Kianian Reza, Sun Deyu, Rojas-Carabali William, Agrawal Rupesh, Tsui Edmund
Stein Eye Institute, Department of Ophthalmology, David Geffen School of Medicine, Los Angeles, CA, United States.
Nanyang Technological University, Lee Kong Chian School of Medicine, Singapore, Singapore.
J Med Internet Res. 2024 Dec 24;26:e59843. doi: 10.2196/59843.
Adequate health literacy has been shown to be important for the general health of a population. To address this, it is recommended that patient-targeted medical information is written at a sixth-grade reading level. To make well-informed decisions about their health, patients may want to interact directly with peer-reviewed open access scientific articles. However, studies have shown that such text is often written with highly complex language above the levels that can be comprehended by the general population. Previously, we have published on the use of large language models (LLMs) in easing the readability of patient-targeted health information on the internet. In this study, we continue to explore the advantages of LLMs in patient education.
This study aimed to explore the use of LLMs, specifically ChatGPT (OpenAI), to enhance the readability of peer-reviewed scientific articles in the field of ophthalmology.
A total of 12 open access, peer-reviewed papers published by the senior authors of this study (ET and RA) were selected. Readability was assessed using the Flesch-Kincaid Grade Level and Simple Measure of Gobbledygook tests. ChatGPT 4.0 was asked "I will give you the text of a peer-reviewed scientific paper. Considering that the recommended readability of the text is 6th grade, can you simplify the following text so that a layperson reading this text can fully comprehend it? - Insert Manuscript Text -". Appropriateness was evaluated by the 2 uveitis-trained ophthalmologists. Statistical analysis was performed in Microsoft Excel.
ChatGPT significantly lowered the readability and length of the selected papers from 15th to 7th grade (P<.001) while generating responses that were deemed appropriate by expert ophthalmologists.
LLMs show promise in improving health literacy by enhancing the accessibility of peer-reviewed scientific articles and allowing the general population to interact directly with medical literature.
充足的健康素养已被证明对人群的总体健康很重要。为解决这一问题，建议以六年级阅读水平编写针对患者的医学信息。为了对自身健康做出明智的决策，患者可能希望直接与经过同行评审的开放获取科学文章进行互动。然而，研究表明，此类文本的语言往往高度复杂，超出了普通人群的理解水平。此前，我们已发表关于使用大语言模型（LLMs）来提高互联网上针对患者的健康信息可读性的文章。在本研究中，我们继续探索大语言模型在患者教育方面的优势。
本研究旨在探索使用大语言模型，特别是ChatGPT（OpenAI），来提高眼科领域经过同行评审的科学文章的可读性。
总共选择了12篇由本研究的资深作者（ET和RA）发表的开放获取、经过同行评审的论文。使用弗莱施-金凯德年级水平和晦涩难懂度简易测量测试来评估可读性。向ChatGPT 4.0提问：“我将给你一篇经过同行评审的科学论文的文本。考虑到文本推荐的可读性为六年级，你能简化以下文本，以便外行阅读此文本时能完全理解吗？-插入论文文本-”。由2名接受过葡萄膜炎培训的眼科医生评估其适当性。在Microsoft Excel中进行统计分析。
ChatGPT显著降低了所选论文的可读性和长度，从15年级降至7年级（P<.001），同时生成的回复被眼科专家认为是适当的。
大语言模型在通过提高经过同行评审的科学文章的可及性并让普通人群直接与医学文献互动来提高健康素养方面显示出前景。
