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Near-miss crashes and other predictors of motorcycle crashes: Findings from a population-based survey.

Liz de RomeJulie BrownMatthew BaldockMichael Fitzharris
Published in: Traffic injury prevention (2018)
These findings provide important population-level information and insights about risk exposure for motorcyclists. Taking a more tailored approach to data collection meant that factors associated with crash involvement were identified that are not commonly observed in studies relying on administrative data. In particular, the study highlights the importance of near-crash experiences as warnings to riders and the need to use such experiences as learning opportunities to improve their riding style and safety.
Keyphrases
  • electronic health record
  • mental health
  • big data
  • cross sectional
  • health information
  • smoking cessation
  • machine learning
  • data analysis