Predictors of Adherence to Treatment in Hemodialysis Patients: A Structural Equation Modeling

Background: Non-compliance to the treatment is a major problem in hemodialysis patients. This study aimed to determine factors predicting adherence to treatment in hemodialysis patients in selected cities of Khuzestan province, Iran. Methods: This cross-sectional study was conducted on 500 patients undergoing hemodialysis in Ahvaz, Shush, Shushtar, and Dezful cities. The data collection tools were ESRD-AQ, perceived health, perceived social support, Beck Depression, self-efficacy, and demographic and clinical factors questionnaires. Data were analyzed using descriptive statistics, t-test, ANOVA, and Pearson's correlation coefficient. Structural equation modeling (SEM) was employed to analyze the relationship between various exogenous and endogenous or mediating variables. Results: The results showed that all predicting variables of perceived social support, depression, self-efficacy, and perceived health had been associated with the variable of adherence to treatment. Accordingly, there was a reverse correlation between social support and depression (p< 0.001, r= -0.94), as well as depression and self-efficacy (p< 0.001, r= -0.87). There was a direct correlation between self-efficacy and perceived health (p< 0.001, r= 0.79), perceived health and adherence to treatment (p< 0.001, r= 0.72). Fitness indices also indicate the adequacy of the proposed model (X2/df= 4.94, CD=0.937, SRMR=0.076, TLI= 0.870, CFI= 0.873, RMSEA= 0.071). Conclusion: The results showed that high social support, low level of depression, high perceived self-efficacy, and high perceived health predicted better compliance with the treatment in hemodialysis patients. The proposed model can be used as a framework to improve adherence to treatment regimens in hemodialysis patients.