Engagement, perceived leadership effectiveness, and performance as predictors of voluntary and involuntary turnover among nurses

Abstract

Turnover is costly to organizations due to lost productivity and employee replacement expenses. Nurses have particularly high voluntary turnover rates and are in high demand. The purpose of the research project is to examine predictors of voluntary and involuntary turnover among nurses. Hypotheses are that engagement and positive perceptions of leadership will be negatively related to voluntary turnover and stronger predictors of voluntary than involuntary turnover. Additionally, performance rating will be negatively related to involuntary turnover and a stronger predictor of involuntary than voluntary turnover. Data will be collected from several thousand nurses at geographically dispersed hospitals owned by a healthcare investment company. Engagement, perceptions of leadership, and performance data will be collected from records from the 2019 employee survey and performance appraisal process. Employee engagement and perceptions of leadership will be measured at the team level to maintain survey response confidentiality, meaning turnover will be measured as team turnover rate. Performance will be measured at the individual level in relation to individual turnover. Turnover will be captured using human resource records and linked to employees or teams using identification numbers. The data will be analyzed using logistic regression. There will be separate analyses with combinations of engagement, leadership perceptions, and performance with voluntary and involuntary turnover. It is expected that engagement and leadership perceptions will have significant negative relationships with voluntary turnover and will be more strongly related to voluntary turnover than involuntary turnover. It is also expected that performance will have a significant negative relationship with involuntary turnover and will be more strongly related to involuntary turnover than voluntary turnover. Findings will contribute to the scientific literature about predictors of turnover. Strengths of the proposed research are that it examines turnover rather than turnover intention and the data for the predictor and criteria variables will be measured approximately two years apart, allowing time for the turnover process to occur. Practitioners could use the findings to inform their efforts to predict and reduce organizational turnover, particularly among nurses

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