Evidence map›Paper›PMID 42249802›Full record

ArticleMovement disorders clinical practice2026

Quality and Readability of ChatGPT Performance on Parkinson's Disease.

Gabriele Riccio, Rosa Coppola, Maria Rosaria Chiariello, Augusta Giglio, Anna De Rosa

Abstract read
In one paragraph

Article in Movement disorders clinical practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Gabriele RiccioDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.ORCID https://orcid.org/0009-0001-4474-1172
Rosa CoppolaDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.
Maria Rosaria ChiarielloDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.ORCID https://orcid.org/0009-0002-9723-6767
Augusta GiglioDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.
Anna De RosaDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.ORCID https://orcid.org/0000-0002-5618-2478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChat Generative Pre-trained Transformer (ChatGPT) is increasingly used for medical education and healthcare counseling.

objectiveTo evaluate the reliability, quality, usefulness, and readability of ChatGPT-4o responses to professional medical quizzes and patient frequently asked questions (FAQs) about Parkinson's disease (PD).

methodsTwenty-two quizzes were put into ChatGPT-4o and also given to two neurologists. ChatGPT answers to 20 FAQs were analyzed by three neurologists using the modified Discern score, the Global Quality score, and the Usefulness score. Text readability was assessed using the Flesch-Kincaid Reading Grade Level, the Flesch Reading Ease Score, and the Simple Measure of Gobbledygook.

resultsThe agreement between the neurologists and ChatGPT was fair. The  answers to the FAQs were of good quality, but unreliable and difficult to read.

conclusionsChatGPT may be an additional valid tool for professional medical education. The quality of the answers to the FAQs is good, but the text is aimed primarily at highly educated individuals. The readability and reliability of the output would likely improve by providing the chatbot with specific prompts.

Indexed as

artificial intelligenceChatGPTmedical informationParkinson's disease

Identifiers

PMID42249802
PMCPMC13338990

What OpenQuestion holds

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LicenceCC BY
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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.