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The development of new remote technologies in disaster medicine education: A scoping review
BACKGROUND: Remote teaching and online learning have significantly changed the responsiveness and accessibility after the COVID-19 pandemic. Disaster medicine (DM) has recently gained prominence as a critical issue due to the high frequency of worldwide disasters, especially in 2021. The new artific...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080133/ https://www.ncbi.nlm.nih.gov/pubmed/37033011 http://dx.doi.org/10.3389/fpubh.2023.1029558 |
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author | Kao, Chia-Lung Chien, Li-Chien Wang, Mei-Chin Tang, Jing-Shia Huang, Po-Chang Chuang, Chia-Chang Shih, Chung-Liang |
author_facet | Kao, Chia-Lung Chien, Li-Chien Wang, Mei-Chin Tang, Jing-Shia Huang, Po-Chang Chuang, Chia-Chang Shih, Chung-Liang |
author_sort | Kao, Chia-Lung |
collection | PubMed |
description | BACKGROUND: Remote teaching and online learning have significantly changed the responsiveness and accessibility after the COVID-19 pandemic. Disaster medicine (DM) has recently gained prominence as a critical issue due to the high frequency of worldwide disasters, especially in 2021. The new artificial intelligence (AI)-enhanced technologies and concepts have recently progressed in DM education. OBJECTIVES: The aim of this article is to familiarize the reader with the remote technologies that have been developed and used in DM education over the past 20 years. LITERATURE SCOPING REVIEWS: Mobile edge computing (MEC), unmanned aerial vehicles (UAVs)/drones, deep learning (DL), and visual reality stimulation, e.g., head-mounted display (HMD), are selected as promising and inspiring designs in DM education. METHODS: We performed a comprehensive review of the literature on the remote technologies applied in DM pedagogy for medical, nursing, and social work, as well as other health discipline students, e.g., paramedics. Databases including PubMed (MEDLINE), ISI Web of Science (WOS), EBSCO (EBSCO Essentials), Embase (EMB), and Scopus were used. The sourced results were recorded in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart and followed in accordance with the PRISMA extension Scoping Review checklist. We included peer-reviewed articles, Epubs (electronic publications such as databases), and proceedings written in English. VOSviewer for related keywords extracted from review articles presented as a tabular summary to demonstrate their occurrence and connections among these DM education articles from 2000 to 2022. RESULTS: A total of 1,080 research articles on remote technologies in DM were initially reviewed. After exclusion, 64 articles were included in our review. Emergency remote teaching/learning education, remote learning, online learning/teaching, and blended learning are the most frequently used keywords. As new remote technologies used in emergencies become more advanced, DM pedagogy is facing more complex problems. DISCUSSIONS: Artificial intelligence-enhanced remote technologies promote learning incentives for medical undergraduate students or graduate professionals, but the efficacy of learning quality remains uncertain. More blended AI-modulating pedagogies in DM education could be increasingly important in the future. More sophisticated evaluation and assessment are needed to implement carefully considered designs for effective DM education. |
format | Online Article Text |
id | pubmed-10080133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100801332023-04-08 The development of new remote technologies in disaster medicine education: A scoping review Kao, Chia-Lung Chien, Li-Chien Wang, Mei-Chin Tang, Jing-Shia Huang, Po-Chang Chuang, Chia-Chang Shih, Chung-Liang Front Public Health Public Health BACKGROUND: Remote teaching and online learning have significantly changed the responsiveness and accessibility after the COVID-19 pandemic. Disaster medicine (DM) has recently gained prominence as a critical issue due to the high frequency of worldwide disasters, especially in 2021. The new artificial intelligence (AI)-enhanced technologies and concepts have recently progressed in DM education. OBJECTIVES: The aim of this article is to familiarize the reader with the remote technologies that have been developed and used in DM education over the past 20 years. LITERATURE SCOPING REVIEWS: Mobile edge computing (MEC), unmanned aerial vehicles (UAVs)/drones, deep learning (DL), and visual reality stimulation, e.g., head-mounted display (HMD), are selected as promising and inspiring designs in DM education. METHODS: We performed a comprehensive review of the literature on the remote technologies applied in DM pedagogy for medical, nursing, and social work, as well as other health discipline students, e.g., paramedics. Databases including PubMed (MEDLINE), ISI Web of Science (WOS), EBSCO (EBSCO Essentials), Embase (EMB), and Scopus were used. The sourced results were recorded in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart and followed in accordance with the PRISMA extension Scoping Review checklist. We included peer-reviewed articles, Epubs (electronic publications such as databases), and proceedings written in English. VOSviewer for related keywords extracted from review articles presented as a tabular summary to demonstrate their occurrence and connections among these DM education articles from 2000 to 2022. RESULTS: A total of 1,080 research articles on remote technologies in DM were initially reviewed. After exclusion, 64 articles were included in our review. Emergency remote teaching/learning education, remote learning, online learning/teaching, and blended learning are the most frequently used keywords. As new remote technologies used in emergencies become more advanced, DM pedagogy is facing more complex problems. DISCUSSIONS: Artificial intelligence-enhanced remote technologies promote learning incentives for medical undergraduate students or graduate professionals, but the efficacy of learning quality remains uncertain. More blended AI-modulating pedagogies in DM education could be increasingly important in the future. More sophisticated evaluation and assessment are needed to implement carefully considered designs for effective DM education. Frontiers Media S.A. 2023-03-24 /pmc/articles/PMC10080133/ /pubmed/37033011 http://dx.doi.org/10.3389/fpubh.2023.1029558 Text en Copyright © 2023 Kao, Chien, Wang, Tang, Huang, Chuang and Shih. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Kao, Chia-Lung Chien, Li-Chien Wang, Mei-Chin Tang, Jing-Shia Huang, Po-Chang Chuang, Chia-Chang Shih, Chung-Liang The development of new remote technologies in disaster medicine education: A scoping review |
title | The development of new remote technologies in disaster medicine education: A scoping review |
title_full | The development of new remote technologies in disaster medicine education: A scoping review |
title_fullStr | The development of new remote technologies in disaster medicine education: A scoping review |
title_full_unstemmed | The development of new remote technologies in disaster medicine education: A scoping review |
title_short | The development of new remote technologies in disaster medicine education: A scoping review |
title_sort | development of new remote technologies in disaster medicine education: a scoping review |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080133/ https://www.ncbi.nlm.nih.gov/pubmed/37033011 http://dx.doi.org/10.3389/fpubh.2023.1029558 |
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