Evidence map›Paper›PMID 38694019›Full record

ArticleJournal of physical therapy science2024

Evaluation of the accuracy of ChatGPT's responses to and references for clinical questions in physical therapy.

Shogo Sawamura, Takanobu Bito, Takahiro Ando, Kento Masuda, Sakiko Kameyama, Hiroyasu Ishida

Open access · diamondAbstract read
In one paragraph

Article in Journal of physical therapy science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
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

9 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Reference Accuracy in Large Language Model Chatbots: A Metric for Inherent Misinformation?Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Review
  9. 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

6 authors at 2 institutions in 1 country.

Shogo SawamuraDepartment of Rehabilitation, Heisei College of Health Sciences: 180 Kurono, Gifu City, Gifu 501-1131, Japan.
Takanobu BitoDepartment of Rehabilitation, Gifu University Hospital, Japan.
Takahiro AndoDepartment of Rehabilitation, Gifu University Hospital, Japan.
Kento MasudaDepartment of Rehabilitation, Gifu University Hospital, Japan.
Sakiko KameyamaDepartment of Rehabilitation, Heisei College of Health Sciences: 180 Kurono, Gifu City, Gifu 501-1131, Japan.
Hiroyasu IshidaDepartment of Rehabilitation, Heisei College of Health Sciences: 180 Kurono, Gifu City, Gifu 501-1131, Japan.
Gifu University Hospital · JPHeisei College of Health Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

[Purpose] This study evaluated the accuracy of ChatGPT's responses to and references for five clinical questions in physical therapy based on the

Indexed as

Artificial intelligenceLanguage modelPhysical therapy

Identifiers

PMID38694019
PMCPMC11060764
OpenAlexW4396523822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.