Large Language Model-Generated Patient Education Materials in Pediatric Ophthalmology: A Scoping Review.

Authors

Abdullahi Abdiaziz Mohamed, Thomas Scott/S Armstrong, Ojas Srivastava, Edsel Ing, Travis Pollock, Carlos Solarte

Published in

Clinical ophthalmology (Auckland, N.Z.). Volume 20. Pages 635998. Epub Sep 30, 2026.

Abstract

Effective management of pediatric ophthalmic conditions such as myopia, amblyopia, and strabismus depend on caregivers understanding patient education materials (PEMs). However, many existing resources exceed recommended grade 8 reading levels. This review maps AI-generated PEMs in pediatric ophthalmology, summarizes reported outcomes across key educational domains, and identifies barriers and opportunities for clinical integration. Following PRISMA-ScR guidelines, a search of Ovid MEDLINE, Embase, and Scopus (January 2015-July 2025) identified studies evaluating LLM-generated PEMs in pediatric ophthalmology. Eligible studies evaluated artificial intelligence for pediatric ophthalmology patient education and reported at least one educational outcome. Data were extracted independently by two reviewers and synthesized descriptively. Twenty studies (2023-2025) evaluated 3286 AI-generated materials across 14 LLMs. Readability was assessed in 17 studies; 59% (37/63) of study-level LLM evaluations exceeded recommended 8th-grade reading levels. ChatGPT-4o evaluations were more often acceptable (52%) than ChatGPT-3.5 evaluations (18%), although these were not head-to-head comparisons. Median understandability (PEMAT-U) exceeded adequacy thresholds (≥70%). Professional society materials were more accurate and higher quality but significantly less readable. No included study explicitly classified outputs as hallucinations under its applied assessment framework; however, incomplete treatment-related content was common. Only two studies assessed patient or caregiver perspectives. LLM-generated PEMs in pediatric ophthalmology are generally understandable and accessible but often exceed readability standards and lack actionable guidance. While professional society materials remain more accurate, LLMs offer scalable tools for generating patient-centered resources. Integrating LLMs into clinician-supervised workflows and emphasizing co-designed, multimodal education strategies may enhance accessibility and clinical safety.

PMID:
42830931
Bibliographic data and abstract were imported from PubMed on 05 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.