Evidence map›Paper›PMID 41111714›Full record

ArticleCureus2025

Evaluating ChatGPT as a Standalone Tool for Patient Education: A Review of Frequently Asked Questions by Patients With Chronic Obstructive Pulmonary Disease.

Yizhu Yin, Zara Riaz, Rafael Amoro Sanchez, Ahmed Mustafa, Ashkan Eighaei Sedeh

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yizhu YinCollege of Medicine, Catholic University of Sacred Heart Rome, Rome, ITA.
Zara RiazInternal Medicine, University Hospital Birmingham, Birmingham, GBR.
Rafael Amoro SanchezInternal Medicine, Capital Health, Trenton, USA.
Ahmed MustafaInternal Medicine, Capital Health, Trenton, USA.
Ashkan Eighaei SedehInternal Medicine, University of Massachusetts, Amherst, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligencechatgpt 4-ocopd (chronic obstructive pulmonary disease)patient-education toolpulmonary disease

Identifiers

PMID41111714
PMCPMC12532070

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Registered trials

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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.