Development of First Aid Self-learning Web Application for Road Accident Victims

Author:

Pearkao Chatkhane,Potisopha WiphawadeeORCID,Ienghong KamonwonORCID,Cheung Lap WoonORCID,Apiratwarakul KorakotORCID

Abstract

BACKGROUND: Knowledge of prehospital scene care for injured person in road accidents is essential for improving outcome and saving lives of traffic accident victims. However, the situation of the COVID-19 pandemic may cause people’s inability to access in-person first aid training. AIM: This study aimed to determine the effect of first aid self-learning web application for road accident victims on the knowledge and satisfaction of the web application users. METHODS: A prospective, single-arm, and educational cohort study was conducted among second-year physical education participants at Khon Kaen University attending first aid self-learning web application for road accident victims in July 2021. All participants were attended ten lessons covering important content of first aid for an injured person in road accidents. Each lesson includes reading texts, 3-min animation videos, and pre-test and post-test. Data analysis includes a comparison of the pre-test and post-test knowledge scores using the paired t-test. The participant’s satisfaction was analyzed using descriptive statistics. RESULTS: The 42 participants were participated in this study. Sixty-two percent of the participants had no previous first aid experience for an injured person in road accidents. The mean pre-test and post-test scores were 25.31 ± 3.87 and 27.50 ± 2.91, respectively. There was a significant difference between the pre-test and the post-test scores (p < 0.001). The participant’s level of satisfaction score was very good (4.25 ± 0.95). CONCLUSIONS: The first aid self-learning web application significantly improved the first aid knowledge of the web application users. Moreover, most participants reported good level of satisfaction for using this tool. This emphasized that the first aid self-learning web application was the great tool in COVID-19 learning.

Funder

Khon Kaen University

Publisher

Scientific Foundation SPIROSKI

Subject

General Medicine

Reference20 articles.

1. World Health Organization. Road Traffic Injuries. Geneva: World Health Organization. Available from: https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries [Last accessed on 2022 Jan 05].

2. World Health Organization. Global Status Report on Road Safety. Geneva: World Health Organization; 2018. Available from: https://www.who.int/publications/i/item/9789241565684. [Last accessed on 2022 Jan 05].

3. O-Charoen N. Flirting with Road Risk a Fatal Pursuit. Available from: https://tdri.or.th/en/2017/09/flirting-road-risk-fatal-pursuit. [Last accessed on 2022 Jan 05].

4. The Thailand National Institute for Emergency Medicine. Information Technology for Emergency Medical System. Available from: https://ws.niems.go.th/items_front/index.aspx. [Last accessed on 2021 Nov 20].

5. Giummarra MJ, Beck B, Gabbe BJ. Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention. PLoS One. 2021;16(1):0245636. https://doi.org/10.1371/journal.pone.0245636 PMid:33503030

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3