Predictors of the intentions to leave among nurses in an academic medical center

Bibliographic Details
Title: Predictors of the intentions to leave among nurses in an academic medical center
Authors: Aoi Sato, Yoshiteru Sato, Norio Sugawara, Masataka Shinozaki, Hiroaki Okayasu, Yasushi Kawamata, Keita Tokumitsu, Yumiko Uchibori, Tomie Komatsu, Norio Yasui‐Furukori, Kazutaka Shimoda
Source: PCN Reports, Vol 1, Iss 4, Pp n/a-n/a (2022)
Publisher Information: Wiley, 2022.
Publication Year: 2022
Collection: LCC:Psychiatry
Subject Terms: intentions to leave, management, nurses, university hospital, work environments, Psychiatry, RC435-571
More Details: Abstract Aim Nurses are an essential human resource for the healthcare system. However, high turnover of nurses is a current issue. Reducing the high turnover of nurses is crucial for facilitating the sustainable provision of care in hospitals. The purpose of this study was to explore the factors affecting nurses' intentions to leave among nurses in an advanced medical center. Methods Using a cross‐sectional design, we conducted a questionnaire survey of nurses working at an academic medical center in August 2020. Of the 1063 distributed questionnaires, there were 821 (77.2%) valid responses. The questionnaire included items on the Kessler 6 (K6), New Brief Job Stress Questionnaire (New BJSQ), Organizational Justice Questionnaire (OJQ), and intention to leave a hospital job. Results Overall, the mean age of the nurses was 34.3 ± 10.1 years and 87.8% (721/821) of them were female. Among respondents, 19.5% (160/821) had a strong intention to leave. After adjusting for all the variables, a logistic regression analysis revealed that longer working hours, job rank (staff nurse), work–self‐balance positive (imbalance), workplace harassment (no bullying), and interactional justice (unfair supervisor) were determinants associated with strong intentions to leave. Conclusions Approximately one‐fifth of nurses working at advanced medical center had a strong intention to leave. However, our findings can help managers predict the turnover of nurses by understanding occupational characteristics. Managing work–self‐balance and treating staff fairly could improve work environments. Further research focusing on the outcome of actual turnover rather than intention to leave is needed.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2769-2558
Relation: https://doaj.org/toc/2769-2558
DOI: 10.1002/pcn5.48
Access URL: https://doaj.org/article/0d1cb7bf278f4daeb3e3795e58c1d4ce
Accession Number: edsdoj.0d1cb7bf278f4daeb3e3795e58c1d4ce
Database: Directory of Open Access Journals
More Details
ISSN:27692558
DOI:10.1002/pcn5.48
Published in:PCN Reports
Language:English