Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix
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 characterist...
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| Format: | Article |
| Language: | English |
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BMC
2021-08-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-021-01578-8 |
| _version_ | 1818832908211716096 |
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| author | Hossein Aghayari Leila R. Kalankesh Homayoun Sadeghi-Bazargani Mohammad-Reza Feizi-Derakhshi |
| author_facet | Hossein Aghayari Leila R. Kalankesh Homayoun Sadeghi-Bazargani Mohammad-Reza Feizi-Derakhshi |
| author_sort | Hossein Aghayari |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T02:10:30Z |
| format | Article |
| id | doaj.art-7664439a73c84d77aed60f5c7eeb4399 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-19T02:10:30Z |
| publishDate | 2021-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-7664439a73c84d77aed60f5c7eeb43992022-12-21T20:40:48ZengBMCBMC Medical Informatics and Decision Making1472-69472021-08-0121111210.1186/s12911-021-01578-8Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrixHossein Aghayari0Leila R. Kalankesh1Homayoun Sadeghi-Bazargani2Mohammad-Reza Feizi-Derakhshi3Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical SciencesDepartment of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical SciencesRoad Traffic Injury Research Center, Tabriz University of Medical SciencesDepartment of Computer Engineering, University of TabrizAbstract 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.https://doi.org/10.1186/s12911-021-01578-8m-HealthTraffic accidentPreventionTraffic safetyHaddon’s matrixPublic health |
| spellingShingle | Hossein Aghayari Leila R. Kalankesh Homayoun Sadeghi-Bazargani Mohammad-Reza Feizi-Derakhshi Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix BMC Medical Informatics and Decision Making m-Health Traffic accident Prevention Traffic safety Haddon’s matrix Public health |
| title | Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix |
| title_full | Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix |
| title_fullStr | Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix |
| title_full_unstemmed | Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix |
| title_short | Mobile applications for road traffic health and safety in the mirror of the Haddon’s matrix |
| title_sort | mobile applications for road traffic health and safety in the mirror of the haddon s matrix |
| topic | m-Health Traffic accident Prevention Traffic safety Haddon’s matrix Public health |
| url | https://doi.org/10.1186/s12911-021-01578-8 |
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