Predicting New Graduate Nurses' Retention during Transition Using Decision Tree Methods: A Longitudinal Study

Area of Science:

• Nursing
• Healthcare Management
• Workforce Retention

Background:

• New nurse retention is a significant challenge in healthcare.
• Longitudinal studies on factors influencing new graduate nurse retention are scarce.
• Understanding the career transition of new nurses is vital for the profession's future.

Purpose of the Study:

• To identify factors influencing new graduate nurse retention.
• To develop a longitudinal prediction model for new graduate nurse retention.

Main Methods:

• Secondary data analysis of the New Nurse e-Cohort Study (2020, 2022).
• Classification and Regression Tree (CART) analysis to build a predictive model.
• Categorization of participants into retention or turnover groups.

Main Results:

• The study included 586 participants; 79% were retained.
• Younger age, higher readiness for practice, lower transition shock, and better person-environment fit predicted retention.
• The CART model achieved 79.7% predictive accuracy.

Conclusions:

• Collaborative efforts between nursing educators and hospital managers are essential.
• Strategies should focus on preparing students for practice, supporting socialization, and fostering professional values.
• Transforming educational strategies and management policies can enhance new graduate nurse retention.