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Related Experiment Video

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Large Language Models: Pioneering New Educational Frontiers in Childhood Myopia.

Mohammad Delsoz1, Amr Hassan2, Amin Nabavi1

  • 1Hamilton Eye Institute, Department of Ophthalmology, University of Tennessee Health Science Center, 930 Madison Ave., Suite 471, Memphis, TN, 38163, USA.

Ophthalmology and Therapy
|April 21, 2025
PubMed
Summary

ChatGPT-4o (o1 Preview) shows promise in creating high-quality patient education materials for childhood myopia, improving readability and accuracy. It also enhances existing online materials, making them more understandable and actionable for patients.

Keywords:
Childhood myopiaLarge language modelsPatient education materials

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Medical Communication
  • Ophthalmology

Background:

  • Patient education materials (PEMs) are crucial for managing childhood myopia.
  • Evaluating the efficacy of large language models (LLMs) in generating and refining these materials is essential.

Purpose of the Study:

  • To assess the performance of ChatGPT-3.5, ChatGPT-4o (o1 Preview), and Google Gemini in creating and improving patient education materials on childhood myopia.
  • To evaluate the readability and quality of LLM-generated content using established metrics.

Main Methods:

  • Three prompts were used to generate and revise PEMs for childhood myopia.
  • LLM outputs were evaluated for quality (DISCERN), readability (FKGL, SMOG), understandability/actionability (PEMAT), and accuracy.
  • Statistical analysis was performed to compare model performance.

Main Results:

  • ChatGPT-4o (o1 Preview) and ChatGPT-3.5 produced good-quality PEMs, though quality slightly decreased with specific readability constraints.
  • All models generated understandable materials, but actionability remained below the target threshold.
  • Readability significantly improved with targeted prompts, with ChatGPT-4o (o1 Preview) showing the greatest gains.

Conclusions:

  • ChatGPT-4o (o1 Preview) is a capable tool for generating accurate, high-quality, and understandable patient education materials for childhood myopia.
  • LLMs can effectively improve the readability and quality of existing online patient education resources.