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This paper is in the following e-collection/theme issue:

Usability of Apps and User Perceptions of mHealth (1242) Mobile Health (mhealth) (3668) Artificial Intelligence (2365) Quality/Credibility of eHealth Information and Trust Issues (674) Qualitative Methods (148)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64715, first published .
Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study

Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study

Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study

Authors of this article:

Katie Ryan1 Author Orcid Image ;   Justin Hogg1 Author Orcid Image ;   Max Kasun1 Author Orcid Image ;   Jane Paik Kim1 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

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  2. Panfil A, Tamasan S, Vasilian C, Horhat R, Lungeanu D. Neuroception of Psychological Safety and Attitude Towards General AI in uHealth Context. Multimodal Technologies and Interaction 2025;10(1):4 View
  3. Agrawal S, Agbeyangi A. Adoption of AI-enabled mental health wearables in India: The roles of psychological assurance and algorithmic credibility. Computers in Human Behavior: Artificial Humans 2026;7:100259 View
  4. Khan M, Gul Z, Yasmeen Z, Akram I. From Doctors to Chatbots: Effect of Disease Threat and Sigma on AI Health Information Seeking Behavior. Qlantic Journal of Social Sciences and Humanities 2026;VII(I):58 View
  5. Subedi R, Chakraborty S, He Z, Pang Y, Zhang S, Lustria M, Charness N, Boot W. Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults Using Source-Free Domain Adaptation: Algorithm Development and Validation. JMIR Aging 2026;9:e79123 View