ORIGINAL RESEARCH article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1697273
This article is part of the Research TopicAI and Mobile Technologies for Population-Level Chronic Disease PreventionView all articles
Modeling the Path to Digital Health Intention: The Mediating Role of System Expectation and Health Beliefs
Provisionally accepted- Sichuan Academy of Fine Arts, Chongqing, China
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Introduction: While mobile health (mHealth) offers a seemingly scalable solution to the persistent challenge of chronic disease prevention, its real-world public health impact has arguably been blunted by a single, stubborn issue: low user adherence. The difficulty, in our view, stems from a tendency in the existing literature to treat technology and user psychology as separate domains. This creates what we call a theoretical "black box" between the features of a digital intervention and the behavioral outcomes it is meant to produce. Without a clearer picture of what happens inside this box, efforts to create truly data-driven and effective population-level interventions remain somewhat handicapped. Methods: A self-administered online survey using Wenjuanxing (wjx.cn) was undertaken in a cross-sectional design. Chinese adults (≥18 years) with pre-existing exposure to or intention to use digital health were the target population; a non-probability, voluntary sampling frame yielded 620 usable surveys after screening for quality. The psychometrics were tested, and screening of common-method bias (full-collinearity VIF) preceded testing of structural paths and serial mediation from persuasive features (functional/experiential) to system expectations and through to health beliefs to intention using PLS-SEM. Results: The data showed that Persuasive Experiential Support (PES) was a key antecedent for Integrated System Expectation (ISE), which in turn stood out as the strongest predictor of Persuasive Health Belief (PHB). Interestingly, we also uncovered a substantial measurement overlap between our PHB construct and Behavioral Intention (BI)—a finding that points toward a potential "belief-intention fusion" process in these kinds of highly persuasive digital environments. Conclusion: Taken together, these results seem to advocate for what might be called an "experience-first, function-as-assist" design philosophy for mHealth interventions targeting chronic disease at scale. In other words, prioritizing an engaging user experience looks to be a critical precondition for building the system trust needed to actually foster health beliefs and drive intentions. Perhaps more importantly, our unexpected finding regarding belief-intention fusion opens up a new, testable research agenda—one that explores how real-time digital interactions might be fundamentally reshaping the cognitive pathways of decision-making. This is a crucial question for the next generation of AI-driven, population-level health promotion tools.
Keywords: Mobile health (mHealth), persuasive systems design, health belief model, useradherence, Behavioral Intention, population health, Chronic disease prevention, PLS-SEM
Received: 02 Sep 2025; Accepted: 22 Sep 2025.
Copyright: © 2025 Pu and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kuoliang Huang, shashiliang@gmail.com
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