ArticleCureus2025
Evaluating ChatGPT as a Standalone Tool for Patient Education: A Review of Frequently Asked Questions by Patients With Chronic Obstructive Pulmonary Disease.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Accuracy, comprehensiveness and understandability of AI-generated answers to questions from people with COPD: the AIR-COPD Study.Respiratory research · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimChronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. As patient education remains a critical tool in battling chronic conditions, including COPD, a potential role for artificial intelligence (AI) chatbots has taken center stage due to their evolving nature and free availability to the public. However, questions remain on the accuracy and reliability of the information offered by these tools. This study aims to evaluate the accuracy and reproducibility of the responses provided by Chat Generative Pre-trained Transformer (ChatGPT), version 4o (OpenAI, San Francisco, CA), a frequently utilized AI chatbot, to common questions asked by COPD patients. MATERIALS AND
methodsA set of 44 patient-centered questions regarding COPD was selected and reviewed by physicians experienced in managing pulmonary disorders to ensure quality and relevance. Each question was submitted to ChatGPT (version 4o) three times by study staff, using separate accounts. A majority response, repeated two times or more, was identified per question and was assessed for accuracy and reproducibility by two physicians experienced in COPD management, using a structured rubric. Responses were classed as accurate (complete responses inline with practice guidelines), partially accurate (omitted some information but relayed key points and did not share false information), or inaccurate (false or misleading information). In case of a disagreement in scoring, a consensus review was performed by a third physician.
resultsThe mean accuracy score was moderate (0.61, SD ± 0.14), with 20.5% (9/44) fully accurate, 79.5% (35/44) partially accurate, and no inaccurate responses, which significantly diverges from the hypothetical perfect score (t=-19.14, p<0.001). However, a high reproducibility score was achieved as responses showed consistency across three iterations, for 93.2% (41/44; 95% CI: 81.4-98.3%) of the questions.
conclusionWhile ChatGPT shows consistency in responding to COPD-related queries, it cannot yet serve as a standalone patient-education tool. Even though none of the responses were inaccurate, suggesting a potentially safe resource, oversimplification and omitting key information are major limiting factors leading to partial and incomplete responses, raising concerns for potential misinformation. ChatGPT may serve as a supplementary tool in COPD-related disease management, but its utilization must be accompanied by validation from healthcare professionals.
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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.