizational expectations and nursing competence will contribute to improving retention within this population. Clinical trial number: not applicable.