ArticlePloS one2025
Physician awareness of, interest in, and current use of artificial intelligence large language model-based virtual assistants.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Smartphone Applications in Dermatology With Special Focus on AI: A European-Continent-Based Review.International journal of dermatology · 2026Review
- Acceptable accuracy for medical AI: a survey of physicians and the general population in Sweden.BMJ health & care informatics · 2026Article
- Meeting clinicians where they are through signal-guided AI innovation.BMJ digital health & AI · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is increasing medical interest and research regarding the potential of large language model-based virtual assistants in healthcare. It is important to understand physicians' interest in implementing these tools into clinical practice, so preceding education could be implemented to ensure appropriate and ethical use. We aimed to assess physician 1) awareness of, 2) interest in, and 3) current use of large language model-based virtual assistants for clinical practice and professional development and determine the specific applications of interest and use. Additionally, we wanted to determine associations with age, gender, and role. We conducted a cross-sectional study between 11/08-12/2023 via an anonymous web-based survey that was disseminated among physicians at a large NY healthcare network using snowball sampling. Descriptive and basic inferential statistics were performed. There were 562 respondents, largely males (55.7%), attending physicians (68.5%), and from nonsurgical specialties (67.4%). Most were aware of large language model chatbots (89.7%) and expressed interest (97.2%). Only a minority incorporated it into their practice (21%). Highest levels of interest were for journal review, patient education, and documentation/dictation (88.1-89.5%). The most frequently employed uses were medical information and education and study/research design. Females showed higher interest than males (99.2% vs. 95.5%, p = 0.011). Attendings were more aware of large language models (92.2% vs. 84.2%, p = 0.004), while trainees had increased rates of use (28.8% vs. 17.4%, p = 0.002). Use varied across age brackets, highest among 20-30 year olds (29.1% vs. 13.5%-23.4%, p = 0.018), except for documentation/dictation, where highest use was among the 41-50 year old group (10.5% vs. 2.6%-8.7%, p = 0.047). We concluded that physicians are interested in large language model-based virtual assistants, a minority are implementing it into their practice, and gender-, role-, and age-based disparities exist. As physicians continue to integrate large language models into their patient care and professional development, there is opportunity for research, education, and guidance to ensure an inclusive, responsible, and safe adoption.
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