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

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. 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. 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). 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.