Because the health care field is expected to be the fastest growing job field until 2020, an urgent need to focus on nurse retention exists.
The aim of this study was to examine the relationships between predictors of turnover (i.e., personal characteristics, role states, job characteristics, group/leader relations, organizational/environmental perceptions, attitudinal reactions) and turnover cognitions and intentions, as well as actual turnover among nurses, in an effort to determine the strongest predictors of voluntary turnover.
Meta-analysis was used to determine best estimates of the effect of predictors on turnover based on 106 primary studies of employed nurses. Meta-analyzed correlations were subjected to path analysis to establish the structural relationships among the study variables.
Supportive and communicative leadership, network centrality, and organizational commitment are the strongest predictors of voluntary turnover based on meta-analytic correlations. Additional variables that relate to nurse turnover intentions include job strain, role tension, work–family conflict, job control, job complexity, rewards/recognition, and team cohesion.
The findings suggest that some factors, such as salary, are relatively less important in prediction of turnover. Administrators concerned about nurse turnover may more effectively direct resources toward altering certain job characteristics and work conditions in the effort to reduce voluntary turnover among nurses.
Darin Nei, PhD, is Consultant, Hogan Assessment Systems, Tulsa, Oklahoma.
Lori Anderson Snyder, PhD, is Associate Professor, Department of Psychology, University of Oklahoma, Norman. E-mail: firstname.lastname@example.org.
Brett J. Litwiller, MS, PhD(c), is a Graduate Student in the Department of Psychology, University of Oklahoma, Norman.
The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article.