TY  - JOUR
AU  - Kianian, Reza
AU  - Sun, Deyu
AU  - Rojas-Carabali, William
AU  - Agrawal, Rupesh
AU  - Tsui, Edmund
PY  - 2024
DA  - 2024/12/24
TI  - Large Language Models May Help Patients Understand Peer-Reviewed Scientific Articles About Ophthalmology: Development and Usability Study
JO  - J Med Internet Res
SP  - e59843
VL  - 26
KW  - uveitis
KW  - artificial intelligence
KW  - ChatGPT
KW  - readability
KW  - peer review
KW  - large language models
KW  - LLMs
KW  - health literacy
KW  - patient education
KW  - medical information
KW  - ophthalmology
AB  - Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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. 
SN  - 1438-8871
UR  - https://www.jmir.org/2024/1/e59843
UR  - https://doi.org/10.2196/59843
DO  - 10.2196/59843
ID  - info:doi/10.2196/59843
ER  -