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Utilizing Artificial Intelligence to Increase the Readability of Patient Education Materials in Pediatric
Andrew J Rothka1, F Jeffrey Lorenz2, Madison Hearn1
1Penn State College of Medicine, Hershey, PA, USA.
Abstract:
Objectives: To identify the reading levels of existing patient education materials in pediatric otolaryngology and to utilize natural language processing artificial intelligence (AI) to reduce the reading level of patient education materials. Methods: Patient education materials for pediatric conditions were identified from the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) website. Patient education materials about the same conditions, if available, were identified and selected from the websites of 7 children's hospitals. The readability of the patient materials was scored before and after using AI with the Flesch-Kincaid calculator. ChatGPT version 3.5 was used to convert the materials to a fifth-grade reading level. Results: On average, AAO-HNS pediatric education material was written at a 10.71 ± 0.71 grade level. After requesting the reduction of those materials to a fifth-grade reading level, ChatGPT converted the same materials to an average grade level of 7.9 ± 1.18 (P < .01). When comparing the published materials from AAO-HNS and the 7 institutions, the average grade level was 9.32 ± 1.82, and ChatGPT was able to reduce the average level to 7.68 ± 1.12 (P = .0598). Of the 7 children's hospitals, only 1 institution had an average grade level below the recommended sixth-grade level. Conclusions: Patient education materials in pediatric otolaryngology were consistently above recommended reading levels. In its current state, AI can reduce the reading levels of education materials. However, it did not possess the capability to reduce all materials to be below the recommended reading level.
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