ArticleFrontiers in public health2026
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.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: 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. Objective: To compare the safety, accuracy, empathy, information quality, and readability of HFMD-related responses generated by five publicly accessible chatbots. Methods: 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 Results: Unsafe-response rates ranged from 5.0 to 15.0%, with no statistically significant difference detected among chatbots ( Conclusion: 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.
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