ArticleNPJ digital medicine2025
The impact of GenAI on applicant behaviour, performance, and interview reliability during virtual interviews for medical school admissions.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Designing AI-resilient admissions interviews for health professions training in the age of generative AI.NPJ digital medicine · 2026Article
- Generative artificial intelligence in medical education: from knowledge assessment to clinical reasoning and professional competence.Frontiers in medicine · 2026Review
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
As artificial intelligence becomes increasingly powerful and accessible, education programs must guard against risks during student selection. Chief among those is avoidance of rewarding applicants who use prohibited tools. The trend towards increased use of virtual interviews makes programs particularly susceptible. To empirically study the risk and mitigation strategies, we conducted a randomized experiment comparing preparatory behaviors, performance, reliability and acceptability for candidates encouraged to surreptitiously use ChatGPT relative to two control groups. No advantages were observed (ChatGPT group mean = 3.67 (sd = 0.69) vs 3.74 (sd = 0.61) for 'usual practice' controls and 3.73 (sd = 0.80) for participants who were foretold station content). Reducing the time interviewees had to engage with ChatGPT off camera did not harm performance (3.73 (sd = 0.58) vs 3.70 (sd = 0.81) for controls); precision of test scores (SEMeas = 0.34 vs 0.39); or acceptability ratings (mean = 4.0 vs 4.1). These findings suggest an easy way to increase confidence in the fairness of virtual interviews.
Identifiers
What OpenQuestion holds
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.