The Mechanism of Online Health Information Seeking Switching to Online Medical Consultation: Cross-Sectional Study

Q: What is the study’s objective?

The study aims to explore the correlation mechanisms of online medical community users’ switching behaviors from OHIS to OMC.

Q: How does the research model the switching from OHIS to OMC?

It builds a research model of users’ willingness to transition from OHIS to OMC using knowledge-attitude-practice theory, combining social support theory and the health belief model.

Q: Which factors influence patients’ transition to online consultation behavior?

Perceived susceptibility, severity, and benefits positively influence the switch, while perceived barriers negatively impact transitioning to online consultation behavior.

Sep 30, 2026

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Internet health care is presented as a key solution for distributing high-quality medical resources and improving health equity in China. The study investigates how users transition from online health information seeking (OHIS) to online medical consultation (OMC), given that OMC use among Chinese patients remains relatively low. Using knowledge-attitude-practice theory with social support theory and the health belief model, the research applies questionnaire survey data and structural equation modeling to identify knowledge support, beliefs, and perceived barriers as drivers of switching behavior.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Background

Objective

Methods

Results

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Keywords

Introduction

JMIR FORMATIVE RESEARCH Zhang et al Original Paper The Mechanism of Online Health Information Seeking Switching to Online Medical Consultation: Cross-Sectional Study | Lijiang Zhang1,2*, PhD; Jingjing Xia1*, MS; Hui Chen1*, MS; Yang Bai3,4,5*, PhD; Jun Wang4,5, PhD; Liuan Wang6,7,8, PhD; Wenjie Ren2*, PhD | | --- | | 1School of Health Management, Henan Medical University, Xinxiang, Henan, China 2Institutes of Health Central Plains, Henan Medical University, Xinxiang, Henan, China 3School of Public Administration and Policy, Renmin University of China, Beijing, China 4Center for Health Policy Research and Evaluation, Renmin University of China, Beijing, China 5Healthy China Institute, Renmin University of China, Beijing, China
6School of Management, Beijing Institute of Technology, Beijing, China 7Social Science Domain, Beijing Institute of Technology, Zhuhai, China 8Qionghai Hospital of Traditional Chinese Medicine, Qionghai, China
*these authors contributed equally
Corresponding Author:
Jun Wang, PhD
Center for Health Policy Research and Evaluation Renmin University of China
59 Zhongguancun Street Hai Dian District Beijing, 100872
China
Phone: 86 8611290668
[Email:](Email: hpreruc2022@126.com)[ ](Email: hpreruc2022@126.com)[hpreruc2022@126.com](Email: hpreruc2022@126.com)
Related Article:
This is a corrected version. See correction statement in: [https://formative.jmir.org/2026/1/e94748](https://formative.jmir.org/2026/1/e94748)
Abstract | Background: Internet health care plays a crucial role in addressing the challenge of distributing high-quality medical resources and promoting the optimal allocation of these resources and health equity in China. Online medical consultation (OMC) plays amore significant role than online health information seeking (OHIS) . Currently, the proportion of Chinese patients using OMCis low. Therefore, it is essential to enhance patient engagement with OMC and fully leverage the role of internet health care in optimizing the allocation of medical resources. Objective: This study aims to explore the correlation mechanisms of online medical community users’ switching behaviors from OHIS to OMC. Methods: This study is based on the knowledge-attitude-practice theory, which combines the social support theory and the health belief model to construct a research model of users’ willingness to transition from OHIS to OMC. The study adopts a questionnaire survey and structural equation modeling method to conduct an empirical study. Results: Gaining knowledge about information support has a significant positive impact on perceived susceptibility (β= .339, P< .001), perceived severity (β= .348, P< .001), and perceived benefits (β= .361, P< .001), while having a significant negative impact on perceived barriers (β=–.285, P< .001) . Gaining knowledge about emotional support positively affects perceived susceptibility (β= .220, P< .001) and perceived benefits (β= . 149, P< .01) but does not significantly influence perceived severity (β=–.006, P> .05) or perceived barriers (β= .099, P> .05) . Perceived susceptibility (β= . 123, P< .05), perceived severity (β= . 174, P< .001), and perceived benefits (β= .273, P< .001) positively influence patients’transition to online consultation behavior, whereas perceived barriers (β=–. 112, P< .05) negatively impact this switch. In addition, we found that gaining knowledge about information support not only directly affects patients’behavior in switching to online consultations but also impacts patients’OMCs through perceived susceptibility (14.23%), perceived severity (13.17%), and perceived benefits (25.28%). In contrast, gaining knowledge about emotional support does not directly influence patient behavior transfer; it operates only through perceived susceptibility (46.95%) and perceived benefit (52.90%) . [https://formative.jmir.org/2025/1/e78397](https://formative.jmir.org/2025/1/e78397) XSL• FO RenderX JMIR Form Re

FAQs

What is the study’s objective?

The study aims to explore the correlation mechanisms of online medical community users’ switching behaviors from OHIS to OMC.

How does the research model the switching from OHIS to OMC?

It builds a research model of users’ willingness to transition from OHIS to OMC using knowledge-attitude-practice theory, combining social support theory and the health belief model.

Which factors influence patients’ transition to online consultation behavior?

Perceived susceptibility, severity, and benefits positively influence the switch, while perceived barriers negatively impact transitioning to online consultation behavior.

Sep 30, 2026

Uploaded by Cart