ArticleProceedings (Baylor University. Medical Center)2025
Evolution of patient education materials from large-language artificial intelligence models on complex regional pain syndrome: are patients learning?
Article in Proceedings (Baylor University. Medical Center), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Quality of ChatGPT-Generated Responses to Common Patient Questions About Peripheral Nerve Stimulation: A Cross-Sectional Study.Clinics and practice · 2026Article
- The rapid evolution of AI in patient education-promise, peril, and the path forward.Proceedings (Baylor University. Medical Center) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study assessed the comprehensiveness and readability of medical information about complex regional pain syndrome provided by ChatGPT, an artificial intelligence (AI) chatbot, and Google using standardized scoring systems. Design: A Google search was conducted using the term "complex regional pain syndrome," and the first 10 frequently asked questions (FAQs) and answers generated were recorded. ChatGPT was presented these FAQs generated by Google, and its responses were evaluated alongside Google's answers using multiple metrics. ChatGPT was then asked to generate its own set of 10 FAQs and answers. Results: ChatGPT's answers were significantly longer than Google's in response to both independently generated questions (330.0 ± 51.3 words, Conclusions: Our findings suggest that ChatGPT is a promising tool for patient education regarding complex regional pain syndrome based on its ability to generate a variety of question topics with responses from credible sources. That said, challenges such as readability and ethical considerations must be addressed prior to its widespread use for health information.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.