Predicting dietary management intention of patients with chronic kidney disease using protection motivation theory

H Huijie Li Y Yueyi Deng Y Yitong Huang (Center for Animal Disease Modeling and Surveillance) H Holly Blake

Abstract

Background Psychological determinants underlying the dietary management intention (DMI) of Chinese patients with chronic kidney disease (CKD) are not well understood. This hinders the development of theory-informed dietary interventions targeting this population. The aim of this study was to identify factors influencing DMI of Chinese patients with CKD through the lens of Protection Motivation Theory (PMT). Methods 500 patients with CKD from a nephrology ward of a large teaching hospital in China completed a survey including measures of PMT constructs (i.e., perceived vulnerability, perceived severity, intrinsic and extrinsic rewards, self-efficacy, response efficacy, and response cost) using validated scales adapted from previous studies. Data were analyzed using confirmatory factor analysis and multiple linear regression. Results Three PMT constructs, namely perceived severity [B = 0.198, P < 0.001], response efficacy [B = 0.331, P  < 0.001], and self-efficacy [B = 0.325, P  < 0.001], two demographic variables, namely single status [B = -0.180, P = 0.028] and education level [B = 0.080, P = 0.007], and a disease-related variable, namely CKD stage [B = .056, P = 0.001], predicted 39.3% of the variance of the CKD DMI. No significant effect on CKD DMI was observed for other predictor variables (P > 0.05). Conclusions Applying the PMT, significant predictors of DMI in Chinese patients with CKD were identified, which should be targeted in behavior change initiatives aimed at promoting dietary management.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 3
Published March 18, 2025
Pages e0320340
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (4)

H

Huijie Li

Y

Yueyi Deng

Y

Yitong Huang

Center for Animal Disease Modeling and Surveillance

H

Holly Blake