Evidence map›Paper›PMID 40965769›Full record

ArticleIrish journal of medical science2025

Comparative analysis of perceptions on artificial intelligence in surgery: a survey study among surgeons and medical students in Ireland.

Doris Braunstein, Haniya Farooq, Marco Paolino, Alice Moynihan, Ronan A Cahill

Abstract readComparative Study
In one paragraph

Article in Irish journal of medical science, 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

5 authors.

Doris BraunsteinUCD School of Medicine, University College Dublin, Dublin, Ireland.ORCID http://orcid.org/0009-0009-0653-4701
Haniya FarooqUCD School of Medicine, University College Dublin, Dublin, Ireland.
Marco PaolinoUCD School of Medicine, University College Dublin, Dublin, Ireland.
Alice MoynihanUCD Centre for Precision Surgery, University College Dublin, 47 Eccles Street, Dublin, Ireland.
Ronan A CahillUCD School of Medicine, University College Dublin, Dublin, Ireland. ronan.cahill@ucd.ie.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial Intelligence (AI) promises to revolutionize healthcare but has been previously characterized by cycles of "boom" and "bust." Alongside technological capability, realistic user expectations are essential for appropriate implementation. We surveyed surgeons, surgical trainees, and medical students in Ireland regarding their current perceptions.

methodsElectronic survey distributed through professional networks and social media with institutional ethical approval. Statistical and thematic analyses were performed to identify key perspectives.

resultsAmong 94 participants (63% medical students, 18% surgical trainees, 15% consultants, and 4% ancillary surgical roles), 62.7% "strongly agreed" that AI could enhance real-time decision-making during surgery. Most (90.5%) believed AI was already being surgically deployed to some extent although only 18% felt it appropriate ever to use for decision-making. While 53.2% were positive about AI's potential to improve surgical outcomes, 72.3% reported no AI training in this context despite 86.2% expressing interest. The primary concerns with AI regarded accuracy and reliability (38.7%) and the lack of evidence of effectiveness (33.7%). Surgical trainees expressed greater concern about AI transparency (47% "extremely concerned") compared to consultants (42.9% "slightly concerned") and, along with students, declared higher concern regarding liability issues versus consultants (64.3% of whom had "little to no concern").

conclusionStudents and postgraduates in surgery in Ireland express optimism and high expectations for AI's potential to improve surgery. However, concerns about reliability, evidence, and liability persist with clear caution regarding automated decision-making and insight regarding the need for education that may help align expectations realistically regarding AI evolution.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelStudents, MedicalSurgeonsAdultFemaleHumansIrelandMaleSurveys and QuestionnairesArtificial intelligenceIntraoperative decision-makingMedical studentsSurgeon perspectivesSurgery

Identifiers

PMID40965769
PMCPMC12769670

What OpenQuestion holds

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LicenceCC BY
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.