Virtual Standardized Patients for Improving Clinical Thinking Ability Training in Residents: Randomized Controlled Trial
Bibliographic record
Abstract
Background: Clinical internal medicine practice training traditionally relies on case-based teaching. This approach limits the development of students' clinical thinking skills. It also places significant pressure on instructors. Virtual standardized patients (VSPs) could offer an alternative solution. However, evidence on their feasibility and effectiveness remains limited. Objective: This study aims to use the "VSPs in general practice" interactive diagnostic and teaching system, which uses VSPs to provide 3D virtual simulated patients and mimic virtual clinical scenarios. Medical students are trained through system-preset cases. This study aims to establish the clinical application of VSPs through a "VSPs in general practice" system and compare its effectiveness with traditional teaching in improving students' clinical thinking ability. Methods: A randomized controlled trial was conducted from October 20, 2022, to October 20, 2024. A total of 60 medical students interning at Quzhou People's Hospital were enrolled and divided into 2 groups: the experimental group receiving VSP training (30/60, 50%) and the control group receiving traditional academic training (30/60, 50%). The teaching effectiveness was evaluated using basic knowledge assessments and virtual system scoring. After completing the course, students were surveyed with a questionnaire to assess their satisfaction with the course. Results: All enrolled medical students completed the study. In the evaluation of training effectiveness, the experimental group showed significantly greater improvement in theoretical scores compared to the control group (mean 17.07, SD 4.24 vs mean 10.67, SD 4.91; F1, 59=29.20; Cohen d=1.15; 95% CI 12.43-15.31; P<.001); the total score improvement in the virtual clinical thinking training system test was also significantly better in the experimental group than in the control group (mean 42.60, SD 9.56 vs mean 31.63, SD 7.24; F1, 59=25.10; Cohen d=1.09; 95% CI 34.51-39.72; P<.001). Specifically, improvements in consultation skills (mean 8.76, SD 1.67 vs mean 7.66, SD 2.08; F1, 59=31.09; Cohen d=0.55; 95% CI 7.70-8.70; P<.001), overall objective improvement (mean 11.97, SD 2.77 vs mean 8.15, SD 2.62; F1, 59=30.08; Cohen d=1.16; 95% CI 9.21-10.91; P<.001), initial diagnostic ability (mean 8.74, SD 1.67 vs mean 7.66, SD 2.08; F1, 59=4.91; Cohen d=0.55, 95% CI 7.70-8.70; P=.03), and ability to provide patient treatment (mean 7.23, SD 2.41 vs mean 5.72, SD 2.19; F1, 59=6.42; Cohen d=0.63; 95% CI 5.85-7.01; P=.01) were significantly higher in the experimental group than in the control group. The questionnaire results indicated that 90% (27/30) of the students who participated in the VSPs' training believed it could enhance their clinical thinking abilities. Conclusions: VSPs reinforce the foundational knowledge of internal medicine among medical students and enhance their clinical thinking abilities, as well as improve their capacity for independent work. The VSP system is feasible, practical, and cost-effective, making it worthy of further promotion in clinical education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".