Evidence map›Paper›PMID 41937174›Full record

Trial reportBMC medical education2026

Self-directed teaching system driven by video analysis feedback improves surgical skill training for clinical interns: a randomized controlled trial.

Boqiang Liu, Bin Gong, Xiaochen Zhang, Chen Lu, Bin Zheng, Jin Yang

Abstract readRandomized Controlled Trial
In one paragraph

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Boqiang Liu *Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.
Bin Gong *Education office, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.
Xiaochen ZhangEducation office, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.
Chen LuDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.
Bin ZhengDepartment of Surgery, University of Alberta, Edmonton, Canada. bin.zheng@ualberta.ca.
Jin YangDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China. 3319017@zju.edu.cn.

Funding

National Natural Science Foundation of China 82403159
6 · The paper itself

Abstract

backgroundClinical skills training in surgical clerkships relies heavily on faculty supervision, yet traditional models often face time constraints, lack of individualized guidance, and the inability to provide timely feedback. Technology-enhanced, learner-centred approaches, such as video-based self-directed systems, may help address these limitations. The Self-directed Teaching System (SDTS) integrates multi-angle video recording, self-paced practice, and structured feedback to support autonomous learning, but its effectiveness compared with that of conventional instructor-led teaching remains unclear.

objectiveThis randomized controlled trial aimed to (1) evaluate the effectiveness and efficiency of SDTS versus traditional teaching in training basic surgical skills and (2) compare three SDTS feedback modalities (self-, peer-, and instructor-feedback) in influencing learning outcomes.

methodsSixty-two surgical interns were randomized to either a traditional teaching group (fixed 3-hour session with real-time faculty guidance) or an SDTS group (self-directed practice with multi-angle video recording and delayed feedback). Within the SDTS arm, participants were further randomized into self-feedback (n = 10), peer-feedback (n = 10), or instructor-feedback (n = 11) subgroups. All students completed pre- and post-training Objective Structured Clinical Examinations (OSCEs) on two skills: incision/suturing and suture removal/dressing change. Total training duration for the SDTS group, including video learning, practice, and feedback activities, was logged through the backend system data.

resultsFifty-six interns completed the full protocol. For incision and suturing, SDTS shows no statistical difference compared with traditional teaching (P > 0.05). However, for suture removal/dressing change, a more complex, step-intensive procedure, the traditional group scored significantly higher than SDTS group (P < 0.05). Despite this, SDTS participants required substantially less total training time in both modules. The three SDTS feedback subgroups demonstrated no statistical differences in post-training OSCE performance. Learners reported high levels of satisfaction with the video-based feedback process and perceived improvement in procedural skills.

conclusionsThe SDTS provides a flexible, technology-supported approach to surgical skills training and can deliver learning outcomes comparable to traditional methods for basic procedures while enabling more flexible use of training time. However, for more complex tasks, fully self-regulated practice without the required minimum training time may risk premature disengagement, before participants could fully refine their skills. While the feedback modality did not significantly impact outcomes, studies with a larger sample size are needed to verify subgroup effects. The SDTS shows strong potential as a scalable, learner-centred model for clinical education.

Indexed as

Clinical CompetenceFormative FeedbackGeneral SurgeryInternship and ResidencyVideo RecordingAdultFeedbackFemaleHumansMaleTeachingSelf-Determination TheorySelf-directed Teaching SystemSelf-Regulated LearningSurgical Skills TrainingVideo Analysis Feedback

Identifiers

PMID41937174
PMCPMC13217737

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Registered trials

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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.