ArticleCureus2024
Is ChatGPT a Reliable Source of Patient Information on Asthma?
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Conversational Agents for Asthma and Chronic Obstructive Pulmonary Disease Management: Scoping Review.Journal of medical Internet research · 2026Article
- The Reliability of Human Evaluation of Large Language Models in Health Care Settings: Scoping Review.Journal of medical Internet research · 2026Article
- Current understanding and future directions in severe asthma through artificial intelligence-integrated multi-omic approaches.European respiratory review : an official journal of the European Respiratory Society · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionChatGPT (OpenAI, San Francisco, CA, USA) is a novel artificial intelligence (AI) application that is used by millions of people, and the numbers are growing by the day. Because it has the potential to be a source of patient information, the study aimed to evaluate the ability of ChatGPT to answer frequently asked questions (FAQs) about asthma with consistent reliability, acceptability, and easy readability.
methodsWe collected 30 FAQs about asthma from the Global Initiative for Asthma website. ChatGPT was asked each question twice, by two different users, to assess for consistency. The responses were evaluated by five board-certified internal medicine physicians for reliability and acceptability. The consistency of responses was determined by the differences in evaluation between the two answers to the same question. The readability of all responses was measured using the Flesch Reading Ease Scale (FRES), the Flesch-Kincaid Grade Level (FKGL), and the Simple Measure of Gobbledygook (SMOG).
resultsSixty responses were collected for evaluation. Fifty-six (93.33%) of the responses were of good reliability. The average rating of the responses was 3.65 out of 4 total points. 78.3% (n=47) of the responses were found acceptable by the evaluators to be the only answer for an asthmatic patient. Only two (6.67%) of the 30 questions had inconsistent answers. The average readability of all responses was determined to be 33.50±14.37 on the FRES, 12.79±2.89 on the FKGL, and 13.47±2.38 on the SMOG.
conclusionCompared to online websites, we found that ChatGPT can be a reliable and acceptable source of information for asthma patients in terms of information quality. However, all responses were of difficult readability, and none followed the recommended readability levels. Therefore, the readability of this AI application requires improvement to be more suitable for patients.
Indexed as
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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.