{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T05:54:17Z","timestamp":1791179657311,"version":"4.1.0"},"reference-count":98,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:00:00Z","timestamp":1791158400000},"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. Digit. Health"],"abstract":"<jats:p>Two health chatbots can give the same clinically appropriate advice and still constitute different interventions: one stops at a clinician referral, the other places an affiliated booking one click away. In this Hypothesis and Theory article we argue that the appropriate unit of health-AI evaluation is therefore not the model output alone, but the configured answer system \u2014 the large language model (LLM) together with source selection, retrieval, interface, action routing and downstream data return. We call this organizationally configured mode of mediation synthetic gatekeeping. Its necessary core comprises source selection and generative synthesis, with personalization and action routing as extending dimensions; its observable manifestations are content and pathway traces, and its proposed mechanism is infrastructural steering. Content parity does not guarantee pathway parity: two systems can name the same options while making only one easily actionable. Organizational position, revenue architecture and integration depth are treated as exposures that may shape these functions, not as elements of the construct, and owner-linked advantage is an empirical outcome to be demonstrated rather than assumed. Direct health evidence of owner- or revenue-linked steering remains sparse, and one comparative study found LLM answers less commercially biased than conventional search; the mechanisms nonetheless appear in adjacent domains, and health outputs are configurable at deployment level. We advance three core propositions \u2014 organizational alignment (P1), pathway asymmetry (P2) and behavioural mediation (P4) \u2014 with one conditional moderator hypothesis on conversion-linked funding (P3) and a measurement corollary on surface\u2013pathway divergence (M1), each stated with its weakening condition. The framework yields a practical audit model based on configuration anchoring, paired content\u2013pathway comparison, organizational disclosure and proportionate governance triggers. The unit of evaluation should move from the model output to the configured answer system in which information becomes action.<\/jats:p>","DOI":"10.3389\/fdgth.2026.1976313","type":"journal-article","created":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T05:33:06Z","timestamp":1791178386000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Synthetic gatekeeping in health chatbots: configured answer systems as the unit of AI evaluation and governance for medical information"],"prefix":"10.3389","volume":"8","author":[{"given":"Simona","family":"W\u00f3jcik","sequence":"first","affiliation":[{"name":"Department of Science, LUX MED Sp. z o.o.","place":["Warsaw, Poland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justyna","family":"Domienik-Kar\u0142owicz","sequence":"additional","affiliation":[{"name":"Warsaw School of Medical Sciences (Wy\u017csza Szko\u0142a Nauk Medycznych, WSNM)","place":["Warsaw, Poland"]},{"name":"Department of Internal Medicine and Cardiology, Medical University of Warsaw","place":["Warsaw, Poland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Rulkiewicz","sequence":"additional","affiliation":[{"name":"LUX MED Sp. z o.o.","place":["Warsaw, Poland"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,5]]},"reference":[{"key":"B1","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":"B2","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.5603\/cj.97515","article-title":"Beyond ChatGPT: what does GPT-4 add to healthcare? 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