Evidence map›Paper›PMID 41085611›Full record

ArticleJournal of robotic surgery2025

Quality assessment of patient-facing urologic telesurgery content using validated tools.

Tarak Davuluri, Paul Gabriel, Matthew Wainstein, Obi Ekwenna

Abstract read
In one paragraph

Article in Journal of robotic surgery, 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

4 authors.

Tarak DavuluriUniversity of Toledo College of Medicine and Life Sciences, Toledo, USA.
Paul GabrielUniversity of Toledo College of Medicine and Life Sciences, Toledo, USA.
Matthew WainsteinUniversity of Toledo College of Medicine and Life Sciences, Toledo, USA.
Obi EkwennaUniversity of Toledo College of Medicine and Life Sciences, Toledo, USA. obi.ekwenna@utoledo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWith increasing accessibility to Artificial Intelligence (AI) chatbots, the precision and clarity of medical information provided require rigorous assessment. Urologic telesurgery represents a complex concept that patients will investigate using AI. We compared ChatGPT and Google Gemini in providing patient-facing information on urologic telesurgical procedures.

methods19 questions related to urologic telesurgery were generated using general information from the American Urologic Association (AUA) and European Robotic Urology Section (ERUS). Questions were organized into 4 categories (Prospective, Technical, Recovery, Other) and directly typed into ChatGPT 4o and Google Gemini 2.5 (non-paid versions). For each question, a new chat was started to prevent any continuation of answers. Three reviewers independently reviewed the responses using two validated healthcare tools: DISCERN (quality) and Patient Education Material Assessment Tool (understandability and actionability).

resultsMean DISCERN scores (out of 80) were higher for Gemini than ChatGPT in all domains except "Other". Prospective 49.2 versus 39.1; technical 52.3 versus 44.3; recovery 53.7 versus 45.4; other 54.3 versus 56.5; overall 52.4 versus 45.8 (Fig. 1). PEMAT-P understandability uniformly exceeded 70% for both platforms: prospective 80.0% versus 71.7%; technical 80.1% versus 79.8%; recovery 79.2% versus 80.1%; other 79.2% versus 81.3%; overall 79.7% versus 78.1% (Fig. 2). Actionability was uniformly low; only Gemini met the 70% threshold in the prospective domain (Fig. 3). Fig. 1 A Mean DISCERN scores (out of 5) with standard deviations for each response B Mean total DISCERN scores (out of 80) among each question category and overall. Numerical representation in the graph was rounded to the closest whole number for easier interpretation. Graphed value is still the true value. [56.5 represented numerically as 57, etc.…] Fig. 2 A Mean PEMAT-P Understandability scores with standard deviations for each response B Mean PEMAT-P Understandability scores among each question category and overall (70% minimum threshold for responses to be deemed "understandable"). Numerical representation in the graph was rounded to the closest whole number for easier interpretation. Graphed value is still the true value. [71.70% represented numerically as 72%, etc.…] Fig. 3 A Mean PEMAT-P Actionability scores with standard errors for each response B Mean PEMAT-P Actionability scores among each question category and overall (70% is the minimum threshold for responses to be deemed "actionable"). Numerical representation in the graph was rounded to the closest whole number for easier interpretation. The graphed value is still the true value. [65.40% represented numerically as 65%, etc.…]

conclusionChatGPT and Gemini deliver relevant and understandable information related to urologic telesurgery, with Gemini more consistently providing sources. However, neither chatbot reliably offers actionable responses, limiting their utility as a standalone gateway for patient decision-making.

Indexed as

Quality Assurance, Health CareRobotic Surgical ProceduresTelemedicineUrologic Surgical ProceduresArtificial IntelligenceHumansPatient Education as TopicAI chatbotsDISCERNPEMATUrologic telesurgery

Identifiers

PMID41085611
PMCPMC12521288

What OpenQuestion holds

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LicenceCC BY
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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.