title: Predictors of hospital nurses' intent to stay: a cross-sectional questionnaire survey in Shanghai, China.
abstract: OBJECTIVE
  To investigate predictors of hospital nurses' intent to stay in the nursing profession.
  
  
  METHODS
  A cross-sectional survey design was adopted. Over 1000 nurses working in hospitals in Shanghai, China, were invited to complete a survey questionnaire between May and October 2009 and 919 nurses responded for an 82% response rate.
  
  
  RESULTS
  Regression models explained 41.3% of variance in nurse intent to stay. Although the proposed model hypothesized 18 predictors of intent to stay, only seven were statistically significant factors of nurse intent to stay: normative commitment, economic costs commitment, age, limited alternatives commitment, praise/recognition, professional advancement opportunities and the hospital classification. Of these, the strongest predictors were normative commitment, economic costs commitment and age, which explained 37.3% of variance in nurse intent to stay.
  
  
  CONCLUSIONS
  Possible strategies to improve nurses' intent to stay include employment practices that improve the work environment, increased wages and benefits, and greater professional opportunity for nurses' personal growth development and promotion. Healthcare organizations should establish an asserting and nurturing environment for nurses and improve nurses' normative commitment and economic costs commitment. Increased effort should be made to improve nurses' conditions in primary and secondary hospitals where nurses report a lower level of intent to stay in nursing.
  
  
  CONCLUSIONS
  Participants came from a limited number of hospitals in Shanghai. A larger sample from different hospitals in Shanghai and other districts in Mainland China could have enhanced the generalizability of the results and increased the power of the study.
authors.affiliation: School of Nursing, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: L
authors.initials: L
authors.lastname: Wang
authors.forename: H
authors.initials: H
authors.lastname: Tao
authors.forename: C H
authors.initials: CH
authors.lastname: Ellenbecker
authors.forename: X H
authors.initials: XH
authors.lastname: Liu
mesh_terms: D001291:Attitude of Health Personnel; D002681:China; D003430:Cross-Sectional Studies; D005544:Forecasting; D033182:Intention; D007588:Job Satisfaction; D015233:Models, Statistical; D008962:Models, Theoretical; D009741:Nursing Staff, Hospital; D010563:Personnel Turnover; D012044:Regression Analysis; D011795:Surveys and Questionnaires