Using High-Fidelity Virtual Reality for Mass-Casualty Incident Training by First Responders - A Systematic Review of the Literature.
Аннотация
INTRODUCTION
First responders' training and learning regarding how to handle a mass-casualty incident (MCI) is traditionally based on reading and/or training through computer-based scenarios, or sometimes through live simulations with actors. First responders should practice in realistic environments to narrow the theory-practice gap, and the possibility of repeating the training is important for learning. High-fidelity virtual reality (VR) is a promising tool to use for realistic and repeatable simulation training, but it needs to be further evaluated. The aim of this literature review was to provide a comprehensive description of the use of high-fidelity VR for MCI training by first responders.
METHODS
A systematic integrative literature review was used according to Whittemore and Knafl's descriptions. Databases investigated were PubMed, CINAHL Complete, Academic Search Ultimate, Web of Science, and ERIC to find papers addressing the targeted outcome. The electronic search strategy identified 797 potential studies. Seventeen studies were deemed eligible for final inclusion.
RESULTS
Training with VR enables repetition in a way not possible with live simulation, and the realism is similar, yet not as stressful. Virtual reality offers a cost-effective and safe learning environment. The usability of VR depends on the level of immersion, the technology being error-free, and the ease of use.
CONCLUSIONS
This integrative review shows that high-fidelity VR training should not rule out live simulation, but rather serve as a complement. First responders became more confident and prepared for real-life MCIs after training with high-fidelity VR, but efforts should be made to solve the technical issues found in this review to further improve the usability.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
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.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.