Evidence map›Paper›PMID 41391127›Full record

ArticleJoint diseases and related surgery2026

Comparison of ChatGPT and Google in addressing patients' questions on robot-assisted total hip arthroplasty.

Mustafa Fatih Dasci, Serkan Surucu, Furkan Aral, Mahmud Aydin, Cihangir Turemis, N Amir Sandiford, Mustafa Citak

Abstract readComparative Study
In one paragraph

Article in Joint diseases and related surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

7 authors.

Mustafa Fatih Dasci
Serkan Surucu
Furkan Aral
Mahmud Aydin
Cihangir Turemis
N Amir Sandiford
Mustafa CitakENDO-Klinik Hamburg, Department of Orthopaedic Surgery, Holstenstr. 2, 22767 Hamburg, Germany. mcitak@gmx.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aims to compare ChatGPT (Generative Pre-Trained Transformer) and Google in addressing frequently asked questions (FAQs), answers, and online sources regarding robot-assisted total hip arthroplasty (RATHA). MATERIALS AND

methodsOn December 15

resultsOverall, 20% of the questions that Google and ChatGPT-4o considered as the most FAQ were similar to each other. Technical details (35%) were the most common categories of questions. The ChatGPT provided significantly more academic references than Google search (70% vs. 20%, p=0.0113). Conversely, Google web search cited more medical practice references (40% vs. 0%, p=0.0033), single surgeon websites (20% vs. 0%, p=0.1060), and government websites (10% vs. 0%, p=0.4872) more frequently than ChatGPT. In terms of response quality, 62% of answers were rated as Grade 1-2 (excellent or satisfactory with minimal clarification), while 38% required moderate or substantial clarification (Grades 3-4).

conclusionChatGPT demonstrated comparable results to those of Google searches on information regarding RATHA, with a higher reliance on academic sources. While most responses were satisfactory, a notable proportion required further clarification, emphasizing the need for continued evaluation of these platforms to ensure accuracy and reliability in patient education. Taken together, these technologies have the capacity to enhance health literacy and provide enhanced shared decision-making for patients seeking information on RATHA.

Indexed as

Arthroplasty, Replacement, HipInternetPatient Education as TopicRobotic Surgical ProceduresSearch EngineSocial MediaGenerative Artificial IntelligenceHumansSurveys and Questionnaires

Identifiers

PMID41391127
PMCPMC12788757

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.