Abstract

Turnover intention among nurses is high, especially in the emergency department. However, factors that are associated with Chinese emergency department nurses' turnover intention have been scarcely studied. The present study examined relationships between turnover intention and demographic characteristics, job-related factors, depressive symptoms, and organizational commitment among emergency department nurses. A cross-sectional study of emergency department nurses was conducted in China between July and August 2018. The questionnaire included demographic characteristics (age, gender, level of education, and self-rated health status), job-related factors (qualification title, job seniority, night shifts, and workplace violence), depressive symptoms, organizational commitment, and turnover intention. A hierarchical linear regression model was used to identify factors that are associated with turnover intention among emergency department nurses. A total of 17 582 emergency department nurses participated in the study. The response rate was 68.9%. The findings indicated that poor self-rated health status (β=0.25, p < .001), working more than 11 night shifts per month (β=0.14, p < .01), experiencing workplace violence in the past year (β=0.08, p < .05), and higher depressive symptom scores (β=0.07, p < .001) positively correlated with turnover intention. More years of service (β=-0.38, p < .001) and higher organizational commitment scores (β=-0.45, p < .001) negatively correlated with turnover intention. Health status, job seniority, night shift frequency per month, workplace violence, depressive symptoms, and organizational commitment were significantly associated with emergency department nurses' turnover intention. To reduce turnover intention in the emergency department nurses, hospital administrators and managers should implement measures to improve their physical and mental health, increase organizational commitment, develop staff acceptable shift schedules, and reduce incidences of workplace violence.

Full Text
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