ArticleMedical science educator2025
Generative AI as the First Patient: Practice, Feedback, and Confidence.
Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Using artificial intelligence thanabots as "thanatobots" to assist anatomy learning and professional development: Ghosts masquerading as opportunity?Anatomical sciences education · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Generative artificial intelligence (GenAI) offers new potential for medical education by providing personalized learning opportunities at scale that address current faculty shortages, such as limited access to clinical preceptors, yet its integration into formal medical training and acceptability by students remains largely unexplored. We deployed a large-language model-based AI Patient Actor app in a first-year medical curriculum, enabling students to conduct simulated clinical interviews while receiving immediate feedback. Students rated their experiences as overwhelmingly positive, with comfort using GenAI in general increasing significantly after repeated engagement. Sentiment analysis of student comments showed appreciation for the AI approaches' flexibility, low-pressure environment, and real-time feedback that students felt helped with clinical reasoning and communication skills. Students identified limitations regarding the authenticity of AI interactions compared to human encounters. This study shows that AI patient actors are perceived as acceptable educational adjuncts in early clinical training, particularly in formative environments where they provide students with immediate feedback and greater autonomy over their learning process, though they cannot fully replace interactions with human actors and patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-025-02473-x.
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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.