Sook Ja Moon; Sang Sook Han

doi:10.4040/jkan.2011.41.5.633

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A Predictive Model on Turnover Intention of Nurses in Korea: Sook Ja Moon, Sang Sook Han; Journal of Korean Academy of Nursing 2011;41(5):633-641.
DOI: https://doi.org/10.4040/jkan.2011.41.5.633
Published online: October 31, 2011

¹Doctoral Students, College of Nursing Science, Kyung Hee University, Seoul, Korea.

²Professor, College of Nursing Science · East-West Nursing Research Institute, Kyung Hee University, Seoul, Korea.

Address reprint requests to: Han, Sang Sook. College of Nursing Science/East-West Nursing Research Institute, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul 130-701, Korea. Tel: +82-2-961-9427, Fax: +82-2-961-9398, sshan12@khu.ac.kr

• Received: October 5, 2010 • Accepted: October 24, 2011

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Abstract
NOTES
REFERENCES

Abstract

Purpose
The purpose of this study was to propose and test a predictive model that could explain and predict Korean nurses' turnover intentions.
Methods
A survey using a structured questionnaire was conducted with 445 nurses in Korea. Six instruments were used in this model. The data were analyzed using SPSS 15.0 and Amos 7.0 program.
Results
Based on the constructed model, organizational commitment, and burnout were found to have a significant direct effect on turnover intention of nurses. In addition, factors such as empowerment, job satisfaction, and organizational commitment were found to indirectly affect turnover intention of nurse. The final modified model yielded χ²=402.30, p<.001), χ²/df=2.94, RMSEA=0.07, RMR=0.03, GFI=0.90, AGF=0.87, NFI=0.88, CFI=0.92 and good fit indices.
Conclusion
This structural equational model is a comprehensive theoretical model that explains the related factors and their relationship with turnover intention in Korean nurses. Findings from this study can be used to design appropriate strategies to further decrease the nurses' turnover intention in Korea.
Keywords: Nurse; Turnover intention

This article is a revision of the first auther's Doctoral thesis from Kyung Hee University.

REFERENCES

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Figure 1

Hypothetical model.

Figure 2

Path diagram of the model.

^*p<.05; ^**p<.01.

Em=Empowerment; St=Stress; Oc=Organizational commitment; Bo=Burnout; Js=Job satisfaction; To=Turnover intention; Tv=Turnover intention variable.

Table 1

Result of the Fit Statistics of the Measurement Model

RMSEA=Root mean square error of approximation; RMRS=Root mean residual square; GFI=Goodness of fit index; AGFI=Adjusted Goodness-of-fit Index; NFI=Normed fit index; CFI=Goodness of fit index; FL=Factor loading; SRC=Standardized residual covariance.

Table 2

The Discriminant Validity of the Model

The shaded section; Average variance extracted. The non-shaded section; Correlation.

Table 3

Effects of Predictor Variables in the Modified Model

SMC=Squared multiple correlation.

Figure & Data

REFERENCES

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A Predictive Model on Turnover Intention of Nurses in Korea

J Korean Acad Nurs. 2011;41(5):633-641. Published online October 31, 2011

DOI: https://doi.org/10.4040/jkan.2011.41.5.633

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Figure

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A Predictive Model on Turnover Intention of Nurses in Korea

Figure 1 Hypothetical model.

Figure 2 Path diagram of the model. *p<.05; **p<.01. Em=Empowerment; St=Stress; Oc=Organizational commitment; Bo=Burnout; Js=Job satisfaction; To=Turnover intention; Tv=Turnover intention variable.

Figure 1

Figure 2

A Predictive Model on Turnover Intention of Nurses in Korea

Table 1

Result of the Fit Statistics of the Measurement Model

Table 2

The Discriminant Validity of the Model

The shaded section; Average variance extracted. The non-shaded section; Correlation.

Table 3

Effects of Predictor Variables in the Modified Model

SMC=Squared multiple correlation.

Table 1 Result of the Fit Statistics of the Measurement Model

Table 2 The Discriminant Validity of the Model

The shaded section; Average variance extracted. The non-shaded section; Correlation.