Evidence map›Paper›PMID 40909242›Full record

ArticleFrontiers in surgery2025

Application of a hybrid virtual-physical teaching model integrating mixed reality and 3D printing in clinical joint orthopedic education.

Honglin Wang, Aoshuang Xu, Wei Hua, Zhewei Ye, Lin Lu

Abstract read
In one paragraph

Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Honglin Wang *Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.
Aoshuang Xu *Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wei HuaDepartment of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.
Zhewei YeDepartment of Orthopaedic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lin LuDepartment of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The diagnosis and treatment of arthropathic orthopaedic conditions are inherently linked to anatomical structures, necessitating strong spatial visualization abilities in students. Providing intuitively accessible methods for students to master specialized knowledge presents a formidable challenge for educators. This study aims to evaluate the pedagogical value of integrating 3D-printed model with mixed reality (MR) technology in clinical orthopaedic surgery education. Methods: Thirty-six senior clinical medical undergraduates were randomized into two groups. The experimental group underwent training using the combined 3D- printed model and mixed reality (MR) technology, while the control group received traditional instruction. Learning outcomes were evaluated through standardized Objective Structured Clinical Examination (OSCE) assessments and questionnaires. Correlation analysis was conducted between total OSCE scores and questionnaire scores. Results: The experimental group achieved significantly higher OSCE scores compared to the control group ( Conclusion: Integrating 3D-printed model and MR technology into orthopedic joint surgery clinical teaching significantly boosts student performance, learning efficiency, and overall teaching quality, demonstrating strong potential for wider application.

Indexed as

3D-printed modeljoint surgery educationmedical undergraduatesmixed reality (MR)teaching modevirtual-physical integration

Identifiers

PMID40909242
PMCPMC12405172

What OpenQuestion holds

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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.