Back to Search Start Over

Extended reality as a training method for medical first responders in mass casualty incidents: A protocol for a systematic review.

Authors :
Lucía Otero-Varela
Ana María Cintora
Salvador Espinosa
María Redondo
Miriam Uzuriaga
Myriam González
Mario García
Jessica Naldrett
Juan Alonso
Tatiana Vazquez
Alberto Blanco
María Del Carmen Cardós Alonso
Source :
PLoS ONE, Vol 18, Iss 3, p e0282698 (2023)
Publication Year :
2023
Publisher :
Public Library of Science (PLoS), 2023.

Abstract

Introduction/backgroundMass-casualty incidents (MCIs) and disasters require an organised and effective response from medical first responders (MFRs). As such, novel training methods have emerged to prepare and adequately train MFRs for these challenging situations. Particular focus should be placed on extended reality (XR), which encompasses virtual, augmented and mixed reality (VR, AR, and MR, respectively), and allows participants to develop high-quality skills in realistic and immersive environments. Given the rapid evolution of high-fidelity simulation technology and its advantages, XR simulation has become a promising tool for emergency medicine. Accordingly, this systematic review aims to: 1) evaluate the effectiveness of XR training methods and 2) explore the experience of MFRs undergoing such training.MethodsA comprehensive search strategy will encompass four distinct themes: MFRs, disasters/MCIs, education and simulation, and XR. Four databases (MEDLINE, EMBASE, CINAHL and LILACs) will be searched along with an in-depth examination of the grey literature and reference lists of relevant articles. MetaQAT will be used as a study quality assessment tool and integrated into Covidence as part of the data extraction form. Given the predicted high heterogeneity between studies, it may not be possible to standardise data for quantitative comparison and meta-analysis. Thus, data will be synthesised in a narrative, semi-quantitative manner.DiscussionThis review will examine the existing literature on the effectiveness of XR simulation as a tool to train MFRs for MCIs, which could ultimately improve preparedness and response to disasters.Trial registrationProtocol registration: PROSPERO CRD42021275692.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
18
Issue :
3
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.b9ec0f0eaf1f43e3b106533e51db6f60
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0282698