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

Generative Language Models Including ChatGPT (708) Information Seeking, Information Needs (561) Chatbots and Conversational Agents (740) Demographics of Users, Social & Digital Divide (914) eHealth Literacy / Digital Literacy (528) Assessing and Building eHealth / Digital Literacy in Populations (64)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55138, first published .
Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study

Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study

Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study

Authors of this article:

Oluwatobiloba Ayo-Ajibola1 Author Orcid Image ;   Ryan J Davis1 Author Orcid Image ;   Matthew E Lin2 Author Orcid Image ;   Jeffrey Riddell3 Author Orcid Image ;   Richard L Kravitz4 Author Orcid Image
Article Authors Cited by (16) Tweetations Metrics

Journals

  1. Ayo-Ajibola O, Julien C, Lin M, Riddell J, Duan N, Kravitz R. Association of Primary Care Access with Health-Related ChatGPT Use: A National Cross-Sectional Survey. Journal of General Internal Medicine 2025 View
  2. Liu J, Segal K, Daher M, Ozolin J, Binder W, Bergen M, McDonald C, Owens B, Antoci V. Artificial intelligence versus orthopedic surgeons as an orthopedic consultant in the emergency department. Injury 2025;56(4):112297 View
  3. Young A, Omosun F. A comparative analysis of CDC and AI-generated health information using computer-aided text analysis. Journal of Communication in Healthcare 2025;18(3):205 View
  4. Thompson P, Thornton R, Ramsden C. Assessing chatbots ability to produce leaflets on cataract surgery: Bing AI, chatGPT 3.5, chatGPT 4o, ChatSonic, Google Bard, Perplexity, and Pi. Journal of Cataract & Refractive Surgery 2025;51(5):371 View
  5. Alain G, Crick J, Snead E, Quatman-Yates C, Quatman C. Evaluating User Interactions and Adoption Patterns of Generative AI in Health Care Occupations Using Claude: Cross-Sectional Study. Journal of Medical Internet Research 2025;27:e73918 View
  6. Lim J, Hong N. Perceived Search Overload, Generative AI Credibility, and Comparative Usefulness: A Channel Complementarity Approach to Health Information Seeking. Health & New Media Research 2025;9(1):124 View
  7. Bautista J, Herbert D, Farmer M, De Torres R, Soriano G, Ronquillo C. Health Consumers' Use and Perceptions of Health Information from Generative Artificial Intelligence Chatbots: A Scoping Review. Applied Clinical Informatics 2025;16(04):892 View
  8. Singla R, Lodhi S, Kibret T, Jegatheswaran J, Glavinovic T, Massicotte‐Azarniouch D, Karpinski J, Powell R, Burns K, Sood M, Bugeja A. Accuracy, Clarity, and Comprehensiveness of ChatGPT Outputs for Commonly Asked Questions About Living Kidney Donation. Clinical Transplantation 2025;39(9) View
  9. Wardle C, Urbani S, Wang E. Evolving Health Information–Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol. Journal of Medical Internet Research 2025;27:e79961 View
  10. Wang A, He D, Luo Z, Ma F. User Studies in Generative Interactive IR (GenIIR): An ISIC‐Informed Systematic Review. Proceedings of the Association for Information Science and Technology 2025;62(1):1705 View
  11. Erden Y, Temel M, Bağcıer F. Evaluating ChatGPT-4 for rheumatology patient education: a comparative analysis of readability, reliability, and similarity to the American College of Rheumatology’s fact sheets. Rheumatology 2025;63(5):313 View
  12. Haber T, Hinman R, Merolli M. Uses of Artificial Intelligence in Nonpharmacological Rheumatology Care: What We Know, What We Need to Learn, and What Its Limitations Are. Arthritis Care & Research 2025 View
  13. Joseph S, Bhardwaj A, Skariah J, Aggarwal I, Shah V, Harris R. Effects of education level on natural language processing in cardiovascular health communication. Frontiers in Public Health 2025;13 View
  14. Liu K, Cheng L, Wang W, Wu R, Li C, Yao K, Ge J. Cross-sectional comparative evaluation of us- and china-developed large language models for bilingual coronary heart disease patient education. Intelligent Medicine 2025 View
  15. Valcheff K, Pennington D, Keaton S, Carter K. Integrating the Essentials Core Competencies Related to Health Literacy Into Undergraduate Curriculum: Tapping Traditional and Emerging Education Strategies. Public Health Nursing 2025 View

Books/Policy Documents

  1. Lin S. Navigating Health Information in the Age of Artificial Intelligence. View