{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T02:24:00Z","timestamp":1793327040031,"version":"4.5.0"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Generative artificial intelligence chatbots are increasingly used as sources of consumer health information. Although their performance has been examined in several medical conditions, evidence specific to hand, foot, and mouth disease (HFMD) remains limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To compare the safety, accuracy, empathy, information quality, and readability of HFMD-related responses generated by five publicly accessible chatbots.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In this exploratory cross-sectional study, 20 researcher-developed English-language prompts were constructed from authoritative public-health sources, Google Trends topic mapping, and caregiver-informed wording refinement. ChatGPT-4o, Gemini 2.5 Pro, Copilot, Doubao, and DeepSeek-V3.2-Exp were evaluated between April 2 and April 5, 2026. Five trained reviewers independently assessed responses against predefined reference standards using safety and accuracy criteria, an empathy scale, DISCERN, EQIP, the Global Quality Score, and JAMA benchmarks. Six formula-based readability indices were calculated. Paired comparisons used Friedman and Cochran\n                      <jats:italic>Q<\/jats:italic>\n                      tests, with prespecified\n                      <jats:italic>post-hoc<\/jats:italic>\n                      procedures and Benjamini-Hochberg correction.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Unsafe-response rates ranged from 5.0 to 15.0%, with no statistically significant difference detected among chatbots (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.797). No statistically significant inter-model differences were detected for accuracy, empathy, DISCERN, EQIP, JAMA, or Global Quality Score in the 20-prompt set; because the study was exploratory and was not powered to establish equivalence, these findings do not demonstrate comparable or interchangeable performance. All six readability indices differed significantly among chatbots (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.030 to &amp;lt;0.001). ChatGPT and Doubao generally produced lower estimated grade-level complexity than Gemini and DeepSeek. Ten potentially unsafe or misleading responses were identified, mainly involving overgeneralization of EV71 vaccine protection, hand-hygiene qualification, and disinfection advice.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Across a limited set of standardized English-language prompts, the five chatbots often generated coherent HFMD information, but occasional safety-relevant inaccuracies and readability barriers remained. These systems may support general information seeking, but their responses require cautious interpretation and should not replace individualized professional advice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1924162","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T05:37:27Z","timestamp":1786426647000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluation of generative AI-driven chatbots as sources of consumer health information on hand, foot, and mouth disease: a cross-sectional comparative study of safety, accuracy, information quality, readability, and empathy"],"prefix":"10.3389","volume":"14","author":[{"given":"Zhaole","family":"Gong","sequence":"first","affiliation":[{"name":"Department of Pediatrics, Mudanjiang Second People\u2019s Hospital","place":["Mudanjiang, Heilongjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Na","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Mudanjiang Second People\u2019s Hospital","place":["Mudanjiang, Heilongjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Mudanjiang Second People\u2019s Hospital","place":["Mudanjiang, Heilongjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoya","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Mudanjiang Second People\u2019s Hospital","place":["Mudanjiang, Heilongjiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojie","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Renmin Hospital of Wuhan University","place":["Wuhan, Hubei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,11]]},"reference":[{"key":"ref1","volume-title":"About Hand, Foot, and Mouth Disease","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"193","DOI":"10.3390\/v16020193","article-title":"A review of enterovirus-associated hand-foot and mouth disease","volume":"16","author":"Huang","year":"2024","journal-title":"Viruses"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"100370","DOI":"10.1016\/j.lanwpc.2021.100370","article-title":"Changing epidemiology of hand, foot, and mouth disease in China, 2013-2019: a population-based study","volume":"20","author":"Hong","year":"2022","journal-title":"Lancet Reg Health West Pac"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"e000442","DOI":"10.1136\/bmjgh-2017-000442","article-title":"Severity and burden of hand, foot and mouth disease in Asia: a modelling study","volume":"3","author":"Koh","year":"2018","journal-title":"BMJ Global Health"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s12929-023-00908-4","article-title":"Current status of hand-foot-and-mouth disease","volume":"30","author":"Zhu","year":"2023","journal-title":"J Biomed Sci"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1016\/S1474-4422(10)70209-X","article-title":"Clinical features, diagnosis, and management of enterovirus 71","volume":"9","author":"Ooi","year":"2010","journal-title":"Lancet Neurol"},{"key":"ref7","volume-title":"Hand, Foot & Mouth Disease: Symptoms, Treatment & Prevention","year":"2025"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"e55372","DOI":"10.2196\/55372","article-title":"Parenting information on social media: systematic literature review","volume":"7","author":"Mertens","year":"2024","journal-title":"JMIR Pediatr Parent"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","article-title":"Large language models in medicine","volume":"29","author":"Thirunavukarasu","year":"2023","journal-title":"Nat Med"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"210","DOI":"10.7326\/M23-2772","article-title":"Large language models in medicine: the potentials and pitfalls: a narrative review","volume":"177","author":"Omiye","year":"2024","journal-title":"Ann Intern Med"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1038\/s41586-023-06291-2","article-title":"Large language models encode clinical knowledge","volume":"620","author":"Singhal","year":"2023","journal-title":"Nature"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1001\/jamainternmed.2023.1838","article-title":"Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum","volume":"183","author":"Ayers","year":"2023","journal-title":"JAMA Intern Med"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"e2457879","DOI":"10.1001\/jamanetworkopen.2024.57879","article-title":"Large language models for chatbot health advice studies: a systematic review","volume":"8","author":"Huo","year":"2025","journal-title":"JAMA Netw Open"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"104620","DOI":"10.1016\/j.jbi.2024.104620","article-title":"Evaluation of ChatGPT-generated medical responses: a systematic review and meta-analysis","volume":"151","author":"Wei","year":"2024","journal-title":"J Biomed Inform"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"235","DOI":"10.4274\/tjd.galenos.2025.06977","article-title":"Evaluation of the accuracy, reliability, quality, and readability of artificial intelligence chatbots-generated responses to acne-related questions","volume":"19","author":"Bostan","year":"2025","journal-title":"Turk J Dermatol"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"1278","DOI":"10.3390\/healthcare14101278","article-title":"Can artificial intelligence support patient education in scabies? A comparative analysis of large language model responses","volume":"14","author":"Ucar","year":"2026","journal-title":"Healthcare (Basel)"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"e001632","DOI":"10.1136\/bmjmed-2025-001632","article-title":"Reporting guideline for chatbot health advice studies: the Chatbot assessment reporting tool (CHART) statement","volume":"4","year":"2025","journal-title":"BMJ Med"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"e083305","DOI":"10.1136\/bmj-2024-083305","article-title":"Reporting guidelines for chatbot health advice studies: explanation and elaboration for the Chatbot assessment reporting tool (CHART)","volume":"390","author":"Collaborative","year":"2025","journal-title":"BMJ"},{"key":"ref19","volume-title":"A Guide to Clinical Management and Public Health Response for Hand, Foot and Mouth Disease","year":"2011"},{"key":"ref20","volume-title":"As the High Incidence Season for Hand, Foot, and Mouth Disease Approaches, China CDC Reminds the Public to Strengthen Prevention","year":"2024"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"e13439","DOI":"10.2196\/13439","article-title":"Google trends in infodemiology and infoveillance: methodology framework","volume":"5","author":"Mavragani","year":"2019","journal-title":"JMIR Public Health Surveill"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1038\/s41746-026-02428-5","article-title":"Large language models provide unsafe answers to patient-posed medical questions","volume":"9","author":"Draelos","year":"2026","journal-title":"NPJ Digit"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1136\/jech.53.2.105","article-title":"DISCERN: an instrument for judging the quality of written consumer health information on treatment choices","volume":"53","author":"Charnock","year":"1999","journal-title":"J Epidemiol Community Health"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1111\/j.1369-7625.2004.00273.x","article-title":"Ensuring quality information for patients: development and preliminary validation of a new instrument to improve the quality of written health care information","volume":"7","author":"Moult","year":"2004","journal-title":"Health Expect"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"2070","DOI":"10.1111\/j.1572-0241.2007.01325.x","article-title":"A systematic review of patient inflammatory bowel disease information