Predictors of Nurse Turnover: Model Development and Testing.
10.4040/jkan.2000.30.7.1667
- Author:
Richard REDMAN
1
;
Sung Hyun CHO
;
Shake KETEFIAN
;
Oi Saeng HONG
Author Information
1. Associate Dean for Academic Affairs, University of Colorado Health Sciences Center, School of Nursing, USA.
- Publication Type:Original Article
- Keywords:
Nursing turnover;
Job satisfaction;
Intent to stay
- MeSH:
Administrative Personnel;
Early Intervention (Education);
Humans;
Intention;
Job Satisfaction;
Logistic Models;
Nurse Administrators;
Nursing;
Surveys and Questionnaires
- From:
Journal of Korean Academy of Nursing
2000;30(7):1667-1678
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: The phenomenon of nursing turnover has been explained by organizational commitment, job satisfaction, or intent to stay in previous studies; yet the combined contribution of these factors to nurse turnover has not been examined. OBJECTIVES: The purpose of this study was to develop and test a turnover model which included professionalism, job-related variables, job satisfaction, organizational commitment, and intent to stay. METHOD: A total of 424 registered nurses in a university hospital completed a self-administered questionnaire including Professionalism Scale, Job Diagnostic Survey, Nurse Assessment Survey, and intention to stay. Nurses were classified as to whether they remained in or had left the organization 18 months after the survey. Multiple regression and logistic regression analyses were conducted to test the model. RESULTS: Overall job satisfaction and intent to stay were the most important determinants of nursing turnover. Organizational commitment positively affected intent to stay and indirectly decreased turnover through intent to stay. Satisfaction with coworkers and supervisor were the most important factors in explaining overall job satisfaction. Satisfaction with pay, autonomy, and feedback from job also positively affected overall job satisfaction. CONCLUSION: Using the results of the tested model nurse managers and administrators could predict turnover by monitoring its determinants, and ultimately reduce the turnover rate through early intervention.
