Table 1_Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.docx

Most examined general-purpose LLMs (n = 267, 93.4%). Studies were concentrated in the United States and China and primarily examined text-based chatbots. Noncommunicable or chronic diseases and general health information were the most common health topics.

Ten health-related purposes were identified across four stakeholder groups and two umbrella categories. Public-facing applications involved the general public or patients and encompassed four purposes: (1) seeking health information, (2) symptom assessment and self-care management, (3) emotional support, and (4) preventive and transitional care support. Professional and organizational applications involved health professionals, health researchers and students, and health institutions, and encompassed six purposes: (5) clinical decision support, (6) improving administrative efficiency, (7) supporting patient interaction and doctor–patient communication, (8) enhancing continuing education, (9) facilitating health research, and (10) institutional workflow support and care navigation.</p>Conclusion<p>This review provides a stakeholder–purpose mapping of AI chatbot applications and evaluations in health care.

The evidence base is concentrated in text-based, lower-acuity, and information-oriented contexts and derives primarily from output evaluations and self-reported perceptions or use. Key gaps concern institutional integration and governance, higher-stakes and longitudinal contexts, and evidence across populations, languages, and interaction modalities.</p>