ArticlePRiMER (Leawood, Kan.)2025
Evaluating ChatGPT's Educational Suitability for Patient Primary Care Queries.
Article in PRiMER (Leawood, Kan.), 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
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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.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: ChatGPT, a large language model created by OpenAI, has emerged as a new source of online medical information. This study aimed to evaluate the appropriateness, readability, and educational value of ChatGPT's responses to frequent patient internet queries regarding 10 common primary care diagnoses. Methods: The responses generated by ChatGPT regarding the 10 most frequently encountered primary care diagnoses were assessed for appropriateness and readability by two primary care physicians. Responses were judged based on educational value in four categories: basic knowledge, diagnosis, treatment, and prevention. We used a 5-point Likert scale based on accuracy, comprehensiveness, and clarity to determine appropriateness. ChatGPT responses that received ratings of 4-5 in all three criteria were considered appropriate. Conversely, if the outputs received ratings of 1-3 in any category, they were deemed inappropriate. We performed readability assessments using the Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKGL) formulas to determine if the responses were at the recommended average American's seventh to eighth grade reading level. Results: Most (92.5%) responses were deemed appropriate unanimously by both reviewers. ChatGPT provided more appropriate responses regarding basic knowledge compared to diagnosis, treatment, and prevention. The ChatGPT responses demonstrated a college graduate reading level, as indicated by the mean FRE score of 25.64 and the median FKGL score of 12.61. Conclusion: Our comprehensive analysis found that ChatGPT's responses were appropriate most of the time. These findings suggest that ChatGPT has potential to be a supplementary educational tool for patients seeking health information online.
Identifiers
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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.