ArticleDigital health
General practitioners' opinions of generative artificial intelligence in the UK: An online survey.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Disclosure is not documentation: an open science framework for documenting generative AI use in scholarly research and publication workflows.Research integrity and peer review · 2026Article
- Article
- Article
- Use of AI scribes in UK primary care: a survey of general practitioners.NPJ digital medicine · 2026Article
- The dark side of Gen-AI-assisted clinical work collaboration: work alienation, trait emotional intelligence, and instigated interprofessional incivility.Frontiers in psychology · 2026Article
- Priorities for artificial intelligence education: clinicians' perspectives.BMJ digital health & AI · 2026Article
- Generative Artificial Intelligence in Primary Care: Qualitative Study of UK General Practitioners' Views.Journal of medical Internet research · 2025Article
- Adoption, perceived value, and barriers to generative artificial intelligence in emergency medicine: A cross-sectional survey of Latin American clinicians.International journal of critical illness and injury scienceArticle
- Article
- Article
- Acceptance of AI scribes within hospital allied health settings: A mixed methods study.Digital healthArticle
- General practitioners' opinions of generative artificial intelligence in the UK: An online survey.Digital healthArticle
- Psychiatrists' experiences and opinions of generative AI: An exploratory online mixed methods survey in Germany.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The rapid rise of large language model-based generative artificial intelligence (AI) tools, such as chatbots and AI scribes, has prompted interest in their clinical applicability. This study examined the perspectives of Methods: In January 2025, a national online survey of 1005 GPs, stratified by region, was administered via the UK's largest clinical marketing platform. The survey gathered data on attitudes towards generative AI, its perceived effects on clinical tasks, care delivery and respondent demographics. Group differences and correlations between opinions and respondent characteristics were analysed. Results: Among the 1005 respondents, 50% were male, 54% aged 46 or older, and 83% practised in England. Only 11% were encouraged by their employer to use generative AI tools, and 5% had received training. Most agreed that AI could improve documentation (69%) and patient information gathering (57%), and 59% expected increased efficiency in care. A similar proportion (59%) anticipated that patients may rely on AI instead of seeking medical care. The majority (79%) agreed that training is needed, while 71% disagreed that AI could enhance empathic communication. Male GPs were more likely to view AI as beneficial across tasks, while female GPs more often emphasised training needs. Older GPs expressed concern about potential inequities stemming from AI use. Conclusions: While GPs were cautiously optimistic about generative AI - particularly for documentation and data collection - scepticism persisted. In particular, around empathy and equity, highlighting the need for guidance on AI integration into primary care.
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Registered trials
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.