Modeling the path to digital health intention

The mediating role of system expectation and health beliefs

Bibliographic Data

ID22087584
AuthorsBo Pu (0000-0002-4711-2486, Sichuan Fine Arts Institute), Bowen Pu, Kuoliang Huang (Sichuan Fine Arts Institute, corresponding author)
Year2025
Volume13
Pages1697273-1697273
Publication date2025-10-07
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1697273
PMID41127607
OpenAlexW4414879794
LanguageEN
Citations received2
References cited64

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

Cognition · Digital health · Health promotion · mHealth · Precondition · Psychological intervention · Behavioral Health and Interventions · Digital Mental Health Interventions · Mobile Health and mHealth Applications

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