ArticleJournal of medical Internet research2024
Characterizing the Adoption and Experiences of Users of Artificial Intelligence-Generated Health Information in the United States: Cross-Sectional Questionnaire Study.
Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Receipt of Medicines Information From the Internet and Other Information Sources Among Adult Medicine Users in Developed Economies, 2010-2025: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: Randomized Controlled Experimental Study.Journal of medical Internet research · 2026Trial
- MicrotiaGPT: Appraisal of Microtia Care Recommendations From an Artificially Intelligent Chatbot.Laryngoscope investigative otolaryngology · 2026Article
- Validating LLM judges for automated oversight of patient communication.medRxiv : the preprint server for health sciences · 2026Article
- CPS-Net (Collaborating Physicians in Silico Network): A Decentralized Multi-Agent Transformer Framework for Specialty-Aware Disease Prediction.Journal of medical systems · 2026Article
- Consumer and Patient Health Information Seeking With Generative AI Tools: Scoping Review of Facilitators and Barriers.Journal of medical Internet research · 2026Article
- Generative Artificial Intelligence (AI)-Assisted Self-Diagnosis and the Patient-Physician Relationship: Mixed Methods Study of Calibration, Participation, and Trust.Journal of medical Internet research · 2026Article
- Ability of Large Language Models to Answer Patients' Questions and Generate Educational Materials for Uncommon Retinal Conditions.Journal of vitreoretinal diseases · 2026Article
- Diagnostic accuracy of ChatGPT-5 in evaluating root canal treatment and periapical pathosis on periapical radiographs.Restorative dentistry & endodontics · 2026Article
- Accuracy of Artificial Intelligence chatbots in responding to myopia-related queries from parents and patients.Indian journal of ophthalmology · 2026Article
- Understanding of Preeclampsia Risk Factors in Large Language Models Compared with a Validated Competing-Risks Model.Diagnostics (Basel, Switzerland) · 2026Article
- Factors Shaping Trust and Satisfaction With AI Medical Chatbots: A Mixed Methods Vignette Survey of Caregivers Seeking Guidance on Pediatric Infectious Diseases.Journal of medical Internet research · 2026Article
- Conversational Artificial Intelligence as a Source of Oral Health Information: A Cross-Sectional Study in a Romanian Population.Dentistry journal · 2026Article
- Article
- Personal Health Large Language Models and the Negotiation of Medical Authority in Clinical Care: Opportunities, Risks, and Governance.Journal of medical Internet research · 2026Article
- Navigating Diabetes Management in the Digital Era: Scoping Review of Online Health Information-Seeking Behavior.Journal of medical Internet research · 2026Article
- Who bears liability when AI gives bad prescribing advice.NPJ digital medicine · 2026Article
- Patient Cognitive Bias in Large Language Model-Supported Health Consultations: Simulation-Based Comparative Study.Journal of medical Internet research · 2026Article
- Patient-Provider Discussions About Online Health Information in the Health Information National Trends Survey.Health education & behavior : the official publication of the Society for Public Health Education · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOpenAI's ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what.
objectiveThis study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform.
methodsIn this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers.
resultsOf 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349).
conclusionsThis study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.