Evidence map›Paper›PMID 40275224›Full record

ArticleBMC medical education2025

Network analysis of an OSCE-based graduation skills assessment for clinical medical students.

Huiqun Zhang, Shanshan Li, Guoquan Zheng, Xiaoyun Chen, Lujie Zhong, Jiaying Li, Yun Li

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

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4 · The record

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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.

Huiqun ZhangPractical Teaching Center, Guangzhou Medical University, Guangzhou, 511436, China.
Shanshan LiAcademic Affairs Office, Guangzhou Medical University, Guangzhou, 511436, China.
Guoquan ZhengAcademic Affairs Office, Guangzhou Medical University, Guangzhou, 511436, China.
Xiaoyun ChenPractical Teaching Center, Guangzhou Medical University, Guangzhou, 511436, China.
Lujie ZhongSchool of Health Management, Guangzhou Medical University, Guangzhou, 511436, China.
Jiaying LiSchool of Health Management, Guangzhou Medical University, Guangzhou, 511436, China.
Yun LiSchool of Health Management, Guangzhou Medical University, Guangzhou, 511436, China. liyun@gzhmu.edu.cn.

Funding

2021 Guangdong Provincial Higher Education Teaching Reform Project of Undergraduate Colleges and Universities "Research on the Reform of Ability-oriented Clinical Internship Exit Assessment and Evaluation" 462Guangzhou Educational Science Planning 2021 Project "Practical Research on Online and Offline Blended Teaching in Clinical Skills" 202113657The 2023 Guangdong Basic and Applied Basic Research Foundation 2023A1515110350The 2023 Ministry of Education Industry-Education Cooperation Collaborative Education Project 230806052074117The 2024 Youth Project of Guangdong Philosophy and Social Sciences Planning Project GD24YXL06The Plan on enhancing scientific research in GMU 02-410-2302338XM
6 · The paper itself

Abstract

backgroundThis study investigates OSCE performance among Chinese undergraduate medical students to identify differences and analyze the interconnections among OSCE modules. Employing network analysis, we map the relationships between modules to determine their predictive strength and centrality to overall clinical competence, offering a novel perspective on skill integration and curriculum design.

methodsAnalyzing data from 3,710 students across three medical specialities (clinical medicine, anesthesiology, medical imaging) from a leading medical institution in Guangzhou, China (Grade 2011-2016), and the independent samples t-tests, analysis of variance (ANOVA), Pearson's correlation, and network analysis were employed to dissect performance trends, compare demographic group differences, and unearth the correlations among the examination modules.

resultsSignificant differences were identified between genders, with female students consistently outperforming male students across modules and overall scores except for auxiliary examination analysis. Besides, specialities differed significantly in physical examination, basic operational skills, auxiliary examination analysis, and case analysis. Network analysis revealed that the nodes "Pediatric Skills" and "Nursing Skill" exhibit the strongest linkage, closely followed by "Cardiac Auscultation" and "Pulmonary Auscultation". "General Physical Examination" is the most influential, with "Pediatric Skills" and "Gynecological Obstetrical Skills" also prominent.

conclusionFrom the perspective of medical education reform, reinforcing core skills like "General Physical Examination" and integrating modules to enhance skill synergy is pivotal. Implementing targeted educational interventions, including advanced training and clinical practice courses, will not only address performance disparities but also bolster students' clinical acumen and communication skills, laying a robust foundation for superior patient care. The network analysis approach reveals how module performances interrelate, highlighting central modules whose improvement can boost related competencies. It complements traditional statistics, visualizing these relationships to inform OSCE reforms and enrich medical education.

Indexed as

Clinical CompetenceEducational MeasurementEducation, Medical, UndergraduateStudents, MedicalChinaCurriculumFemaleHumansMaleClinical skillsMedical educationMedical studentsNetwork analysisOSCE

Identifiers

PMID40275224
PMCPMC12023391

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.