Factors Predicting Health-Related Quality of Life in Patients with Post-COVID Condition
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Abstract
Purpose: To study predictive power of body-mass index, sleep quality, fatigue, and social support on health-related quality of life among patients with post-COVID condition.
Design: Predictive correlational research.
Methods: The sample consisted of 126 patients with post-COVID condition aged 18 years and older, who had been admitted to the outpatient departments of two tertiary hospitals in Bangkok. The research instruments included personal data and illness record questionnaires, Pittsburgh Sleep Quality Index, Functional Assessment of Chronic Illness Therapy-Fatigue Scale, Revised Thai version of the Multidimensional Scale of Perceived Social Support, and EuroQol Group-5 Dimension-5 Levels. Data were analyzed using descriptive statistics and multiple regression.
Main findings: The utility score of patients with post-COVID condition ranged from -1 to 1, with a mean of .83 (SD = .10). Multiple regression analysis revealed that all of the independent variables could account for 68% (R2 = .68) of the variance explained in health-related quality of life. The strongest predictor was fatigue (β = .67, p < .001), followed by social support (β = .21, p < .001) and sleep quality (β = - .13, p = 033).
Conclusion and recommendations: Nurses and health care providers should assess health-related quality of life and its determinant factors, namely fatigue, sleep quality, and social support. Moreover, nursing programs should be created to relieve fatigue or promote sleep quality and social support in patients with post-COVID condition to achieve a good health-related quality of life in the future.
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