To address elevated risk for older pilots, we examined the efficacy of a virtual reality (VR) cognitive health screening tool (integrated into simulated flight scenarios) in identifying general aviation pilots who experienced a critical incident during flight in a full-scale Cessna 172 simulator. Performance data were obtained from 51 certified pilots (17–71 years). Machine learning classification algorithms, based on key data from the VR flight, were used to validate the utility of the screening tool for identifying pilot risk. The results showed that aviation-relevant cognitive factors obtained in the VR screening tool, including situation awareness and prospective memory, predicted risk of a critical incident with good sensitivity (0.83) and specificity (0.85), AUC = 0.82. These results support VR-based cognitive screening to identify at-risk older pilots. The present findings inform procedures for optimizing safety and reducing critical incidents at any point in the pilot lifespan and are timely in view of the impending pilot workforce shortage.

为了解决老年飞行员风险升高的问题，我们研究了虚拟现实 (VR) 认知健康筛查工具（集成到模拟飞行场景中）在识别在全尺寸 Cessna 172 模拟器中飞行期间遇到严重事故的通用航空飞行员的功效. 绩效数据来自 51 名经过认证的飞行员（17-71 岁）。机器学习分类算法基于 VR 飞行的关键数据，用于验证筛选工具在识别飞行员风险方面的效用。结果表明，在 VR 筛选工具中获得的与航空相关的认知因素，包括态势感知和前瞻性记忆，以良好的敏感性 (0.83) 和特异性 (0.85) 预测危急事件的风险，AUC = 0.82。这些结果支持基于 VR 的认知筛查来识别有风险的老年飞行员。目前的调查结果为在飞行员生命周期的任何时候优化安全和减少关键事故的程序提供了信息，并且鉴于即将到来的飞行员劳动力短缺是及时的。