Evidence map›Paper›PMID 41137046›Full record

Trial reportBMC medical education2025

Group competition mechanism in surgical robot training: a randomized controlled trial.

Huiqin Zhou, Liyuan Huang, Yuanzhuo Du, Jonathan Lio, Bin Luo, Xingyuan Xiao, Kun Yang

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC medical education, 2025. 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

7 authors.

Huiqin Zhou *Department of Urology, Zhongnan Hospital, Wuhan University, 169 Donghu Road, Wuhan, Hubei, 430071, China.
Liyuan Huang *First Clinical Medical School, Kunming Medical University, Kunming, Yunnan, China.
Yuanzhuo DuDepartment of Urology, Zhongnan Hospital, Wuhan University, 169 Donghu Road, Wuhan, Hubei, 430071, China.
Jonathan LioDepartment of Medicine, University of Chicago, Chicago, United States.
Bin LuoMedicine-Remote Mapping Associated Laboratory, Wuhan University, Wuhan, Hubei, China.
Xingyuan XiaoDepartment of Urology, Zhongnan Hospital, Wuhan University, 169 Donghu Road, Wuhan, Hubei, 430071, China. xiaoxingyuan@whu.edu.cn.
Kun YangDepartment of Urology, Zhongnan Hospital, Wuhan University, 169 Donghu Road, Wuhan, Hubei, 430071, China. jesuisking198411@hotmail.com.

Funding

Key Research Planning Project , China Association of Higher Education 24KC0303
6 · The paper itself

Abstract

backgroundLimited training equipment and instructors at training centers cannot fulfill the simultaneous training required of numerous trainees. Optimizing the training organization can improve the training efficiency and trainee performance to enhance the overall training effectiveness. This study aims to evaluate the effectiveness and feasibility of group competition mechanism under peer evaluation during robot training.

methodsA randomized controlled trial was conducted with 60 robotic-naive medical students, divided into two groups: independent training and team-based learning with a competitive element. Both groups performed Pick-and-Place (PP), Match-Board-2 (MB), and Thread-the-Rings-1 (TR) tasks on a dV-Trainer robot simulator. Training scores were automatically recorded to construct learning curves and calculate scoring efficiencies, which were compared between the two groups.

resultsCompared with the conventional training group, the group utilizing the group competition training format demonstrated significantly higher average operational scores, scoring efficiency, and learning curves (P < 0.05). In addition, the group competition mode demonstrates a higher performance in cultivating the trainees' satisfactory operational habits (P < 0.001).

conclusionsBased on task-reporting strategies guided by peer evaluation, the group competition mechanism is a novel and effective model for improving robot simulator training. This method holds promise as an effective tool for the surgical education of practicing surgeons and clinical medical students.

Indexed as

Competitive BehaviorRobotic Surgical ProceduresSimulation TrainingAdultClinical CompetenceFemaleHumansLearning CurveMaleStudents, MedicalYoung AdultGroup competitionPeer evaluationRobot simulatorRobot training

Identifiers

PMID41137046
PMCPMC12551284

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.