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J Multidiscip Care. 2022;11(2): 61-70.
doi: 10.34172/jmdc.2022.72
  Abstract View: 18
  PDF Download: 24

Original Article

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

Fatemeh Hassani 1 ORCID logo, Maryam Gholamzadeh Jofreh 1* ORCID logo, Kourosh Zarea 2 ORCID logo, Zahra Dashtebozorg 3 ORCID logo, Sally Wai-Chi Chan 4 ORCID logo

1 Department of Counseling, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
2 Nursing Care Research Center in Chronic Diseases, Department of Nursing, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
3 Department of Psychology, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
4 Tung Wah College, Hong Kong
*Corresponding Author: Corresponding Author: Maryam Gholamzadeh, Email: , Email: Maryam-jofreh@iauahvaz.ac.ir

Abstract

Background and aims: An important factor for determining the efficacy of treatment for patients under hemodialysis is the health-related quality of life (HRQOL). This study aimed to examine the predictor of HRQOL among hemodialysis (HD) patients based on spiritual well-being (SWB), perceived social support (PSS), health literacy (HL), and resilience.

Methods: The present correlational study was performed on 260 patients randomly selected from the teaching hospitals of Ahvaz Jundishapur University of Medical Sciences. Data collection tools were a 36-item HRQQL questionnaire, Paloutzian & Ellison SWB scale, Zimet PSS scale, the Connor and Davidson resilience scale, and Montazeri and colleagues’ HL for Iranian adults. Python software was used to conduct data analysis. Descriptive statistics, feedforward, and backpropagation algorithm in an artificial neural network (ANN) was used to determine the effect of studied variables on HRQOL.

Results: The mean age of patients was 51.73±15.32 years. Most of the patients were married (76.9%), had low-income level (55%), and had at least one comorbidity (59.2%). The mean duration of hemodialysis machine use was 5.06±3.43 years. Studied variables had grater impact on Physical QOL than the mental QOL. It was revealed that two dimensions of HL included evaluation skills (accuracy 0.92), accessibility skills (accuracy 0.92), and PSS (accuracy 0.88) were stronger predictors of physical QOL than other variables and SWB in the existence dimension (accuracy 0.80), understanding skills of HL (accuracy 0.76) and evaluation skills of HL (accuracy 0.75) were stronger predictors of mental QOL that other variables.

Conclusion: To improve the HRQOL of HD patients, we should increase HL, support social relationships, and improve meaning in life by giving importance to the SWB of these patients in providing care services to them.


Cite this article as: Hassani F, Gholamzadeh G, Zarea K, Dashtebozorg Z, Chan Z. 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. Journal of Multidisciplinary Care. 2022;11(2):61-70. doi: 10.34172/jmdc.2022.72.
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Submitted: 20 Jun 2022
Accepted: 21 Jun 2022
ePublished: 30 Jun 2022
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