Predicting the Intention to Use Generative Artificial Intelligence for Health Information: Comparative Survey Study
Generative AI use for health information is currently driven by early adopters-those who find it useful, easy to integrate, enjoyable, and have the necessary skills and infrastructure to do so. Cross-national consistency suggests a shared adoption pattern across Europe. To promote equitable adoption, communication efforts should focus on usefulness, convenience, and enjoyment, while ensuring digital access and safeguards for vulnerable users.
Authors
- Corina Paraschiv (ORCID: https://orcid.org/0000-0001-8762-9482)
- Alice Binder (ORCID: https://orcid.org/0000-0003-3266-8614)
- Anne Reinhardt (ORCID: https://orcid.org/0000-0001-5231-0877)
- Jaroslava Kaňková (ORCID: https://orcid.org/0009-0007-2364-844X)
- Knud Ryom
- Selma Hodzic
- Helle Terkildsen Maindal
- Jörg Matthes
- Ljubisa Bojic
Institutions
- University of Vienna (AT)
- Aarhus University (DK)
- Université Paris Cité (FR)
- University of Belgrade (RS)
- Laboratoire Interdisciplinaire pour la Sociologie Economique (FR)
- Boehringer Ingelheim (Austria) (AT)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2026-01-28
- DOI
- https://doi.org/10.2196/75648
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 17.70