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针对道路交通事故的医疗急救教育中由教师主导的虚拟现实培训:一项基于问卷调查的研究

Instructor-Led VR training in medical emergency rescue education for road traffic accidents: a questionnaire-based study.

作者信息

Li Zhe, Qiu Guozheng, Chen Wan, Shi Lei, Tang Yutao, Qin Guoqing, Mo Jingshu, Lyu Liwen

机构信息

Department of Emergency, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, 530021, China.

出版信息

Sci Rep. 2025 Aug 12;15(1):29558. doi: 10.1038/s41598-025-15258-4.


DOI:10.1038/s41598-025-15258-4
PMID:40796635
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12343776/
Abstract

The application of Virtual Reality (VR) in medical emergency training, particularly in road traffic accident (RTA) management, remains underexplored. While VR offers immersive and dynamic learning environments, the effectiveness of instructor-led VR training in large-scale, emergency medical education is not yet fully understood. This study aimed to evaluate the effectiveness of instructor-led virtual reality (VR) training in medical emergency rescue education, particularly in the context of road traffic accidents. Effectiveness was assessed through participant satisfaction, perceived engagement, and self-reported learning outcomes. A cross-sectional survey was conducted among 300 emergency medical professionals who attended one-hour instructor-led VR sessions delivered through a series of workshops. Participants completed a post-training questionnaire consisting of Likert-scale items assessing course design, content practicality, clarity of instruction, VR interest, and overall satisfaction. Quantitative data were analyzed using regression and mediation analyses to identify the predictors of overall evaluation scores. Regression analysis identified course practicality (Estimate = 0.131, P < 0.001) and VR interest (Estimate = 0.357, P < 0.001) as the strongest predictors of overall satisfaction. Mediation analysis revealed that the effect of course practicality on satisfaction was partially mediated by VR interest (mediation effect = 32.5%). Participants consistently rated the sessions highly, with an overall evaluation score of 4.82 ± 0.35 out of 5. Sentiment analysis of 227 qualitative responses indicated 70.67% expressed positive opinions, particularly on the engaging and practical aspects of the VR-based approach. While the findings support the potential of instructor-led VR to enhance learner engagement and comprehension in high-stakes scenarios, limitations include the cross-sectional design and lack of long-term follow-up. Instructor-led VR training appears to be a practical, engaging, and scalable method for emergency medical education. Future research should assess its long-term impact on skill retention and real-world application.

摘要

虚拟现实(VR)在医疗急救培训中的应用,尤其是在道路交通事故(RTA)管理方面,仍未得到充分探索。虽然VR提供了沉浸式和动态的学习环境,但在大规模的紧急医疗教育中,由教师主导的VR培训的有效性尚未得到充分理解。本研究旨在评估由教师主导的虚拟现实(VR)培训在医疗急救教育中的有效性,特别是在道路交通事故的背景下。通过参与者满意度、感知参与度和自我报告的学习成果来评估有效性。对300名参加了通过一系列工作坊进行的一小时教师主导VR课程的紧急医疗专业人员进行了横断面调查。参与者完成了一份培训后问卷,其中包括李克特量表项目,用于评估课程设计、内容实用性、教学清晰度、VR兴趣和总体满意度。使用回归和中介分析对定量数据进行分析,以确定总体评估分数的预测因素。回归分析确定课程实用性(估计值=0.131,P<0.001)和VR兴趣(估计值=0.357,P<0.001)是总体满意度的最强预测因素。中介分析表明,课程实用性对满意度的影响部分由VR兴趣介导(中介效应=32.5%)。参与者对课程的评价一直很高,总体评估分数为4.82±0.35(满分5分)。对227条定性回复的情感分析表明,70.67%的人表达了积极意见,特别是对基于VR的方法的参与性和实用性方面。虽然研究结果支持教师主导的VR在高风险场景中提高学习者参与度和理解能力的潜力,但局限性包括横断面设计和缺乏长期随访。教师主导的VR培训似乎是一种实用、引人入胜且可扩展的紧急医疗教育方法。未来的研究应评估其对技能保留和实际应用的长期影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/3c273786a9f1/41598_2025_15258_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/e7a38d1a27d2/41598_2025_15258_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/14ff108485ea/41598_2025_15258_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/9a5873d311f3/41598_2025_15258_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/c661fa79115e/41598_2025_15258_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/3c273786a9f1/41598_2025_15258_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/e7a38d1a27d2/41598_2025_15258_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/14ff108485ea/41598_2025_15258_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/9a5873d311f3/41598_2025_15258_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/c661fa79115e/41598_2025_15258_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3964/12343776/3c273786a9f1/41598_2025_15258_Fig5_HTML.jpg

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本文引用的文献

[1]
IoT-Driven Skin Cancer Detection: Active Learning and Hyperparameter Optimization for Enhanced Accuracy.

IEEE J Biomed Health Inform. 2025-6-10

[2]
Interprofessional Team Training With Virtual Reality: Acceptance, Learning Outcome, and Feasibility Evaluation Study.

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[3]
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Disaster Med Public Health Prep. 2024-10-28

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West J Emerg Med. 2024-9

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BMC Med Educ. 2024-7-18

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J Clin Periodontol. 2024-11

[10]
Exploring a GPT-based large language model for variable autonomy in a VR-based human-robot teaming simulation.

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