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基于哈顿矩阵视角的道路交通健康与安全移动应用程序

Mobile applications for road traffic health and safety in the mirror of the Haddon's matrix.

作者信息

Aghayari Hossein, Kalankesh Leila R, Sadeghi-Bazargani Homayoun, Feizi-Derakhshi Mohammad-Reza

机构信息

Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.

Health Services Management Research Center, Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.

出版信息

BMC Med Inform Decis Mak. 2021 Aug 2;21(1):230. doi: 10.1186/s12911-021-01578-8.

DOI:10.1186/s12911-021-01578-8
PMID:34340699
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8330074/
Abstract

BACKGROUND

Road traffic accidents have been one of the leading causes of death. Despite the increasing trend of road traffic apps, there is no comprehensive analysis of their features and no taxonomy for the apps based on traffic safety theories. This study aimed to explore the characteristics of available mobile apps on road traffic health/safety and classify them with emphasis on Haddon's matrix.

METHODS

The researchers examined the mobile applications related to road traffic health/safety using qualitative content analysis. Google Play was searched using a combination of the keywords. Haddon's matrix was applied to analyze and classify those mobile apps residing in the categories of Road Traffic health & Safety, and Road Traffic Training.

RESULTS

Overall, 913 mobile apps met the inclusion criteria and were included in the final analysis. Classification of the apps based on their features resulted in 4 categories and 21 subcategories. A total number of 657 mobile apps were classified based on Haddon's matrix. About 45.67% of these apps were categorized as the road traffic health & safety group.

CONCLUSIONS

Haddon's matrix appears to have the potential to reveal the strengths and weaknesses of existing mobile apps in the road traffic accident domain. Future development of mobile apps in this domain should take into account the existing gap.

摘要

背景

道路交通事故一直是主要死因之一。尽管道路交通应用程序呈增长趋势，但对于其功能尚无全面分析，且基于交通安全理论也没有对这些应用程序进行分类。本研究旨在探讨现有道路交通健康/安全移动应用程序的特点，并重点依据哈顿矩阵对其进行分类。

方法

研究人员采用定性内容分析法对与道路交通健康/安全相关的移动应用程序进行了审查。通过关键词组合在谷歌应用商店进行搜索。应用哈顿矩阵对归类于道路交通健康与安全以及道路交通培训类别的移动应用程序进行分析和分类。

结果

总体而言，913个移动应用程序符合纳入标准并被纳入最终分析。根据其功能对应用程序进行分类产生了4个类别和21个子类别。基于哈顿矩阵对657个移动应用程序进行了分类。其中约45.67%的应用程序被归类为道路交通健康与安全组。

结论

哈顿矩阵似乎有潜力揭示现有移动应用程序在道路交通事故领域的优势与不足。该领域移动应用程序的未来发展应考虑到现有差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/73e75e840823/12911_2021_1578_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/d8190b789626/12911_2021_1578_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/dc541e5a73e0/12911_2021_1578_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/ac0cdee0f373/12911_2021_1578_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/73e75e840823/12911_2021_1578_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/d8190b789626/12911_2021_1578_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/dc541e5a73e0/12911_2021_1578_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/ac0cdee0f373/12911_2021_1578_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d42/8330074/73e75e840823/12911_2021_1578_Fig4_HTML.jpg

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