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Original Article

Predictors of Turnover Intention among Nurses in Small and Medium-sized Hospitals

Jeong Hye Park1, Hye Young Hwang2
Journal of Korean Academy of Nursing Administration 2017;23(5):471-482.
Published online: December 31, 2017

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Corresponding author: Hwang, Hye Young. Department of Nursing, Gim-cheon University, 214 Daehack-ro, Gimcheon 39528, Korea. Tel: +82-54-420-4237, Fax: +82-54-420-4292, 20120035@gimcheon.ac.kr
• Received: August 14, 2017   • Revised: November 12, 2017   • Accepted: November 26, 2017

Copyright © 2017 Korean Academy of Nursing Administration

This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Purpose
    The purpose of this study was to explore the predictors of turnover intention among nurses working in small and medium-sized hospitals in South Korea.
  • Methods
    Data were obtained from a survey conducted in 2016 on welfare policy and system improvement. The participants were nurses of the Korean Nurses Association who worked in small and medium-sized hospitals. The responses of 2,011 nurses were analyzed using hierarchical multiple regression analysis, which was performed to explore the predictors of nurses' turnover intentions.
  • Results
    The findings of this study showed that the predictors significantly reducing nurses' desire to leave their hospitals were a 40-hour workweek, satisfaction with the salary, and six out of the 40 fringe benefits provided by their hospitals: the provision of uniforms and work shoes, paid menstrual leave, operational costs for the department, job-related educational costs, and in-house nurse training program.
  • Conclusion
    These findings suggest that hospitals should provide proper work hours and reasonable rewards for nurses' work in order to reduce turnover intention among their nurses.
  • Key Words: Nurses; Employee turnover; Hospitals; Salaries and fringe benefits

This work was supported by 2016 Korean Nurses Association.

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Table 1

Differences in Turnover Intention according to Participant Characteristics (N=2,011)

jkana-23-471-i001.jpg
Table 2

Fringe Benefit Rate for Nurses in Small and Medium-sized Hospitals (N=2,011)

jkana-23-471-i002.jpg
Table 3

Relationship among Salary Satisfaction, Fringe Benefits and Turnover Intention (N=2,011)

jkana-23-471-i003.jpg
Table 4

Factors Influencing Turnover Intention by Multiple Hierarchical Regression Analysis (N=2,011)

jkana-23-471-i004.jpg

*Special units=intensive care unit, operation room, emergency room.

Figure & Data

References

    Citations

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    Predictors of Turnover Intention among Nurses in Small and Medium-sized Hospitals
    J Korean Acad Nurs Adm. 2017;23(5):471-482.   Published online December 31, 2017
    DOI: https://doi.org/10.11111/jkana.2017.23.5.471
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    Predictors of Turnover Intention among Nurses in Small and Medium-sized Hospitals
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    DOI: https://doi.org/10.11111/jkana.2017.23.5.471
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    Related articles

    Predictors of Turnover Intention among Nurses in Small and Medium-sized Hospitals
    Predictors of Turnover Intention among Nurses in Small and Medium-sized Hospitals

    Differences in Turnover Intention according to Participant Characteristics (N=2,011)

    Fringe Benefit Rate for Nurses in Small and Medium-sized Hospitals (N=2,011)

    Relationship among Salary Satisfaction, Fringe Benefits and Turnover Intention (N=2,011)

    Factors Influencing Turnover Intention by Multiple Hierarchical Regression Analysis (N=2,011)

    *Special units=intensive care unit, operation room, emergency room.
    Table 1 Differences in Turnover Intention according to Participant Characteristics (N=2,011)

    Table 2 Fringe Benefit Rate for Nurses in Small and Medium-sized Hospitals (N=2,011)

    Table 3 Relationship among Salary Satisfaction, Fringe Benefits and Turnover Intention (N=2,011)

    Table 4 Factors Influencing Turnover Intention by Multiple Hierarchical Regression Analysis (N=2,011)

    *Special units=intensive care unit, operation room, emergency room.

    Table 1

    Table 2

    Table 3

    Table 4

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