Suhee Kim; Kyongeun Lee

doi:10.4040/jkan.2016.46.5.733

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Original Article
Predictors of Turnover among New Nurses using Multilevel Survival Analysis: Suhee Kim, Kyongeun Lee; Journal of Korean Academy of Nursing 2016;46(5):733-743.
DOI: https://doi.org/10.4040/jkan.2016.46.5.733
Published online: October 31, 2016

¹College of Nursing·Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Korea.

²Department of Nursing, Tongmyong University, Busan, Korea.

Address reprint requests to : Lee, Kyongeun. Department of Nursing, Tongmyong University, 428 Sinseon-ro, Nam-gu, Busan 48520, Korea. Tel: +82-51-629-2686, Fax: +82-51-629-2679, leekyongeun@gmail.com

• Received: November 17, 2015 • Revised: August 5, 2016 • Accepted: August 8, 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

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Abstract
NOTES
REFERENCES

Abstract

Purpose
The purpose of this study was to examine factors influencing new graduate nurse turnover.
Methods
This study was carried out as a secondary analysis of data from the 2010 Graduates Occupational Mobility Survey (GOMS). A total of 323 nurses were selected for analysis concerning reasons for turnover. Data were analyzed using descriptive statistics and multilevel survival analysis.
Results
About 24.5% of new nurses left their first job within 1 year of starting their jobs. Significant predictors of turnover among new nurse were job status, monthly income, job satisfaction, the number of hospitals in region, and the number of nurses per 100 beds.
Conclusion
New graduate nurses are vulnerable to turnover. In order to achieve the best health of the nation, policy approaches and further studies regarding reducing new graduate nurse turnover are needed.
Keywords: Nurses; Employee Turnover; Survival Analysis; Multilevel Analysis

The authors declared no conflict of interest.

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Table 1

Turnover by General and Job-related Characteristics of Nurses (N=323)

^*Fisher's exact test.

Table 2

Characteristics of Region (N=16)

Table 3

Turnover by Characteristics of Region (N=323)

Table 4

Multilevel Survival Analysis of New Nurses'Turnover

HR=Hazard ratio; CI=Confidence interval.

Figure & Data

REFERENCES

Citations

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Predictors of Turnover among New Nurses using Multilevel Survival Analysis

J Korean Acad Nurs. 2016;46(5):733-743. Published online October 31, 2016

DOI: https://doi.org/10.4040/jkan.2016.46.5.733

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Predictors of Turnover among New Nurses using Multilevel Survival Analysis

Table 1

Turnover by General and Job-related Characteristics of Nurses (N=323)

^*Fisher's exact test.

Table 2

Characteristics of Region (N=16)

Table 3

Turnover by Characteristics of Region (N=323)

Table 4

Multilevel Survival Analysis of New Nurses'Turnover

HR=Hazard ratio; CI=Confidence interval.

Table 1 Turnover by General and Job-related Characteristics of Nurses (N=323)

^*Fisher's exact test.

Table 2 Characteristics of Region (N=16)

Table 3 Turnover by Characteristics of Region (N=323)

Table 4 Multilevel Survival Analysis of New Nurses'Turnover

HR=Hazard ratio; CI=Confidence interval.