TY - JOUR AU - Ayo-Ajibola, Oluwatobiloba AU - Davis, Ryan J AU - Lin, Matthew E AU - Riddell, Jeffrey AU - Kravitz, Richard L PY - 2024 DA - 2024/8/14 TI - Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study JO - J Med Internet Res SP - e55138 VL - 26 KW - artificial intelligence KW - ChatGPT KW - health information KW - patient information-seeking KW - online health information KW - health literacy KW - ResearchMatch KW - users KW - diagnosis KW - decision-making KW - cross-sectional KW - survey KW - surveys KW - adoption KW - utilization KW - AI KW - less-educated KW - poor health KW - worse health KW - experience KW - experiences KW - user KW - non user KW - non users KW - AI-generated KW - implication KW - implications KW - medical practice KW - medical practices KW - public health KW - descriptive statistics KW - t test KW - t tests KW - chi-square test KW - chi-square tests KW - health-seeking behavior KW - health-seeking behaviors KW - patient-provider KW - interaction KW - interactions KW - patient KW - patients AB - Background: OpenAI’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. Objective: This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform. Methods: In 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. Results: Of 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). Conclusions: This 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. SN - 1438-8871 UR - https://www.jmir.org/2024/1/e55138 UR - https://doi.org/10.2196/55138 DO - 10.2196/55138 ID - info:doi/10.2196/55138 ER -