2019
DOI: 10.2196/13222
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Paper Versus Digital Data Collection for Road Safety Risk Factors: Reliability Comparative Analysis From Three Cities in Low- and Middle-Income Countries

Abstract: Background Rapid advances in mobile technologies and applications and the continued growth in digital network coverage have the potential to transform data collection in low- and middle-income countries. A common perception is that digital data collection (DDC) is faster and quickly adaptable. Objective The objective of this study was to test whether DDC is faster and more adaptable in a roadside environment. We conducted a reliability study comparing digital versus pap… Show more

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Cited by 10 publications
(4 citation statements)
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“…It was also found that the official and actual accident reports were different and unreliable. The results of the official record are misleading and lead to underestimating the accidents [30]. The example conveys a message that the official records are not satisfactory.…”
Section: Literature Reviewmentioning
confidence: 95%
See 1 more Smart Citation
“…It was also found that the official and actual accident reports were different and unreliable. The results of the official record are misleading and lead to underestimating the accidents [30]. The example conveys a message that the official records are not satisfactory.…”
Section: Literature Reviewmentioning
confidence: 95%
“…It was found that digitally collected data productivity was higher due to less errors. It was also pointed out that the cost spent on digital recording devices prove useful in the long-term use despite of its maintenance costs [30].…”
Section: Literature Reviewmentioning
confidence: 99%
“…The web app was powered by Enketo and specifically designed for low-resource settings. Other countries where KoBo has previously been implemented include Vietnam, Indonesia, Ghana, and Malawi [ 62 , 63 ]. This platform was selected as it was free and open source, adaptative in a range of challenging contexts with varying Wi-Fi availability, and had accessible features that could be further expanded and customized depending on user feedback during the exit interview.…”
Section: Methodsmentioning
confidence: 99%
“…With this method, there is the potential for misclassification (Muni et al, 2020), double counting, limited geographic coverage, and missed riders. In addition, if paper records are used, there can be issues related to legibility, storage costs, and the additional time and cost of entering the data twice (Mehmood, Taber, Bachani, Gupta, & Paichadze, 2019). Roadside observation can also suffer from observation bias (e.g., age) and selection bias since only specified areas and observation times are utilised.…”
Section: Current Methodologymentioning
confidence: 99%