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Generative Artificial Intelligence in Primary Care: Qualitative Study of UK General Practitioners' Views
Charlotte Blease1, Carolina Garcia Sanchez1, Cosima Locher2
1Participatory eHealth & Health data Research Group, Department of Women's and Children's Health, Uppsala University, MTC-huset, Dag Hammarskjölds väg 14B, 1 tr, Uppsala, 752 37, Sweden, 46 184710000.
Background:
The potential for generative artificial intelligence (GenAI) to assist with clinical tasks is the subject of ongoing debate within biomedical informatics and related fields.
Objective:
This study aimed to explore general practitioners' (GPs') opinions about GenAI on primary care.
Methods:
In January 2025, we conducted a web-based survey of 1005 UK GPs' experiences and opinions of GenAI in clinical practice. This study involved a qualitative inductive descriptive analysis of a written response ("comments") to an open-ended question in the survey. After analysis, the interpretation of themes was also informed by the technology acceptance model.
Results:
Out of 1005 respondents, 611 GPs (61%) provided written comments in response to the free text question, totaling 7990 words. Comments were classified into 3 major themes and 8 subthemes in relation to GenAI in clinical practice. The major themes were (1) unfamiliarity, (2) ambivalence and anxiety, and (3) role in clinical tasks. "Unfamiliarity" encompassed a lack of experience and knowledge, and the need for training on GenAI. "Ambivalence and anxiety" included mixed expectations among GPs in relation to these tools, beliefs about diminished human connection, and skepticism about AI accountability. Finally, commenting on the role of GenAI in clinical tasks, GPs believed it would help with documentation. However, respondents questioned AI's clinical judgment and raised concerns about operational uncertainty concerning these tools. Female GPs were more likely to leave comments than male GPs, with 53% (324/611) of female GPs providing feedback compared to 41.1% (162/394) who did not. Chi-square tests confirmed this difference ((χ²₂= 14.6, P=.001). In addition, doctors who left comments were significantly more likely to have used GenAI in clinical practice compared with those who did not. Among all respondents, 71.7% (438/611) had not used GenAI. However, noncommenters were even less likely to have used it, with 80.7% (318/394) reporting no use. A chi-square test confirmed this difference (χ²₁=10.0, P=.002).
Conclusions:
This study provides timely insights into UK GPs' perspectives on the role, impact, and limitations of GenAI in primary care. However, the study has limitations. The qualitative data analyzed originates from a self-selected subset of respondents who chose to provide free-text comments, and these participants were more likely to have used GenAI tools in clinical practice. However, the substantial number of comments offers valuable insights into the diverse views held by GPs regarding GenAI. Furthermore, the majority of our respondents reported limited experience and training with these tools; however, many GPs perceived potential benefits of GenAI and ambient AI for documentation. Notably, 2 years after the widespread introduction of GenAI, GPs' persistent lack of understanding and training remains a critical concern. More extensive qualitative work would provide a more in-depth understanding of GPs' views.
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