JMIR Publications

ABSTRACT

Background:

Mpox outbreaks since 2022 have emphasized the importance of accessible health education materials. However, many Japanese online resources on mpox are difficult to understand, creating barriers for public health communication. Recent advances in artificial intelligence (AI), such as ChatGPT-4o, show promise in generating more comprehensible and actionable health education content.

Objective:

To evaluate the comprehensibility, actionability, and readability of Japanese health education materials on mpox, compared with texts generated by ChatGPT-4o.

Methods:

A cross-sectional study was conducted using systematic quantitative content analysis. A total of 119 publicly available Japanese health education materials on mpox were compared with 30 texts generated by ChatGPT-4.0. Websites containing videos, social media posts, academic papers, and non-Japanese language content were excluded. ChatGPT-4.0 generated texts using the same prompt, repeated 10 times to account for variations. The Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) was used to assess understandability and actionability, while the Japanese Readability Measurement System (jReadability) was used to evaluate readability. The Journal of the American Medical Association (JAMA) benchmark criteria were applied to evaluate the quality of the materials.

Results:

A total of 119 Japanese mpox-related health education webpages and 30 ChatGPT-4.0-generated texts were analyzed. AI-generated texts significantly outperformed webpages in understandability, with 80% scoring ≥70% in PEMAT-P (P < .001). Readability scores were also higher for AI texts (mean 2.9 ± 0.4) than for webpages (mean 2.4 ± 1.0; P = .009). However, webpages included more visual aids and actionable guidance, such as practical instructions, which were largely absent in AI-generated content. Government agencies authored 75.6% of the webpages, but only 26.1% included proper attribution. Most webpages (98.3%) disclosed sponsorship and ownership.

Conclusions:

AI-generated texts were easier to understand and read than traditional web-based materials. However, web-based texts provided more visual aids and practical guidance. Combining AI-generated texts with traditional web-based materials may enhance the effectiveness of health education materials and improve accessibility to a broader audience. Further research is needed to explore the integration of AI-generated content into public health communication strategies and policies to optimize information delivery during health crises like the mpox outbreak.