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Background: A clear understanding of factors affecting patients’ perception of quality of life (QOL) would be useful for improving continuous care in coronary artery disease (CAD) patients. Objective: To examine the causal relationships between cardiac self-efficacy, social support, left-ventricular ejection fraction (LVEF), angina, dyspnea, depression, vital exhaustion, functional performance, and QOL in CAD patients experiencing postpercutaneous coronary intervention (post-PCI). Methods: We used a research survey for causal analysis design to explore the theoretical linkage, guided by the revised Wilson and Cleary model, between QOL interest variables and patient QOL. The 303 subjects were all post-PCI CAD patients. All participants completed the following surveys: (1) a demographic data questionnaire, (2) a QOL Index (Cardiac version IV), (3) the Center for Epidemiologic Studies Depression Scale, (4) the Cardiac Self-efficacy Scale, (5) the Social Support Questionnaire, (6) the Rose Questionnaire for angina, (7) the Rose Dyspnea Scale, (8) the SF-36: vitality subscale, and (9) the Functional Performance Inventory Short-Form, with reliability ranging from 0.72 to 0.98. Data were analyzed using a linear structural relationship analysis. Results: The postulated model was found to fit the empirical data and explained 54% of the variance in quality of life (χ 2  = 1.90, df = 3, p = 0.59, χ 2 /df = 0.63, root mean square error of approximation = 0.00, Goodness of Fit Index = 0.99, Adjusted Goodness of Fit Index = 0.98). Social support, depression, and vital exhaustion were found to significantly and directly affect the QOL of post-PCI CAD patients. Cardiac self-efficacy was the only variable that had an indirect effect on quality of life (β = 0.21, p &lt; 0.001). Conclusion: Health care providers should be aware of the significant effects of social support, depression, vital exhaustion, and self-efficacy on QOL, and develop appropriate nursing interventions to improve quality of life in post-PCI CAD patients.

Factors predicting quality of life for coronary artery disease patients after percutaneous coronary intervention