Intensive care unit staff nurses: predicting factors for career decisions

Aims and Objectives. The aim of this study was to understand the factors related to intention to leave their job among intensive care unit (ICU) nurses in eastern Taiwan and to make between-group comparisons between an intention to leave and an intention to stay as well as to predict the influencing factors that affect ICU staff nurses’ intention to leave. Background. Nurses’ intention to leave their job may have an important impact on the actual turnover of nurses. The issue has always been of concern to nursing executives. Only limited empirical studies in the area have been investigated in an Asian culture context and particularly the eastern Taiwan region. Methods. A cross-sectional predictive study was performed during 2005 with 130 nurses recruited from two ICUs at a medical centre. A researcher-designed questionnaire based on the Cooper's model with structured interviews was used to determine each nurse's characteristics and their intention to leave their job. Multiple logistic regression analysis was employed to investigate the various factors associated with this. Results. The overall response rate was 100%; 63 (48·9%) revealed that they intended to leave their jobs. The findings were that their self-rated health status, the number of diseases, the level of happiness, the presence of depression, job satisfaction, sleep quality, type of license and their unit were significantly associated with an intention to leave (p = 0·05–0·001). Depression and sleep quality proved to be the most significant predictors of ICU staff nurses’ intention to leave their job. Conclusions. The findings suggest that there is a need to take steps to improve nurses’ health-related quality of life and to develop effective strategies to improve nurse retention. Relevance to clinical practice. A succinct validated instrument would help identify the important factors that predict ICU nurses’ intention to leave their job, which may result in job disengagement. Predictors found in this study may be used as outcome variables for developing such an effective method of improving nurse retention in ICUs.