Resuscitation plus · 2026
Nighttime human-supervised drone-delivered automated external defibrillators: a quasi-experimental mixed-methods feasibility study.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chan C K J, Ho S Y J, Yip A, Tung F L N
Аннотация
AIM: To evaluate the feasibility, safety, and operational challenges of human-supervised flight drone-delivered automated external defibrillator (AED) operations during nighttime for out-of-hospital cardiac arrest (OHCA), using a convergent mixed-methods design integrating quantitative performance metrics with qualitative human factors analysis.
METHODS: A quasi-experimental study with 24 controlled flights (12 daytime, 12 nighttime) was conducted in a semi-urban area using a DJI M30T drone carrying a lightweight CellAED (480 g) over 877 m. Advanced-rated paramedic drone pilots executed human-supervised flight flights under extended visual line of sight (EVLOS), using automated waypoint navigation and manual final approach and landing. protocols. Quantitative data included flight times and safety incidents, analyzed using paired t-tests. Qualitative data from semi-structured pilot interviews were analyzed thematically using the SHELL (Software-Hardware-Environment-Liveware-Liveware) human factors framework. Integration occurred through convergent triangulation comparing quantitative duration metrics with pilot-reported operational themes.
RESULTS: All 24 flights completed successfully without safety incidents or obstacle-avoidance triggers. Mean flight times were comparable (day: 136.00 ± 8.71 s vs. night: 139.92 ± 14.16 s; paired mean difference 3.92 s, S.D. 16.49, p = 0.43, Cohen's d = 0.24). Qualitative analysis identified eight major themes: night-mode interface challenges, GPS routing reliability, infrared sensor performance, pilot fatigue and stress, communication coordination, cognitive workload, landing zone conditions, and regulatory constraints. Triangulation of quantitative and qualitative findings showed that despite comparable flight performance, pilots reported significantly increased cognitive demands and environmental complexity during nighttime operations.
CONCLUSION: Under controlled, early-night, open-area conditions, all human-supervised flight drone-delivered AED operations missions were completed without observed safety incidents. However, successful nighttime implementation requires addressing pilot workload, interface design, and operational protocols. These findings support development of 24/7 drone AED services while highlighting critical human factors considerations for sustainable operations.
METHODS: A quasi-experimental study with 24 controlled flights (12 daytime, 12 nighttime) was conducted in a semi-urban area using a DJI M30T drone carrying a lightweight CellAED (480 g) over 877 m. Advanced-rated paramedic drone pilots executed human-supervised flight flights under extended visual line of sight (EVLOS), using automated waypoint navigation and manual final approach and landing. protocols. Quantitative data included flight times and safety incidents, analyzed using paired t-tests. Qualitative data from semi-structured pilot interviews were analyzed thematically using the SHELL (Software-Hardware-Environment-Liveware-Liveware) human factors framework. Integration occurred through convergent triangulation comparing quantitative duration metrics with pilot-reported operational themes.
RESULTS: All 24 flights completed successfully without safety incidents or obstacle-avoidance triggers. Mean flight times were comparable (day: 136.00 ± 8.71 s vs. night: 139.92 ± 14.16 s; paired mean difference 3.92 s, S.D. 16.49, p = 0.43, Cohen's d = 0.24). Qualitative analysis identified eight major themes: night-mode interface challenges, GPS routing reliability, infrared sensor performance, pilot fatigue and stress, communication coordination, cognitive workload, landing zone conditions, and regulatory constraints. Triangulation of quantitative and qualitative findings showed that despite comparable flight performance, pilots reported significantly increased cognitive demands and environmental complexity during nighttime operations.
CONCLUSION: Under controlled, early-night, open-area conditions, all human-supervised flight drone-delivered AED operations missions were completed without observed safety incidents. However, successful nighttime implementation requires addressing pilot workload, interface design, and operational protocols. These findings support development of 24/7 drone AED services while highlighting critical human factors considerations for sustainable operations.