The Application Effect of 3D Body Technology in the Teaching of Anesthesiology Interns: A Randomized Controlled Study

Journal: Journal of Higher Education Research DOI: 10.32629/jher.v6i2.3807

Junkai Hou1, Yifang Shui2

1. Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
2. Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China

Abstract

Anesthesiology requires strong anatomical knowledge and operational skills. Traditional 2D teaching methods struggle to display complex 3D structures, hindering theory-to-practice transitions. This study introduced 3D Body technology, using high-precision models and interactive operations to visually demonstrate airways, nerves, and vessels, improving understanding. A randomized trial divided 20 anesthesiology interns into experimental (3D Body) and control (traditional) groups. Results showed the experimental group significantly outperformed in anatomical visualization, operational skills, learning interest, and clinical thinking (P<0.05). Students found 3D Body more intuitive and engaging, while the control group saw limited improvement. 3D Body addresses traditional limitations, enhances clinical training, and supports medical education innovation, with potential for broader application.

Keywords

3D Body technology, anesthesiology teaching, anatomical structure visualization, operational skill training, learning interest stimulation

References

[1] CHEN C, YANG S, XIONG X, et al. Enhancing Anesthesia Education and Clinical Practice: A Comprehensive Review of GASMAN Simulation Software . Journal of medical education and curricular development, 2024, 11: 1-6.
[2] Wang JZ, Lillia J, Kumar A, Bray P, Kim J, Burns J, Cheng TL. Clinical applications of machine learning in predicting 3D shapes of the human body: a systematic review[J]. BMC Bioinformatics. 2022,23(1):431.
[3] YAHIRO D S, CRUZ M P, RIBEIRO B F C, et al. Impact of 3D Printing on Cardiac Surgery in Congenital Heart Diseases: A Systematic Review and Meta-Analysis [J]. Arquivos brasileiros de cardiologia, 2024, 121(12): e20240430.

Copyright © 2025 Junkai Hou, Yifang Shui

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