Jihyun Oh; Myungsun Yi

doi:10.4040/jkan.2014.44.1.75

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Original Article
Structural Equation Modeling on Quality of Life in Older Adults with Osteoarthritis: Jihyun Oh, Myungsun Yi; Journal of Korean Academy of Nursing 2014;44(1):75-85.
DOI: https://doi.org/10.4040/jkan.2014.44.1.75
Published online: February 28, 2014

College of Nursing, The Research Institute of Nursing Science, Seoul National University, Seoul, Korea.

Address reprint requests to: Oh, Ji Hyun. College of Nursing, The Research Institute of Nursing Science, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul 110-799, Korea. Tel: +82-2-740-8839, Fax: +82-2-740-8845, forshun@hanmail.net

• Received: August 31, 2013 • Revised: September 11, 2013 • Accepted: January 13, 2014

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 aim of this study was to explore how individual factors, physiologic factors, symptoms, environmental factors, functional status and health perception predict the quality of life (QOL) for older adults with osteoarthritis and to provide guidelines for interventions and strategies to improve QOL in these patients. The conceptual model was based on the Wilson and Cleary's Model.
Methods
Data were analyzed using SPSS WIN 20.0 and AMOS 19.0 program.
Results
The proposed model was a good fit for the data based on the model fit indices. Based on the constructed model, individual factors, social support, functional status and health perception were founded to have direct effects on QOL. Symptom had a indirect effect on QOL. Social support had a significant effect on QOL, and this model explained 63.6% of the variance in QOL.
Conclusion
The results of this study suggest that nursing strategies to increase QOL in this population should contain social support to promote QOL and manage functional limitations and health perception.
Keywords: Elderly osteoarthritis; Health attitude; Limitation of activity; Quality of life; Social support

This manuscript is based on a part of the first author's doctoral dissertation from Seoul National University.

REFERENCES

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Figure 1

Conceptual framework of this study.

Figure 2

Path diagram for the modified model.

Table 1

Descriptive Statistics of Observed Variables (N=180)

Table 2

Comparison of Model Fit for the Modified Model to the Hypothetical Model

GFI=Goodness of Fit Index; RMSEA=Root mean squared error of approximation; NFI=Normed Fit Index; CFI=Comparative Normed of Fit Index; TLI=Tucker-Lewis Index; PGFI=Parsimonious Goodness of Fix Index; PNFI=Parsimonious Normed Fit Index.

Table 3

Standardized Direct, Indirect, and Total Effects for the Modified Model

^*p<.05; ^†p<.01; β=Standardized regression weight; SMC=Squared multiple correlation (R²); C.R.=Critical ratio.

Figure & Data

REFERENCES

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Structural Equation Modeling on Quality of Life in Older Adults with Osteoarthritis

J Korean Acad Nurs. 2014;44(1):75-85. Published online February 28, 2014

DOI: https://doi.org/10.4040/jkan.2014.44.1.75

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Structural Equation Modeling on Quality of Life in Older Adults with Osteoarthritis

Figure 1 Conceptual framework of this study.

Figure 2 Path diagram for the modified model.

Figure 1

Figure 2

Structural Equation Modeling on Quality of Life in Older Adults with Osteoarthritis

Table 1

Descriptive Statistics of Observed Variables (N=180)

Table 2

Comparison of Model Fit for the Modified Model to the Hypothetical Model

Table 3

Standardized Direct, Indirect, and Total Effects for the Modified Model

^*p<.05; ^†p<.01; β=Standardized regression weight; SMC=Squared multiple correlation (R²); C.R.=Critical ratio.

Table 1 Descriptive Statistics of Observed Variables (N=180)

Table 2 Comparison of Model Fit for the Modified Model to the Hypothetical Model

Table 3 Standardized Direct, Indirect, and Total Effects for the Modified Model

^*p<.05; ^†p<.01; β=Standardized regression weight; SMC=Squared multiple correlation (R²); C.R.=Critical ratio.