Exploring How Health-related Advertising Interference Contributes to the Development of Cyberchondria: A Stressor-strain-outcome Approach

Overview

Journal Digit Health

Specialty Medical Informatics

Date 2024 Feb 22

PMID 38384368

Authors

Xinmiao Zhang

Han Zheng

Yueliang Zeng

Jiayi Zou

Lin Zhao

Affiliations

Soon will be listed here.

Abstract

Objectives: Cyberchondria is increasingly recognized as the dark side of digital health, given the pervasive use of the internet as a main source of health information in people's daily lives. While previous studies have identified many factors contributing to cyberchondria, there is a dearth of research on the impact of health-related advertisements. Therefore, this study adopts the stressor-strain-outcome (SSO) model to investigate how health-related advertising interference is directly and indirectly related to cyberchondria.

Methods: To empirically validate the proposed research model, we conducted an online survey with 437 internet users with medical information seeking experience in China. Structural equation modeling (SEM) was employed to analyze the survey data.

Results: Our findings revealed a positive, direct association between health-related advertising interference and cyberchondria. Meanwhile, advertising interference was positively related to both information overload and information irrelevance, with the former further predicting cyberchondria. Moreover, doctor-patient communication weakened the positive effect of information overload on cyberchondria.

Conclusions: The study not only theoretically contributes to the literature by theorizing the relationship between health-related advertising interference and cyberchondria but also practically underlines the pivotal role of effective doctor-patient communication in reducing the development of cyberchondria.

Citing Articles

Online Health Information Seeking and Cyberchondria Among Men at Risk of HIV Infection: A Moderated Mediation Model.

Guo Y, Wang Y, Li Y Int J Sex Health. 2025; 37(1):102-115.

PMID: 39935906 PMC: 11810094. DOI: 10.1080/19317611.2024.2444590.

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