Evidence map›Paper›PMID 41049646›Full record

ArticleJSES international2025

Evaluation of ChatGPT's responses to frequently asked questions about shoulder arthroplasty.

Fátima Fernández Dorado, Salvador Álvarez Villar, Carlos Alexi Osuna Mavare, Raquel Ruíz Díaz, Jorge Díaz Heredia, Miguel Ángel Ruiz Ibán

Abstract read
In one paragraph

Article in JSES international, 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

6 authors.

Fátima Fernández DoradoServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.
Salvador Álvarez VillarServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.
Carlos Alexi Osuna MavareServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.
Raquel Ruíz DíazServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.
Jorge Díaz HerediaServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.
Miguel Ángel Ruiz IbánServicio de Traumatología y Cirugía Ortopédica, Hospital Ramón y Cajal, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients now have access to numerous resources about common orthopedic procedures before clinical consultations. Recently, artificial intelligence (AI)-powered chatbots have gained popularity, offering human-like, convincing responses. A prominent example is ChatGPT, an AI-based chat technology, which has seen rapid growth in acceptance. Given the increasing likelihood that patients will turn to this technology for educational information prior to undergoing surgical intervention, we aimed to determine ChatGPT's ability to provide adequate answers to frequently asked questions about shoulder arthroplasty. Methods: After a literature review, we formulated the 10 most frequently asked questions about shoulder arthroplasty and presented them to the chatbot without follow-up questions or repetitions. The responses were analyzed by 15 independent shoulder surgeons, who evaluated each response for accuracy using an evidence-based approach. The responses were classified as "excellent response without need for clarification," "satisfactory requiring minimal clarification," "satisfactory requiring moderate clarification," or "unsatisfactory requiring substantial clarification." Results: Of the responses given by the chatbot, 45.5% of the time the expert panel rated the response as "excellent," 38.2% of the time the rating was "satisfactory requiring minimal clarification," and only 11.8% and 4.5% of the responses were rated as "satisfactory requiring moderate clarification" and "unsatisfactory," respectively. Conclusion: ChatGPT provides reliable information to patients undergoing shoulder arthroplasty. As a complementary educational resource, AI shows potential by delivering accurate, evidence-based answers with little need for clarification and minimal bias. Despite limitations, the study underscores the promising role of AI-based platforms in healthcare.

Indexed as

ArthroplastyArtificial intelligenceChatGPTOpenAIShoulderSurgery

Identifiers

PMID41049646
PMCPMC12490572

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.