Evidence map›Paper›PMID 42712286›Full record

ArticleBMJ digital health & AI2025

Generative artificial intelligence in medicine: a mixed-methods survey of UK general practitioners.

Anna Kharko, Cosima Locher, John Torous, Sophie Anna Rosch, Maria Hägglund, Jens Gaab, Brian McMillan, David Sundemo, Kenneth D Mandl, Charlotte Blease

Abstract read
In one paragraph

Article in BMJ digital health & AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

10 authors.

Anna KharkoDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-0908-6173
Cosima LocherDepartment of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University of Zurich, Zürich, Switzerland.
John TorousDepartment of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA.
Sophie Anna RoschUniversity Hospital Zurich, Zürich, Switzerland.ORCID 0009-0009-1092-2109
Maria HägglundDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Jens GaabClinical Psychology and Psychotherapy, University of Basel, Basel, Switzerland.
Brian McMillanCentre for Primary Care and Health Services Research, The University of Manchester, Manchester, UK.
David SundemoInstitute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Kenneth D MandlBoston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Charlotte BleaseDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the opinions of general practitioners (GPs) in the UK about the use of generative artificial intelligence (AI) tools in primary care. Methods and analysis: At the beginning of 2024, using a convenience sample, we administered an online mixed-methods survey to registered GPs currently working in the UK. Results: A total of 1006 GPs responded, with 53% being male and 54% over 46 years old. One-fifth of GPs reported having used AI for clinical practice, with male doctors and those in bigger cities being more likely to have used it. 80% of respondents expressed a need for more training in understanding these tools. GPs at least somewhat agreed AI would improve documentation (59%) and patient information gathering (56%). 55% felt AI could increase inequities and 54% saw potential for patient harm, but 47% believed it could enhance healthcare efficiency. GPs who used these tools were significantly more optimistic about the scope for generative AI in improving clinical tasks. One-third of GPs left comments that were classified into four major themes: (1) lack of familiarity and understanding with AI, (2) role of AI in clinical practice, (3) concerns about AI and (4) AI and the future of healthcare. Conclusions: This study highlights UK GPs' developing perspectives on generative AI in clinical practice, emphasising the need for more training. Many GPs reported a lack of knowledge and experience with this technology, although a portion already used non-medical grade technology for clinical tasks, with the risks that this entails.

Indexed as

Artificial intelligenceDocumentationPrimary Health Care

Identifiers

PMID42712286
PMCPMC13528321

What OpenQuestion holds

Textmetadata
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.