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Artificial intelligence meets HIV education: Comparing three large language models on accuracy, readability, and

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Claude 3.7 Sonnet excels in accuracy and reliability for HIV information, outperforming ChatGPT-4o and Gemini Advanced 2.0 Flash. ChatGPT-4o offers better readability, making model selection crucial for effective HIV patient education.

Keywords:
AIDSHuman immunodeficiency virusartificial intelligencepatient education as topic

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Medical Informatics
  • Public Health Communication

Background:

  • Growing concerns regarding the accuracy and reliability of Large Language Models (LLMs) for patient education.
  • The critical need for dependable information sources in Human Immunodeficiency Virus (HIV) patient care.
  • Assessing the suitability of current LLMs for disseminating accurate HIV-related knowledge.

Purpose of the Study:

  • To compare the performance of three leading LLMs in answering common HIV-related queries.
  • To evaluate LLM accuracy, readability, and reliability for HIV patient education.
  • To guide the selection of appropriate LLMs for healthcare information dissemination.

Main Methods:

  • Three LLMs (Claude 3.7 Sonnet, ChatGPT-4o, Gemini Advanced 2.0 Flash) answered 63 HIV questions.
  • Accuracy assessed using a 5-point Likert scale.
  • Readability evaluated with Flesch-Kincaid, Gunning Fog, and Coleman-Liau indices.
  • Reliability measured by DISCERN and EQIP criteria.

Main Results:

  • Claude 3.7 Sonnet demonstrated superior accuracy (p < .001) and reliability (EQIP: p = .049) compared to other models.
  • ChatGPT-4o provided the most accessible content based on Flesch-Kincaid and Coleman-Liau indices.
  • Gemini Advanced 2.0 Flash generated more complex text and had lower reliability scores.

Conclusions:

  • Claude 3.7 Sonnet is recommended for its accuracy and reliability in HIV information.
  • ChatGPT-4o is a viable option when readability is prioritized.
  • Continuous evaluation of LLM performance, content quality, and cultural sensitivity is essential for effective HIV education.