{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T05:19:49Z","timestamp":1793251189381,"version":"4.5.0"},"reference-count":32,"publisher":"American Medical Association (AMA)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Health care systems are increasingly considering large language model (LLM)\u2013based chatbots for vaccine communication, but evidence that they improve durable, behaviorally relevant outcomes beyond existing health materials is limited.<\/jats:p>\n <\/jats:sec>\n \n Objectives<\/jats:title>\n To examine whether brief, multiturn interactions with an LLM chatbot increase parental intention to vaccinate children against human papillomavirus (HPV) compared with no intervention and government public health materials and to assess whether any effects persist.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This randomized clinical trial was conducted online among individuals in the US, Canada, and the UK from March 3 to May 25, 2025, with follow-up at 15 and 45 days. Eligible participants were parents 18 years or older with at least 1 HPV vaccine\u2013eligible child (aged 11-17 years in the US and Canada and 12-17 years in the UK) who had not received HPV vaccination or whose vaccination status was unknown.<\/jats:p>\n <\/jats:sec>\n \n Interventions<\/jats:title>\n Participants were randomized to (1) no-message control, (2) government public health materials matched to country (minimum 3-minute exposure), or (3) a 3-minute interaction with an LLM chatbot (OpenAI\u2019s GPT-4o) prompted to encourage HPV vaccination using a default response style or a shorter conversational style.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The primary outcome was self-reported likelihood of vaccinating the child against HPV within 12 months (0- to 100-point scale, with 0 indicating extremely unlikely and 100 indicating extremely likely) measured immediately after intervention. Prespecified follow-ups included vaccination intent and self-reported vaccination at 15 and 45 days.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n A total of 1297 participants (mean [SD] age, 42.84 [6.93] years; 935 [72.1%] female) were randomized. Compared with no intervention, public health materials increased immediate vaccination intent (Cohen\n d<\/jats:italic>\n = 0.53; 95% CI, 0.36-0.70), as did the default chatbot (\n d<\/jats:italic>\n = 0.48; 95% CI, 0.30-0.65) and conversational chatbot (\n d<\/jats:italic>\n = 0.33; 95% CI, 0.17-0.49). At 45 days, neither chatbot increased intent relative to controls, whereas public health materials maintained modest effects. No intervention increased self-reported vaccination uptake.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n The findings of this randomized clinical trial suggest that well-designed public health messaging may match or exceed the impact of short chatbot conversations for HPV vaccine promotion.<\/jats:p>\n <\/jats:sec>\n \n Trial Registration<\/jats:title>\n \n ClinicalTrials.gov Identifier:\n NCT07132125<\/jats:ext-link>\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.16822","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:30:39Z","timestamp":1780932639000},"page":"e2616822","source":"Crossref","is-referenced-by-count":4,"title":["Large Language Model Chatbot Conversations vs Public Health Materials and Parental HPV Vaccination Intentions"],"prefix":"10.1001","volume":"9","author":[{"given":"Neil K. R.","family":"Sehgal","sequence":"first","affiliation":[{"name":"Computer and Information Science Department, University of Pennsylvania, Philadelphia"},{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sunny","family":"Rai","sequence":"additional","affiliation":[{"name":"Computer and Information Science Department, University of Pennsylvania, Philadelphia"},{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manuel","family":"Tonneau","sequence":"additional","affiliation":[{"name":"Oxford Internet Institute, University of Oxford, Oxford, UK"},{"name":"Development Impact Department, World Bank, Washington, DC"},{"name":"Department of Computer Science, New York University, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anish K.","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"},{"name":"Penn Medicine Center for Health Care Transformation and Innovation, University of Pennsylvania, Philadelphia"},{"name":"Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Cappella","sequence":"additional","affiliation":[{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"},{"name":"Annenberg School for Communication, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie L.","family":"Kornides","sequence":"additional","affiliation":[{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"},{"name":"Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lyle","family":"Ungar","sequence":"additional","affiliation":[{"name":"Computer and Information Science Department, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alison","family":"Buttenheim","sequence":"additional","affiliation":[{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"},{"name":"Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia"},{"name":"Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharath Chandra","family":"Guntuku","sequence":"additional","affiliation":[{"name":"Computer and Information Science Department, University of Pennsylvania, Philadelphia"},{"name":"Leonard Davis Institute of 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