Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study
This paper provides additional context relating to a number of concerns previously posited or identified in the AI-mHealth literature, including trust, explainability, and information sharing, and revealed additional considerations that have not been previously documented, that is, users' differentiation between the value of AI-mHealth for physical and mental health use cases and their willingness to extend empathy to nonexplainable AI. To the best of our knowledge, this study is the first to apply an open-ended, qualitative descriptive approach to explore the perspectives of end users of direct-to-consumer AI-mHealth apps.
Authors
- Max Kasun (ORCID: https://orcid.org/0000-0002-6364-6234)
- Katie Ryan (ORCID: https://orcid.org/0000-0003-1437-3126)
- Justin Hogg (ORCID: https://orcid.org/0009-0005-9329-606X)
- Jane Kim (ORCID: https://orcid.org/0000-0002-1475-9822)
Institutions
- Stanford University (US)
Publication Details
- Journal
- JMIR mhealth and uhealth
- Published
- 2025-04-25
- DOI
- https://doi.org/10.2196/64715
- Citations
- 6
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 9.26