Hye Sook Kim; Hyang Sook So

doi:10.4040/jkan.2009.39.4.518

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A Prediction Model Development on Quality of Life in Kidney Transplant Recipients: Hye Sook Kim, Hyang Sook So; Journal of Korean Academy of Nursing 2009;39(4):518-527.
DOI: https://doi.org/10.4040/jkan.2009.39.4.518
Published online: August 31, 2009

¹Full-time Lecturer, Department of Nursing, Chodang University, Muan, Korea.

²Professor, College of Nursing, Chonnam National University, Gwangju, Korea.

Address reprint requests to: Kim, Hye Sook. Department of Nursing, Chodang University, 1644 Seongnam-ri, Muan-eup, Muan 534-701, Korea. Tel: 82-61-450-1812, Fax: 82-61-450-1812, opaal@hanmail.net

• Received: October 9, 2008 • Accepted: July 21, 2009

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Abstract
REFERENCES

Abstract

Purpose
The purpose of this study was to identify factors influencing quality of life in kidney transplant recipients and to understand the concrete pathway of influence and the power of each variable, so that integrated prediction model to promote the quality of life of kidney transplant recipients could be developed.
Methods
The sample was composed of 218 patients in follow-up care after a kidney transplant in one of 4 university hospitals in the Honam area. A structured questionnaire was used and the collected data were analyzed for fitness, using the LISREL program.
Results
This model was concise and extensive in predicting the quality of life of kidney transplant recipients.
Conclusion
The research verified the factors influencing quality of life for kidney transplant recipients and it verified that direct factors such as perception of health state, compliance, self-efficacy, stress and indirect factors such as self-efficacy and social support can be important factors to predict the quality of life for recipients. Moreover, those variables represent 87% of variance in explaining quality of life in a prediction model so that the variables can be utilized to predict quality of life for kidney transplant recipients.
Keywords: Kidney transplant recipient; Quality of life

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Figure 1

Path diagram for hypothetical model.

^*p<.05; ^**p<.01. χ₅=Medical personnel support; χ₆=Family support.

Figure 2

Path diagram for modified model.

^*p<.05; ^**p<.01. χ₅=Medical personnel support; χ₆=Family support.

Table 1

Descriptive Statistics of Observed Variables (N=218)

Table 2

Fitness Index for the Modified and Hypothetical Model (N=218)

df=degrees of freedom; GFI=goodness of fit index; AGFI=adjusted goodness of fit index; NFI=normed fit index; NNFI=non normed fit index; RMR=root mean square residual; RMSEA=root mean square error of approximation; PNFI=parsimonious normed fit index; CFI=comparative fit index; CN=critical N.

Table 3

Lisrel Estimates for the Modified Model and Direct, Indirect & Total Effects (N=218)

^*p<.05; ^**p<.01. SMC=squared multiple correlation.

Figure & Data

REFERENCES

Citations

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A Prediction Model Development on Quality of Life in Kidney Transplant Recipients

J Korean Acad Nurs. 2009;39(4):518-527. Published online August 31, 2009

DOI: https://doi.org/10.4040/jkan.2009.39.4.518

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A Prediction Model Development on Quality of Life in Kidney Transplant Recipients

Figure 1 Path diagram for hypothetical model. *p<.05; **p<.01. χ5=Medical personnel support; χ6=Family support.

Figure 2 Path diagram for modified model. *p<.05; **p<.01. χ5=Medical personnel support; χ6=Family support.

Figure 1

Figure 2

A Prediction Model Development on Quality of Life in Kidney Transplant Recipients

Table 1

Descriptive Statistics of Observed Variables (N=218)

Table 2

Fitness Index for the Modified and Hypothetical Model (N=218)

Table 3

Lisrel Estimates for the Modified Model and Direct, Indirect & Total Effects (N=218)

^*p<.05; ^**p<.01. SMC=squared multiple correlation.

Table 1 Descriptive Statistics of Observed Variables (N=218)

Table 2 Fitness Index for the Modified and Hypothetical Model (N=218)

Table 3 Lisrel Estimates for the Modified Model and Direct, Indirect & Total Effects (N=218)

^*p<.05; ^**p<.01. SMC=squared multiple correlation.