Predicting the Intention to Use Generative Artificial Intelligence for Health Information: Comparative Survey Study.

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Bibliographic Details
Title: Predicting the Intention to Use Generative Artificial Intelligence for Health Information: Comparative Survey Study.
Authors: Matthes J; Department of Communication, University of Vienna, Waehringer Street 29, Vienna, 1090, Austria, 43 14277493., Reinhardt A; Department of Media and Communication, Ludwig-Maximilians-Universität München, Munich, Germany., Hodzic S; Department of Communication, University of Vienna, Waehringer Street 29, Vienna, 1090, Austria, 43 14277493., Kaňková J; Department of Communication, University of Vienna, Waehringer Street 29, Vienna, 1090, Austria, 43 14277493., Binder A; Department of Communication, University of Vienna, Waehringer Street 29, Vienna, 1090, Austria, 43 14277493., Bojic L; Digital Society Lab, Institute for Philosophy and Social Theory, University of Belgrade, Belgrade, Serbia.; Institute for Artificial Intelligence Research and Development of Serbia, Novi Sad, Serbia., Maindal HT; Department of Public Health, Aarhus University, Aarhus, Denmark., Paraschiv C; Laboratoire Interdisciplinaire de Recherche Appliquée en Économie de la Santé (LIRAES), Université Paris Cité, Paris, France., Ryom K; Department of Public Health, Aarhus University, Aarhus, Denmark.
Source: Journal of medical Internet research [J Med Internet Res] 2026 Jan 28; Vol. 28, pp. e75648. Date of Electronic Publication: 2026 Jan 28.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1438-8871
DOI:10.2196/75648