BRIEF RESEARCH REPORT article
Front. Digit. Health
Sec. Human Factors and Digital Health
Trust and Anxiety as Primary Drivers of Digital Health Acceptance in Multiple Sclerosis: Toward an Extended Disease-Specific Technology Acceptance Model
Felix Höpfl
Mira Brundiers
University of Applied Sciences Rosenheim, Rosenheim, Germany
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Abstract
Background: Digital health applications and AI-supported wearables may benefit people with Multiple Sclerosis (MS), yet fluctuating cognitive and physical symptoms may shape adoption in ways not fully captured by traditional technology acceptance models. Objective: To examine determinants of digital health acceptance in MS, focusing on emotional factors and disease-related moderators, and to compare these patterns with individuals living with other chronic conditions. Methods: An online survey (Winter 2024/2025) assessed Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) constructs in MS patients (n = 64) and a comparison group (n = 14). Measures included perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention (BI), social influence (SI), trust in technology (TT), technological anxiety (TA), symptom severity, and self-reported wearable/app use. Results: Groups did not differ significantly in PU, PEOU, BI, or SI (all p > .05), though comparisons should be interpreted cautiously due to the small comparison group. MS participants reported significantly lower regular wearable use (χ²(2) = 7.83, p = .020), indicating an intention–behavior gap. TT (β = .52, p < .001) and TA (β = −.38, p < .001) were the strongest predictors of BI, while PU and PEOU showed limited influence. Symptom severity moderated acceptance pathways by weakening PEOU effects and amplifying TA effects. Conclusion: Digital health acceptance in MS is primarily shaped by emotional and capability-related factors. We outline foundational elements of a disease-sensitive extension of technology acceptance frameworks and highlight implications for trust-building and anxiety-reducing design.
Summary
Keywords
artificial intelligence, Digital Health, Multiple Sclerosis, TAM, technology acceptance, UTAUT, wearables
Received
08 December 2025
Accepted
17 February 2026
Copyright
© 2026 Höpfl and Brundiers. 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: Felix Höpfl
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.