An Acceptance Criteria Framework for Determining the Implementation Fit of Custom Large Language Models in Public Health Interventions

Large language models (LLMs) are increasingly embedded in clinical and population health workflows, including conversational agents such as health chatbots. As chatbots evolve from rule-based approaches to hybrid and LLM-enabled designs, risks and concerns about deployment readiness shift. Unlike rule-based chatbots, LLM outputs can be unpredictable, error-prone, and difficult to validate with traditional evaluation methods. Public health teams integrating customized LLMs into interventions face

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ethics.ai (16 July 2026), “An Acceptance Criteria Framework for Determining the Implementation Fit of Custom Large Language Models in Public Health Interventions,” evidence record 11080, https://ethics.ai/record/11080 (originally published by JMIR (Journal of Medical Internet Research)).

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