Evidence map›Paper›PMID 39806591›Full record

ArticleBMJ open2024

Healthcare ethics and artificial intelligence: a UK doctor survey.

Daniel Joseph Warrington, Søren Holm

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

2 authors.

Daniel Joseph Warrington *Manchester University NHS Foundation Trust, Manchester, UK.ORCID http://orcid.org/0000-0002-0122-2938
Søren Holm *Centre for Social Ethics and Policy, Department of Law, School of Social Sciences, University of Manchester, Manchester, UK soren.holm@manchester.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo survey UK doctors on their uses of artificial intelligence (AI) and of their views on the ethics and regulation of AI in healthcare.

designAnonymous cross-sectional e-survey.

settingAn online survey of UK General Medical Council (GMC) registered doctors.

participants272 individuals.

main outcome measuresLikert-scale responses to questions covering personal use of AI, concerns about AI, requirements for introduction of AI and views on necessary AI regulation in healthcare.

resultsMost doctors rated themselves as slightly or moderately knowledgeable about AI, with men rating their knowledge levels higher than women. Doctors in training are more likely to have used AI than doctors after training. 37% of doctors who use AI reported using AI to help write the required reflective pieces for their portfolio. Doctors reported concerns about AI regarding patient safety and patients' right to confidentiality. They also expressed a strong desire for further regulation of AI in healthcare and, specifically, for their professional bodies to draft guidelines for the use of AI by doctors.

conclusionsThis study provides useful insights into UK doctors' uses of AI in healthcare and their opinions on its introduction and regulation. It provides a case for guidance on the use of AI in the reflective practices of doctors and for further evaluation of doctors' concerns about AI in healthcare. We call on doctors' professional bodies (GMC, BMA and royal colleges) to draft professional guidance for doctors using AI.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelDelivery of Health CareEthics, MedicalPhysiciansAdultConfidentialityCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesUnited KingdomArtificial IntelligenceDecision MakingMEDICAL EDUCATION & TRAININGMEDICAL ETHICS

Identifiers

PMID39806591
PMCPMC11667393

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.