A model for predicting factors affecting health information avoidance on WeChat.

ABSTRACT:

Objective

WeChat serves as a crucial source of health information, distinguished by its highly personalized nature. Avoidance of such personalized health information has a direct impact on individuals' health decision-making. This study aims to identify the factors influencing personalized health information avoidance on WeChat and to construct a hierarchical framework illustrating the relationships among these factors.

Methods

A hybrid method was utilized. Semi-structured interviews and grounded theory were used to identify the influencing factors. The interpretive structural modeling (ISM) method was adopted to develop a hierarchical model of the identified factors, followed by matrice d'impacts croises-multiplication appliqué a un classemen (MICMAC) to analyze the depende

SUBMITTER: Chen M 

PROVIDER: S-EPMC11826881 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature