1. New insights on a recurring theme: A secondary analysis of nurse turnover using the National Sample Survey of Registered Nurses.
- Author
-
Jones CB, Kim S, McCollum M, and Tran AK
- Subjects
- Humans, United States, Cross-Sectional Studies, Employment, Personnel Turnover, Job Satisfaction, Nursing Staff, Nurses
- Abstract
Background: Registered nurse (RN) turnover is a recurring phenomenon that accelerated during COVID-19 and heightened concerns about contributing factors., Purpose: Provide baseline RN turnover data to which pandemic and future RN workforce turnover behaviors can be compared., Methods: A cross-sectional, secondary analysis of RN turnover using U.S. National Sample Survey of Registered Nurses 2018 data. Responses from 41,428 RNs (weighted N = 3,092,991) across the United States were analyzed. Sociodemographic, professional, employment, and economic data and weighting techniques were used to model prepandemic RN turnover behaviors., Discussion: About 17% of the sample reported a job turnover, with 6.2% reporting internal and 10.8% reporting external turnover. The factors common across both internal and external turnover experiences included education, employment settings, and years of nursing experience., Conclusions: Baseline RN turnover data can help employers and policymakers understand new and recurring nursing workforce trends and develop targeted actions to reduce nurse turnover., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)
- Published
- 2024
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