Utilization of Artificial Intelligence in the Creation of Patient Information on Laryngology Topics

Abstract

OBJECTIVE: To evaluate and compare the readability and quality of patient information generated by Chat-Generative Pre-Trained Transformer-3.5 (ChatGPT) and the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) using validated instruments including Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease, DISCERN, and Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P). METHODS: ENTHealth.org and ChatGPT-3.5 were queried for patient information on laryngology topics. ChatGPT-3.5 was queried twice for a given topic to evaluate for reliability. This generated three de-identified text documents for each topic: one from AAO-HNS and two from ChatGPT (ChatGPT Output 1, ChatGPT Output 2). Grade level and reading ease were compared between the three sources using a one-way analysis of variance and Tukey's post hoc test. Independent t-tests were used to compare DISCERN and PEMAT understandability and actionability scores between AAO-HNS and ChatGPT Output 1. RESULTS: Material generated from ChatGPT Output 1 and ChatGPT Output 2 were at least two reading grade levels higher than that of material from AAO-HNS (p < 0.001). Regarding reading ease, ChatGPT Output 1 and ChatGPT Output 2 documents had significantly lower mean scores compared to AAO-HNS (p < 0.001). Moreover, ChatGPT Output 1 material on vocal cord paralysis had a lower PEMAT-P understandability compared to that of AAO-HNS material (p > 0.05). CONCLUSION: Patient information on the ENTHealth.org website for select laryngology topics was, on average, of a lower grade level and higher reading ease compared to that produced by ChatGPT, but interestingly with largely no difference in the quality of information provided. LEVEL OF EVIDENCE: NA Laryngoscope, 135:1295-1300, 2025.

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