Predictors of Turnover among New Nurses using Multilevel Survival Analysis.
10.4040/jkan.2016.46.5.733
- Author:
Suhee KIM
1
;
Kyongeun LEE
Author Information
1. College of Nursing·Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Korea.
- Publication Type:Original Article
- Keywords:
Nurses;
Employee Turnover;
Survival Analysis;
Multilevel Analysis
- MeSH:
Job Satisfaction;
Multilevel Analysis;
Personnel Turnover;
Survival Analysis*
- From:Journal of Korean Academy of Nursing
2016;46(5):733-743
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: The purpose of this study was to examine factors influencing new graduate nurse turnover. METHODS: This study was carried out as a secondary analysis of data from the 2010 Graduates Occupational Mobility Survey (GOMS). A total of 323 nurses were selected for analysis concerning reasons for turnover. Data were analyzed using descriptive statistics and multilevel survival analysis. RESULTS: About 24.5% of new nurses left their first job within 1 year of starting their jobs. Significant predictors of turnover among new nurse were job status, monthly income, job satisfaction, the number of hospitals in region, and the number of nurses per 100 beds. CONCLUSION: New graduate nurses are vulnerable to turnover. In order to achieve the best health of the nation, policy approaches and further studies regarding reducing new graduate nurse turnover are needed.