resources on the world wide web","volume":"102","author":"Bernard","year":"2007","journal-title":"Am J Gastroenterol"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"1244","DOI":"10.1001\/jama.1997.03540390074039","article-title":"Assessing, controlling, and assuring the quality of medical information on the internet: caveant lector et viewor-let the reader and viewer beware","volume":"277","author":"Silberg","year":"1997","journal-title":"JAMA"},{"key":"ref27","volume-title":"Automated Readability Index. AMRL-TR-66-220","author":"Smith","year":"1967"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1037\/h0057532","article-title":"A new readability yardstick","volume":"32","author":"Flesch","year":"1948","journal-title":"J Appl Psychol"},{"key":"ref29","volume-title":"Derivation of New Readability Formulas: Automated Readability Index, Fog Count and Flesch Reading Ease Formula for Navy Enlisted Personnel. Research Branch Report 8\u201375","author":"Kincaid","year":"1975"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1037\/h0076540","article-title":"A computer readability formula designed for machine scoring","volume":"60","author":"Coleman","year":"1975","journal-title":"J Appl Psychol"},{"key":"ref31","first-page":"639","article-title":"SMOG grading: a new readability formula","volume":"12","author":"McLaughlin","year":"1969","journal-title":"J Read"},{"key":"ref32","volume-title":"Health Literacy: A Manual for Clinicians","author":"Weiss","year":"2003"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1037\/h0031619","article-title":"Measuring nominal scale agreement among many raters","volume":"76","author":"Fleiss","year":"1971","journal-title":"Psychol Bull"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1037\/0033-2909.86.2.420","article-title":"Intraclass correlations: uses in assessing rater reliability","volume":"86","author":"Shrout","year":"1979","journal-title":"Psychol Bull"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","article-title":"The use of ranks to avoid the assumption of normality implicit in the analysis of variance","volume":"32","author":"Friedman","year":"1937","journal-title":"J Am Stat Assoc"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"80","DOI":"10.2307\/3001968","article-title":"Individual comparisons by ranking methods","volume":"1","author":"Wilcoxon","year":"1945","journal-title":"Biom Bull"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J R Stat Soc B Stat Methodol"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"1712","DOI":"10.1038\/s41598-024-83575-1","article-title":"Comparison of the performances between ChatGPT and Gemini in answering questions on viral hepatitis","volume":"15","author":"Sahin Ozdemir","year":"2025","journal-title":"Sci Rep"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1186\/s12879-025-12022-x","article-title":"Comparison of the accuracy and reliability of ChatGPT-4o and Gemini in answering HIV-related questions","volume":"25","author":"Tarhan","year":"2025","journal-title":"BMC Infect Dis"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"1201","DOI":"10.1056\/NEJMra2302038","article-title":"Artificial intelligence and machine learning in clinical medicine, 2023","volume":"388","author":"Haug","year":"2023","journal-title":"N Engl J Med"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"e69955","DOI":"10.2196\/69955","article-title":"Enhancing the readability of online patient education materials using artificial intelligence","volume":"27","author":"Will","year":"2025","journal-title":"J Med Internet Res"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1093\/bjd\/ljae377","article-title":"Do large language model chatbots perform better than established patient information resources? A longitudinal evaluation in melanoma information","volume":"192","author":"Kamminga","year":"2025","journal-title":"Br J Dermatol"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A guideline of selecting and reporting intraclass correlation coefficients for reliability research","volume":"15","author":"Koo","year":"2016","journal-title":"J Chiropr Med"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1038\/s41746-024-01157-x","article-title":"The ethics of ChatGPT in medicine and healthcare: a systematic review on large language models","volume":"7","author":"Haltaufderheide","year":"2024","journal-title":"NPJ Digit Med."},{"key":"ref45","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1038\/s41746-023-00873-0","article-title":"The imperative for regulatory oversight of large language models, or generative AI, in healthcare","volume":"6","author":"Mesko","year":"2023","journal-title":"NPJ Digit"}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1924162\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T05:37:31Z","timestamp":1786426651000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1924162\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,11]]},"references-count":45,"alternative-id":["10.3389\/fpubh.2026.1924162"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2026.1924162","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,11]]},"article-number":"1924162"}}