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Symptom Management to Predict Quality of Life in Patients with Heart Failure: A Structural Equation Modeling Approach
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Ja Ok Lee, Rhayun Song
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J Korean Acad Nurs 2015;45(6):846-856. Published online December 15, 2015
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DOI: https://doi.org/10.4040/jkan.2015.45.6.846
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 Abstract
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- Abstract
Purpose
The focus of this study was on symptom management to predict quality of life among individuals with heart failure. The theoretical model was constructed based on situation-specific theory of heart failure self-care and literature review.
Methods
For participants, 241 outpatients at a university hospital were invited to the study from May 19 to July 30, 2014. Data were collected with structured questionnaires and analyzed using SPSSWIN and AMOS 20.0.
Results
The goodness of fit index for the hypothetical model was .93, incremental fit index, .90, and comparative fit index, .90. As the outcomes satisfied the recommended level, the hypothetical model appeared to fit the data. Seven of the eight hypotheses selected for the hypothetical model were statistically significant. The predictors of symptom management, symptom management confidence and social support together explained 32% of the variance in quality of life. The 28% of variance in symptom management was explained by symptom recognition, heart failure knowledge and symptom management confidence. The 4% of variance in symptom management confidence was explained by social support.
Conclusion
The hypothetical model of this study was confirmed to be adequate in explaining and predicting quality of life among patients with heart failure through symptom management. Effective strategies to improve quality of life among patients with heart failure should focus on symptom management. Symptom management can be enhanced by providing educational programs, encouraging social support and confidence, consequently improving quality of life among this population.
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Citations
Citations to this article as recorded by  - Correlation between symptom status, health perception, and spiritual well‐being in heart failure patients: A structural equation modeling approach
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