Evidence map›Paper›PMID 41209462›Full record

ArticleFrontiers in veterinary science2025

Anatomy of meat cuts: integrating 3D scanning and virtual reality in veterinary education and training.

Nedžad Hadžiomerović, Kenan Čaklovica, Nejra Dučić, Migena Gjoni Gündemir, Anel Vejzović, Neira Fazlović, Rizah Avdić, Faruk Čaklovica, Faruk Tandir

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Nedžad HadžiomerovićDepartment of Basic Sciences of Veterinary Medicine, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Kenan ČaklovicaDepartment of Food Safety and Environmental Protection, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Nejra DučićDepartment of Basic Sciences of Veterinary Medicine, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Migena Gjoni GündemirInstitute of Graduate Studies, İstanbul University-Cerrahpaşa, İstanbul, Türkiye.
Anel VejzovićDepartment of Basic Sciences of Veterinary Medicine, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Neira FazlovićDepartment of Food Safety and Environmental Protection, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Rizah AvdićDepartment of Basic Sciences of Veterinary Medicine, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Faruk ČaklovicaDepartment of Food Safety and Environmental Protection, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.
Faruk TandirDepartment of Basic Sciences of Veterinary Medicine, University of Sarajevo-Veterinary Faculty, Sarajevo, Bosnia and Herzegovina.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding meat categorization is a fundamental component of veterinary education, especially within the context of food hygiene and public health. Veterinary students must grasp legal classifications of meat, which depend on variables such as species, age, quality, and processing techniques. This knowledge is essential for accurate meat inspection, labeling, and compliance with both national and international food safety standards. Despite prior exposure to muscle anatomy in anatomy course, students often face challenges in applying this knowledge to practical meat classification tasks. This study aimed to assess the effectiveness of three distinct instructional methods in improving veterinary students' ability to identify meat categories and associated muscle structures: traditional classroom teaching, computer-based instruction using 3D models, and immersive virtual reality (VR). Participants included fourth-year veterinary students during the summer semester of the 2024/2025 academic year. To facilitate digital learning, a dedicated 3D model library "3DMeat" was developed as well as virtual reality environment. Results indicate that technology-enhanced instructional approaches, can significantly enhance student engagement and understanding of complex topics such as meat categorization. Initial test scores were highest in the group using 3D models (16.3 ± 4.1), followed by the traditional lecture-based group (15.6 ± 3.07), and the VR group (11.7 ± 5.1). However, a follow-up assessment conducted 2 weeks later revealed that VR group demonstrated the highest retention of knowledge. These findings suggest that although immediate performance may vary, immersive learning environments such as VR can foster stronger medium-term retention of complex material.

Indexed as

digital toolsimmersive technologyinteractive learningmuscle structureskill development

Identifiers

PMID41209462
PMCPMC12590504

What OpenQuestion holds

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LicenceCC BY
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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.