Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 10, 2025
Date Accepted: May 20, 2025

The final, peer-reviewed published version of this preprint can be found here:

Integrating the Situational Theory of Problem Solving and Technology Acceptance Model to Predict Intention to Practice Health Protective Behavior for Influenza-Like Illness Among TikTok Users: Cross-Sectional Study

Li C, Tham JS, Ghazali AHA, Hashim N, Kim JN

Integrating the Situational Theory of Problem Solving and Technology Acceptance Model to Predict Intention to Practice Health Protective Behavior for Influenza-Like Illness Among TikTok Users: Cross-Sectional Study

J Med Internet Res 2025;27:e73677

DOI: 10.2196/73677

PMID: 40601922

PMCID: 12268223

Integrating Situational Theory of Problem Solving and Technology Acceptance Model to Predict Intention to Practice Health Protective Behavior for Influenza-Like Illness: A Cross-Sectional Study of TikTok Users

  • Can Li; 
  • Jen-Sern Tham; 
  • Akmar Hayati Ahmad Ghazali; 
  • Norliana Hashim; 
  • Jeong-Nam Kim

ABSTRACT

Background:

Outbreaks of influenza-like illnesses (ILI) present significant public health challenges, heightening the need for timely and accessible health information. In response, many individuals increasingly rely on TikTok as a primary platform for acquiring health-related content, particularly among Chinese users. Despite TikTok’s growing role in digital health communication, existing research lacks an integrated perspective that combines problem-solving and technology adoption to comprehensively explain user engagement in this context.

Objective:

This study integrates the situational theory of problem solving (STOPS) and the technology acceptance model (TAM) to examine perceptions, communicative actions, and health-protective intentions related to influenza-like illness (ILI) among Chinese TikTok users.

Methods:

Using snowball and convenience sampling, online cross-sectional data were collected from 1,109 Chinese adults. Partial least squares structural equation modeling (PLS-SEM) analyzed the relationships between variables and tested the proposed model.

Results:

Technology beliefs significantly influence attitude, with perceived usefulness (β=.344, P<.001) and perceived ease of use (β=.359, P<.001) playing key roles. Risk perception (β=.050, P<.05) also positively affects attitude. Situational motivation is significantly enhanced by risk perception (β=.154, P<.001), problem recognition (β=.153, P<.001), and involvement recognition (β=.248, P<.001), while constraint recognition negatively impacts it (β=−.266, P<.001). Attitude (β=.390, P<.001) and situational motivation (β=.471, P<.001) positively influence communicative action, which predicts health-protective intentions (β=.390, P<.001).

Conclusions:

TikTok serves as an effective platform for health communication and behavior promotion in China. Integrating STOPS and TAM enhances understanding of digital health engagement, providing insights for designing effective online health communication strategies.


 Citation

Please cite as:

Li C, Tham JS, Ghazali AHA, Hashim N, Kim JN

Integrating the Situational Theory of Problem Solving and Technology Acceptance Model to Predict Intention to Practice Health Protective Behavior for Influenza-Like Illness Among TikTok Users: Cross-Sectional Study

J Med Internet Res 2025;27:e73677

DOI: 10.2196/73677

PMID: 40601922

PMCID: 12268223

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.