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ChatGPT-5.4 in health education: inter-generation stability and persistent readability challenges
Xingmin Han1, Dan Li2, Ruirui Xing1
1Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia.
Frontiers in Public Health
|July 16, 2026
Summary
Generative AI like ChatGPT-5.4 shows moderate stability in creating spinal surgery patient education materials. However, readability remains a challenge, requiring clinician review for patient use.
Area of Science:
- Artificial Intelligence in Healthcare
- Medical Education Technology
Background:
- Generative AI offers potential for creating patient education materials (PEMs).
- Previous studies noted limitations in AI-generated PEMs regarding readability and stability.
- ChatGPT-5.4 presents an opportunity to assess newer AI model performance.
Purpose of the Study:
- Evaluate ChatGPT-5.4's inter-generation stability and usability for spinal surgery PEMs.
- Assess the quality and readability of AI-generated patient education content.
- Determine the consistency of core medical information across multiple AI responses.
Main Methods:
- ChatGPT-5.4 generated five responses for common spinal surgery questions.
- Qualitative analysis assessed language, information depth, structure, and supplementary content.
- Readability was measured using Flesch-Kincaid and SMOG indices.
- Content quality was rated by independent reviewers using the DISCERN tool.
Main Results:
- Core medical information was consistent across responses, with variations in tone and detail.
- Readability scores indicated challenging levels (FKGL 9.12-13.34, SMOG 8.90-11.84).
- Average DISCERN scores suggested "average" quality (43.2-44.9).
- ChatGPT-5.4 demonstrated moderate-to-high inter-generation stability.
Conclusions:
- ChatGPT-5.4 shows potential for generating stable spinal surgery PEMs.
- Readability and lack of verifiable references pose limitations for patient accessibility.
- Clinician review and plain-language optimization are necessary before patient use.
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