title: Beyond the tradition: test of an integrative conceptual model on nurse turnover.
abstract: OBJECTIVE
  This paper aimed to extend research on nurse turnover by developing and testing a theoretical model of turnover intention that includes two emergent key off-the-job constructs, work-family conflict (WFC) and community embeddedness (CE).
  
  
  BACKGROUND
  Nurse turnover is considered one of the most significant issues in health care. There is a considerable body of knowledge that has focused on the study of the on-the-job factors of nurse turnover, showing the important role of job attitudes. Recently, WFC and job embeddedness (JE) have been identified as variables that could help explain levels of nurse turnover.
  
  
  METHODS
  Using structural equation modelling from a cross-sectional survey, the relationships between the variables were explored in a sample of 440 nurses from an Italian public hospital. The questionnaire measures demographic data and psychosocial factors such as job satisfaction, organizational commitment, WFC, CE and turnover intentions.
  
  
  RESULTS
  The findings supported the importance of non-work dimensions in turnover models.
  
  
  CONCLUSIONS
  The results suggest that when studying turnover phenomena in health organizations, the extra-work domains (WFC and JE) can contribute to a decrease in the intention to leave, in addition to the more typically emphasized attitude dimension.
authors: Laboratory Epsylon Dynamics of Human Abilities and Health Behaviors, Université Paul Valéry Montpellier 3, Montpellier, France. adalgisa.battistelli@univ-montp3.fr
authors: A
authors: A
authors: Battistelli
authors: I
authors: I
authors: Portoghese
authors: M
authors: M
authors: Galletta
authors: S
authors: S
authors: Pohl
mesh_terms: D000328:Adult; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007558:Italy; D007588:Job Satisfaction; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009726:Nurses / Q000600:supply & distribution*; D010563:Personnel Turnover / Q000706:statistics & numerical data*; D025341:Principal Component Analysis; D011795:Surveys and Questionnaires