Readability, Reliability, and Quality Analysis of Internet-Based Patient Education Materials and Large Language Models on Meniere's Disease

Importance Online patient education materials (PEMs) and large language model (LLM) outputs can provide critical health information for patients, yet their readability, quality, and reliability remain unclear for Meniere's disease.Objective To assess the readability, quality, and reliability of online PEMs and LLM-generated outputs on Meniere's disease.Design Cross-sectional study.Setting PEMs were identified from the first 40 Google Search results based on inclusion criteria. LLM outputs were extracted from unique interactions with ChatGPT and Google Gemini.Participants Thirty-one PEMs met inclusion criteria. LLM outputs were obtained from 3 unique interactions each with ChatGPT and Google Gemini.Intervention Readability was assessed using 5 validated formulas [Flesch Reading Ease (FRE), Flesch Kincaid Grade Level (FKGL), Gunning-Fog Index, Coleman-Liau Index, and Simple Measure of Gobbledygook Index]. Quality and reliability were assessed by 2 independent raters using the DISCERN tool.Main Outcome Measures Readability was assessed for adherence to the American Medical Association's (AMA) sixth-grade reading level guideline. Source reliability, as well as the completeness, accuracy, and clarity of treatment-related information, was evaluated using the DISCERN tool.Results The most common PEM source type was academic institutions (32.2%), while the majority of PEMs (61.3%) originated from the United States. The mean FRE score for PEMs corresponded to a 10th- to 12th-grade reading level, whereas ChatGPT and Google Gemini outputs were classified at post-graduate and college reading levels, respectively. Only 16.1% of PEMs met the AMA's sixth-grade readability recommendation using the FKGL readability index, and no LLM outputs achieved this standard. Overall DISCERN scores categorized PEMs and ChatGPT outputs as "poor quality," while Google Gemini outputs were rated "fair quality." No significant differences were found in readability or DISCERN scores across PEM source types. Additionally, no significant correlation was identified between PEM readability, quality, and reliability scores.Conclusions Online PEMs and LLM-generated outputs on Meniere's disease do not meet AMA readability standards and are generally of poor quality and reliability.Relevance Future PEMs should prioritize improved readability while maintaining high-quality, reliable information to better support patient decision-making for patients with Meniere's disease.