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Purpose: To examine how robot‐enabled focus on professional task engagement and robot‐reduced nonprofessional task engagement are related to nurses' professional turnover intention. Design: We adopted a two‐wave study design. Methods: We collected the first wave of data in a large hospital in Taiwan during October and November 2019 and the second wave between December 2019 and February 2020. We used the data collected from 331 nurses who participated in both waves. Findings: We found that robot‐enabled focus on professional task engagement is positively related to nurses' overall job satisfaction and perceived health improvement. Robot‐reduced nonprofessional task engagement is positively related to nurses' perceived health improvement. Both overall job satisfaction and perceived health improvement are negatively related to nurses' professional turnover intention. Conclusions: Robots' ability to focus nurses' efforts in professional tasks may help improve nurses' health and overall job satisfaction, and by extension reduce their turnover intention. Clinical Relevance: Nurse managers could suggest hospitals introduce robots, particularly those that can share nurses' nonprofessional workload. This, meanwhile, could focus nurses' efforts on professional task engagement. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to (a) test the fit of the hypothesized model for new nurses' intent to leave and (b) determine the extent to which personal characteristics, work conditions, and work-related fatigue predict intent to leave among new nurses. Design and Methods This study was a cross-sectional survey study. A total of 162 new nurses were recruited. A hypothesized model was proposed for model testing. Structural equation modelling was used for data analysis. Findings Work conditions only had an effect through work-related fatigue on new nurses' intent to leave. Personal characteristics did not have a significant effect on new nurses' intent to leave. The final model showed a good fit. Work-related fatigue, work conditions, and health explained 65% of the variance in new nurses' intent to leave. Conclusions Work-related fatigue was a major determinant of new nurses' intent to leave. More attention should be paid to fatigue reduction strategies among new nurses. Clinical Relevance Work-related fatigue should be monitored, particularly for new nurses who work more than 10 hr per day and who have greater workloads. [ABSTRACT FROM AUTHOR]

Purpose This study examined which aspects of professional commitment can effectively retain nurses in the nursing profession. Design, Settings, and Participants This study used a longitudinal design, simple random sampling, and two-wave data collection to survey and follow up a representative sample of 579 nurses for 1 year in a major medical center in northern Taiwan. Methods Items measuring each aspect of professional commitment came from Meyer et al.'s scale. In the second wave, administrative data were culled to determine whether these nurses remain employed as nurses. Structural equation modeling is used to analyze the data. Results Analytical results indicate that continuance commitment predicts nurse retention in the nursing profession (path coefficient = 0.34, p < .01). Conclusions Institutional efforts to improve continuance commitment (e.g., improved salary structures and enhanced professional development opportunities) likely retain nurses in the nursing profession. Clinical Relevance The findings of this study indicate the importance of continuance intention in retaining nurses. Nursing managers who face staff retention issues may consider making efforts to improve nurse salary and employer-sponsored benefits. [ABSTRACT FROM AUTHOR]