Abstract

Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010-2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

Highlights

  • By 2030 road traffic injuries are projected to become the fifth leading cause of mortality globally [1]

  • Of the 5,813 motor vehicle drivers, motorcyclist, pedal cyclists and pedestrians with a compensation claim who met the inclusion criteria, only 2,486 could be included in the study as their claim included a description of the injury event

  • A higher proportion of cases whose claim did not include a description of the injury event spoke English as their preferred language, lived in neighbourhoods with greater disadvantage, were working pre-injury, had a pre-existing substance use or mental health condition, sustained more severe injuries, were involved in collisions with fewer vehicles, were injured in the evening hours, and when another vehicle was at fault (Table 1)

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Summary

Objectives

We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. The primary aim of the present study was to classify injury events reported by injured motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians who survive an unintentional road traffic collision using text mining methods

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