aceInformation quality, understandability, actionability and readability of large language models for HIV health education: A cross-platform evaluation
Objectives: Large language models (LLMs) are increasingly used to generate health education materials, but their suitability for patient-facing human immunodeficiency virus (HIV) education remains insufficiently evaluated. We assessed the information quality, understandability, actionability, readability, text structure and source transparency of HIV patient education materials generated by six LLMs or artificial intelligence platforms. Methods: In this cross-sectional study, 100 common HIV patient education que…
Chatbot-generated HIV patient education varied widely across platforms and topics, with limited actionability and high readability demands, so it is not suited to serve as an independent patient information source.
The study did not assess direct factual accuracy, guideline concordance, hallucination or clinical safety, and each question was submitted only once in English.
Evidence
- Peer-reviewedHIV Medicine2026-10-18
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Truvace Impact Record TRV-2026-1874, v1: “Information quality, understandability, actionability and readability of large language models for HIV health education: A cross-platform evaluation.” Truvace, 2026-10-19. /record/TRV-2026-1874 (accessed at citation time). sha256 20446afe90aeb4ef…
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