Readability, understandability, and quality of online education materials and large language models for retrograde cricopharyngeal muscle dysfunction

Türe N., Tahir E., Enver N.

European Archives of Oto-Rhino-Laryngology, vol.1, no.1, pp.1-2, 2025 (SCI-Expanded)

Abstract

Abstract

Objective: This study aims to evaluate online patient education materials on retrograde cricopharyngeal dysfunction (RCPD) by comparing the readability, understandability, and quality of content generated by large language models (LLM).

Method: A web search in December 2024 evaluated 51 online resources and four LLMs (ChatGPT 4.0, Gemini 1.5 Flash, Perplexity GPT-3.5, DeepSeek-V2.5). Readability was analyzed using Readable.io, understandability actionability was assessed using PEMAT, and information quality was assessed using DISCERN.

Results: The average readability level of the online material and the LLM responses was at the 11th-12th grade level. The Flesch Reading Ease score was lowest for the LLMs, especially for the DeepSeek-V2.5 model (24.21). While PEMAT understandability scores were adequate for online (82%) and LLMs (79%), actionability was low across all groups (25-37%). DISCERN analyses showed that both sources of information were of limited quality in supporting treatment decisions.

Conclusion: This study revealed that both online and LLM-generated materials on RCPD exceeded the recommended readability levels. Although the materials demonstrated acceptable understandability, they exhibited low actionability and inadequate overall quality, emphasizing the need for more patient-centered digital health communication.

Keywords: Artificial intelligence; Deglutition disorders; Health literacy; Patient education; Readability.