Open Access, Peer-reviewed
eISSN 2093-758X
    J Korean Acad Nurs. 2015 Dec;45(6):846-856. Korean.
    Published online Dec 31, 2015.
    https://doi.org/10.4040/jkan.2015.45.6.846
    © 2015 Korean Society of Nursing Science
    Original Article

    Symptom Management to Predict Quality of Life in Patients with Heart Failure: A Structural Equation Modeling Approach

    Ja Ok Lee,1 and Rhayun Song2
      • 1The Catholic University Daejeon St. Mary's Hospital, Daejeon, Korea.
      • 2College of Nursing, Chungnam National University, Daejeon, Korea.
    • Address reprint requests to: Song, Rhayun. College of Nursing, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon 35015, Korea. Tel: +82-42-580-8331, Fax: +82-42-584-8915, Email: songry@cnu.ac.kr
    Received May 11, 2015; Revised May 20, 2015; Accepted August 12, 2015.

    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.

    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.

    Keywords
    Heart failure; Symptom; Management; Quality of life

    Figures

    Figure 1
    Model of heart failure self-care [2].

    Figure 2
    Path diagram of the hypothetical model.
    *p <.05; †p <.01; ‡p <.001; QOL=Quality of life; SS=Special symptom; GS=General symptom; DPA=Daily physical activity; IR=Inter-relationship; ES=Emotional status.

    Figure 3
    Path diagram of the hypothetical model including control variable.
    *p <.05; †p <.01; ‡p <.001; QOL=Quality of life; SS=Special symptom; GS=General symptom; DPA=Daily physical activity; IR=Inter-relationship; ES=Emotional status.

    Tables

    Table 1
    Fit Index of the Hypothetical Model

    Table 2
    Direct Effect, Indirect Effect, and Total Effect in Hypothetical Model (N =241)

    Notes

    This manuscript is a condensed form of the first author's doctoral dissertation from Chungnam National University.

    CONFLICTS OF INTEREST:The authors declared no conflict of interest.

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    MeSH Terms
    Quality of Life*
    Aged
    Female
    Health Knowledge, Attitudes, Practice
    Heart Failure/psychology*
    Humans
    Male
    Models, Theoretical
    Self Care
    Self Concept
    Social Support
    Surveys and Questionnaires
    Metrics
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