JMIR Publications

ABSTRACT

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 6th 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 LLMs in easing the readability of patient-targeted health information on the internet. No studies, however, have looked at its efficacy in making scientific articles more accessible to the general population.

Objective:

To explore the utility of large language models (LLMs), specifically ChatGPT, to enhance the readability of peer-reviewed scientific articles in the field of Ophthalmology.

Methods:

Twelve open-access, peer-reviewed manuscripts published by the senior authors of this study (E.T. and R.A.) 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 two uveitis-trained ophthalmologists. Statistical analysis was performed in Microsoft Excel.

Results:

ChatGPT significantly lowered the readability and length of the selected manuscripts from 15th to 7th grade (p<0.0001) while generating responses that kept the original meaning of the manuscripts and were deemed appropriate.

Conclusions:

LLMs show promise in improving health literacy through enhancing the accessibility of peer-reviewed scientific articles and allowing the general population to interact directly with medical literature.