ArticleCureus2023
ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications and Concerns of ChatGPT and Other Conversational Large Language Models in Health Care: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Utilization and prospects of artificial intelligence in the diagnosis, prediction, and treatment of erectile dysfunction.Sexual medicine · 2026Review
- Readability Analysis of Commonly Cited Patient-Reported Outcome Measures in the Orthopaedic Joint Literature.Arthroplasty today · 2026Article
- Feeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer.Journal of translational medicine · 2025Article
- Evaluating the Readability of Pediatric Neurocutaneous Syndromes-Related Patient Education Material Created by a Custom GPT With Retrieval Augmentation.JMIR dermatology · 2025Article
- Potential role of large language models and personalized medicine to innovate cardiac rehabilitation.World journal of clinical cases · 2025Article
- How accurate are ChatGPT-4 responses in chronic urticaria? A critical analysis with information quality metrics.The World Allergy Organization journal · 2025Article
- The Availability and Readability of Multilingual Online Patient Materials for Legg-Calve-Perthes Disease.Journal of the Pediatric Orthopaedic Society of North America · 2025Article
- Article
- Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.Frontiers in artificial intelligence · 2025Article
- Article
- Can ChatGPT provide quality information about fever in children?Journal of paediatrics and child health · 2025Article
- Large Language Models May Help Patients Understand Peer-Reviewed Scientific Articles About Ophthalmology: Development and Usability Study.Journal of medical Internet research · 2024Article
- Readability Metrics in Patient Education: Where Do We Innovate?Clinics and practice · 2024Article
- Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.Medicine · 2024Observational
- Article
- A Systematic Review of ChatGPT and Other Conversational Large Language Models in Healthcare.medRxiv : the preprint server for health sciences · 2024Article
- Artificial Intelligence in Senology - Where Do We Stand and What Are the Future Horizons?European journal of breast health · 2024Article
- Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review.Online journal of public health informatics · 2024Review
- The rise of artificial intelligence-driven health communication.Translational andrology and urology · 2024Article
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
Introduction Artificial Intelligence (AI) platforms have gained widespread attention for their distinct ability to generate automated responses to various prompts. However, its role in assessing the quality and readability of a provided text remains unclear. Thus, the purpose of this study is to evaluate the proficiency of the conversational generative pre-trained transformer (ChatGPT) in utilizing the DISCERN tool to evaluate the quality of online content regarding shock wave therapy for erectile dysfunction. Methods Websites were generated using a Google search of "shock wave therapy for erectile dysfunction" with location filters disabled. Readability was analyzed using Readable software (Readable.com, Horsham, United Kingdom). Quality was assessed independently by three reviewers using the DISCERN tool. The same plain text files collected were inputted into ChatGPT to determine whether they produced comparable metrics for readability and quality. Results The study results revealed a notable disparity between ChatGPT's readability assessment and that obtained from a reliable tool, Readable.com (p<0.05). This indicates a lack of alignment between ChatGPT's algorithm and that of established tools, such as Readable.com. Similarly, the DISCERN score generated by ChatGPT differed significantly from the scores generated manually by human evaluators (p<0.05), suggesting that ChatGPT may not be capable of accurately identifying poor-quality information sources regarding shock wave therapy as a treatment for erectile dysfunction. Conclusion ChatGPT's evaluation of the quality and readability of online text regarding shockwave therapy for erectile dysfunction differs from that of human raters and trusted tools. Therefore, ChatGPT's current capabilities were not sufficient for reliably assessing the quality and readability of textual content. Further research is needed to elucidate the role of AI in the objective evaluation of online medical content in other fields. Continued development in AI and incorporation of tools such as DISCERN into AI software may enhance the way patients navigate the web in search of high-quality medical content in the future.
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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.