Trial reportBMC medical education2026
Artificial intelligence-powered virtual standardized patients in teaching history-taking skills to medical students: a randomized controlled trial.
Trial report in BMC medical education, 2026. 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
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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.
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.
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) has emerged as a promising tool in medical education. It offers opportunities to enhance learning experiences, particularly through the development of virtual standardized patients (SP) integrated with AI for training purposes. These virtual patients are especially useful for teaching history-taking skills (HTS). However, evidence comparing AI-powered virtual standardized patients (AI-VSP) with traditional SP in teaching HTS remains unclear. This study aimed to evaluate the effectiveness of AI-VSP and compare it with conventional SP in teaching HTS to undergraduate medical students.
methodsA randomized controlled trial (TCTR20251202012) was conducted among third-year medical students at Duy Tan University, Vietnam. This study included participants in the pre-clinical skills curriculum without prior formal HTS training. Students were randomized at the class level to intervention or control groups via a computer-generated sequence. The intervention group practiced with AI-VSP, while the control group learned with conventional SP. Primary outcomes included pre-test, post-test, and objective structured clinical examination (OSCE) scores. Examiners were blinded to group allocation. Student satisfaction was assessed as a secondary outcome using a 5-point Likert scale.
resultsA total of 67 medical students were included, comprising 34 in the AI-VSP group and 33 in the SP group. Both groups demonstrated significant improvement in post-test scores compared with pre-test results (p < 0.001). In the AI-VSP group, the mean score increased from 3.41 ± 2.56 to 8.56 ± 1.85, while in the SP group, it rose from 3.24 ± 1.64 to 7.97 ± 1.85. The magnitude of improvement was 5.15 ± 2.88 in the AI-VSP group and 4.73 ± 1.75 in the SP group (p = 0.503). The mean OSCE scores were 6.5 ± 1.5 for the AI-VSP group and 6.3 ± 1.7 for the SP group (p = 0.543). Mixed-effects modeling adjusting for age and class-level clustering confirmed that neither pre-test, post-test, OSCE scores, nor score improvement differed significantly between instructional methods. Regarding student satisfaction, there was no statistically significant difference in perceived learning experience between the two groups (all p > 0.05).
conclusionsLearning outcomes and student satisfaction did not differ significantly between the AI-VSP and SP instructional methods.
trial registrationTCTR20251202012 (registered on 20/11/2025); retrospectively registered; https://www.thaiclinicaltrials.org/show/TCTR20251202012.
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