Behavior Change Content and Implementation of Large Language Model–Driven Conversational Agents in Cardiometabolic Care: Scoping Review
Background: Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self-management, but their behavior change content, delivery mechanisms, and implementation transparency are poorly understood. Objective: This scoping review mapped behavior change techniques (BCTs) used in LLM-driven conversational agents for cardiometabolic prevention and management, described how these techniques are delivered across static, rule-b
Record details
Published: 15 July 2026
Source: JMIR (Journal of Medical Internet Research)
Category: Research
Topics: Agents & autonomy · Transparency
Retrieved: 16 July 2026
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How to cite this record
ethics.ai (15 July 2026), “Behavior Change Content and Implementation of Large Language Model–Driven Conversational Agents in Cardiometabolic Care: Scoping Review,” evidence record 10703, https://ethics.ai/record/10703 (originally published by JMIR (Journal of Medical Internet Research)).
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