Prediction of health-related quality of life through health literacy, perceived social support, spiritual well-being, and resilience in patients undergoing hemodialysis: An artificial neural network study

Background and aims: An important factor for determining the efficacy of treatment patients under hemodialysis is health-related quality life (HRQOL). This study aimed to examine predictor HRQOL among (HD) based on spiritual well-being (SWB), perceived social support (PSS), health literacy (HL), resilience. Methods: The present correlational was performed 260 randomly selected from teaching hospitals Ahvaz Jundishapur University Medical Sciences. Data collection tools were a 36-item HRQQL questionnaire, Paloutzian & Ellison SWB scale, Zimet PSS Connor Davidson resilience Montazeri colleagues’ HL Iranian adults. Python software used conduct data analysis. Descriptive statistics, feedforward, backpropagation algorithm in an artificial neural network (ANN) determine effect studied variables HRQOL. Results: mean age 51.73±15.32 years. Most married (76.9%), had low-income level (55%), at least one comorbidity (59.2%). duration machine use 5.06±3.43 Studied grater impact Physical QOL than mental QOL. It revealed that two dimensions included evaluation skills (accuracy 0.92), accessibility 0.88) stronger predictors physical other existence dimension 0.80), understanding 0.76) 0.75) variables. Conclusion: To improve HD patients, we should increase HL, relationships, meaning by giving importance these providing care services them.