Emotional reactions to cycle helmet use
ABSTRACT It has been suggested that the safety benefits of bicycle helmets are limited by risk compensation. The current article tests if previous helmet use influences the response to helmets as a safety intervention. This was investigated in a field experiment where pace and psychophysiological load were measured. We found that after having removed their helmets, routine helmet users cycled more slowly and demonstrated increased psychophysiological load. However, for non-users there was no significant change in either cycling behaviour or psychophysiological load. We discuss the implications of these results for a hypothesis of risk compensation in response to helmet use. We also show that heart rate variability is a promising measure of psychophysiological load in real-world cycling, at least in situations where there is limited physical demand.
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ABSTRACT: Objective: The current study aimed at uncovering patterns of cyclist-motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users' crash patterns derives from the need to prioritize safety issues and to devise efficient preventive measures. Method: The current study focused on cyclist-motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic clustering approach that relies on the statistical concept of likelihood and allows partial overlap across clusters. Results: The analysis yielded 13 distinguishable cyclist-motorist latent classes. Specific crash patterns for urban and rural areas were revealed. Prevalent features that allowed differentiating the latent classes were speed limit, infrastructure type, road surface conditions, number of lanes, motorized vehicle precrash maneuvers, the availability of a cycle lane, cyclist intoxication, and helmet wearing behavior. After the latent class clustering, the distribution of cyclists' injury severity within each cluster was analyzed. Conclusions: The latent class clustering approach provided a comprehensive and clear map of cyclist-motorist crash patterns. The results are useful for prioritizing and resolving safety issues in urban areas, where there is a significant share of cyclists potentially involved in multiple hazardous situations or where extensive bicycle sharing programs are planned.Traffic Injury Prevention 08/2013; 14(7):725-33. DOI:10.1080/15389588.2012.759654 · 1.29 Impact Factor
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ABSTRACT: Bicycle helmets are designed to mitigate head injury during a collision. In the early 1990's, Australia and New Zealand mandated helmet wearing for cyclists in an effort to increase helmet usage. Since that time, helmets and helmet laws have been portrayed as a failure in the peer-reviewed literature, by the media and various advocacy groups. Many of these criticisms claim helmets are ineffective, helmet laws deter cycling, helmet wearing increases the risk of an accident, no evidence helmet laws reduce head injuries at a population level, and helmet laws result in a net health reduction. This paper reviews the data and methods used to support these arguments and shows they are statistically flawed. When the majority of evidence against helmets or mandatory helmet legislation (MHL) is carefully scrutinised it appears overstated, misleading or invalid. Moreover, much of the statistical analysis has been conducted by people with known affiliations with anti-helmet or anti-MHL organisations.