沉浸式虚拟现实中的大规模伤亡事件培训:多方法绩效指标的准实验评估
Mass Casualty Incident Training in Immersive Virtual Reality: Quasi-Experimental Evaluation of Multimethod Performance Indicators.
作者信息
Baetzner Anke Sabine, Hill Yannick, Roszipal Benjamin, Gerwann Solène, Beutel Matthias, Birrenbach Tanja, Karlseder Markus, Mohr Stefan, Salg Gabriel Alexander, Schrom-Feiertag Helmut, Frenkel Marie Ottilie, Wrzus Cornelia
机构信息
Institute of Sports and Sports Sciences, Heidelberg University, Heidelberg, Germany.
Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
出版信息
J Med Internet Res. 2025 Jan 27;27:e63241. doi: 10.2196/63241.
BACKGROUND
Immersive virtual reality (iVR) has emerged as a training method to prepare medical first responders (MFRs) for mass casualty incidents (MCIs) and disasters in a resource-efficient, flexible, and safe manner. However, systematic evaluations and validations of potential performance indicators for virtual MCI training are still lacking.
OBJECTIVE
This study aimed to investigate whether different performance indicators based on visual attention, triage performance, and information transmission can be effectively extended to MCI training in iVR by testing if they can discriminate between different levels of expertise. Furthermore, the study examined the extent to which such objective indicators correlate with subjective performance assessments.
METHODS
A total of 76 participants (mean age 25.54, SD 6.01 y; 45/76, 59% male) with different medical expertise (MFRs: paramedics and emergency physicians; non-MFRs: medical students, in-hospital nurses, and other physicians) participated in 5 virtual MCI scenarios of varying complexity in a randomized order. Tasks involved assessing the situation, triaging virtual patients, and transmitting relevant information to a control center. Performance indicators included eye-tracking-based visual attention, triage accuracy, triage speed, information transmission efficiency, and self-assessment of performance. Expertise was determined based on the occupational group (39/76, 51% MFRs vs 37/76, 49% non-MFRs) and a knowledge test with patient vignettes.
RESULTS
Triage accuracy (d=0.48), triage speed (d=0.42), and information transmission efficiency (d=1.13) differentiated significantly between MFRs and non-MFRs. In addition, higher triage accuracy was significantly associated with higher triage knowledge test scores (Spearman ρ=0.40). Visual attention was not significantly associated with expertise. Furthermore, subjective performance was not correlated with any other performance indicator.
CONCLUSIONS
iVR-based MCI scenarios proved to be a valuable tool for assessing the performance of MFRs. The results suggest that iVR could be integrated into current MCI training curricula to provide frequent, objective, and potentially (partly) automated performance assessments in a controlled environment. In particular, performance indicators, such as triage accuracy, triage speed, and information transmission efficiency, capture multiple aspects of performance and are recommended for integration. While the examined visual attention indicators did not function as valid performance indicators in this study, future research could further explore visual attention in MCI training and examine other indicators, such as holistic gaze patterns. Overall, the results underscore the importance of integrating objective indicators to enhance trainers' feedback and provide trainees with guidance on evaluating and reflecting on their own performance.
背景
沉浸式虚拟现实(iVR)已成为一种培训方法,能以资源高效、灵活且安全的方式让医疗急救人员(MFR)为应对大规模伤亡事件(MCI)和灾难做好准备。然而,对于虚拟MCI培训潜在性能指标的系统评估和验证仍很缺乏。
目的
本研究旨在通过测试基于视觉注意力、分诊表现和信息传递的不同性能指标能否区分不同专业水平,来探究其是否能有效扩展到iVR中的MCI培训。此外,该研究还考察了此类客观指标与主观性能评估的相关程度。
方法
共有76名参与者(平均年龄25.54岁,标准差6.01岁;45/76,59%为男性),他们具有不同的医学专业知识(MFR:护理人员和急诊医生;非MFR:医学生、住院护士和其他医生),以随机顺序参与了5个不同复杂程度的虚拟MCI场景。任务包括评估情况、对虚拟患者进行分诊以及向控制中心传递相关信息。性能指标包括基于眼动追踪的视觉注意力、分诊准确性、分诊速度、信息传递效率以及自我性能评估。专业知识根据职业群体(39/76,51%为MFR对37/76,49%为非MFR)以及患者病例知识测试来确定。
结果
MFR和非MFR之间在分诊准确性(d = 0.48)、分诊速度(d = 0.42)和信息传递效率(d = 1.13)方面存在显著差异。此外,更高的分诊准确性与更高的分诊知识测试分数显著相关(斯皮尔曼ρ = 0.40)。视觉注意力与专业知识无显著关联。此外,主观性能与任何其他性能指标均无相关性。
结论
基于iVR的MCI场景被证明是评估MFR性能的有价值工具。结果表明,iVR可整合到当前的MCI培训课程中,以便在可控环境中提供频繁、客观且可能(部分)自动化的性能评估。特别是,分诊准确性、分诊速度和信息传递效率等性能指标涵盖了性能的多个方面,建议予以整合。虽然本研究中所考察的视觉注意力指标未起到有效的性能指标作用,但未来研究可进一步探索MCI培训中的视觉注意力,并考察其他指标,如整体注视模式。总体而言,结果强调了整合客观指标以增强培训师反馈并为学员提供评估和反思自身性能指导的重要性。