Traffic injury prevention
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Traffic injury prevention · Jan 2016
Evaluation of developmental metrics for utilization in a pediatric advanced automatic crash notification algorithm.
Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric. ⋯ The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.
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Traffic injury prevention · Jan 2016
An estimate of the effectiveness of an in-vehicle automatic collision notification system in reducing road crash fatalities in South Australia.
The aim of this study was to estimate the potential effectiveness of an in-vehicle automatic collision notification (ACN) system in reducing all road crash fatalities in South Australia (SA). ⋯ The minimum effectiveness rate of an ACN system in SA with full deployment is likely to be in the range of 2.4 to 3.8% of all road crash fatalities involving all vehicle types and all vulnerable road users (pedestrians, cyclists, and motorcyclists) from 2008 to 2009. Considering only passenger vehicle occupants, the benefit is likely to be 2.6 to 4.6%. These fatality reductions could only have been achieved through earlier notification of each crash and their location to enable a quicker medical response. This might be achievable through a fully deployed in-vehicle ACN system.
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Traffic injury prevention · Jan 2016
Underutilization Of Occupant Restraint Systems In Motor Vehicle Injury Crashes: A Quantitative Analysis From Qatar.
Restraint systems (seat belts and airbags) are important tools that improve vehicle occupant safety during motor vehicle crashes (MVCs). We aimed to identify the pattern and impact of the utilization of passenger restraint systems on the outcomes of MVC victims in Qatar. ⋯ The nonuse of seat belts is associated with worse outcomes during MVCs in Qatar. Our study highlights the lower rate of seat belt compliance in young car occupants that results in more severe injuries, longer hospital stays, and higher mortality rates. Therefore, we recommend more effective seat belt awareness and education campaigns, the enforcement of current seat belt laws, their extension to all vehicle occupants, and the adoption of proven interventions that will assure sustained behavioral changes toward improvements in seat belt use in Qatar.
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Traffic injury prevention · Jan 2015
Observational StudyThe prevalence of distraction among passenger vehicle drivers: a roadside observational approach.
Distracted driving contributes to a large proportion of motor vehicle crashes, yet little is known about the prevalence of distracted driving and the specific types of distracting behaviors. The objective of this study was to estimate the prevalence of driver distraction using a roadside observational study design. ⋯ When using similar methodology, roadside observational studies generate comparable prevalence estimates of driver distraction as naturalistic driving studies. Driver distraction is a common problem among passenger vehicle drivers. Despite the increased awareness on the dangers of texting and cell phone use while driving, these specific activities were 2 of the most frequently observed distractions. There is a continued need for road safety education about the dangers of distracted driving, especially for younger drivers.
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Traffic injury prevention · Jan 2015
Estimated injury risk for specific injuries and body regions in frontal motor vehicle crashes.
Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data. ⋯ These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.