A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk

Motorcyclists and a matched group of non-motorcycling car drivers were assessed on behavioral measures known to relate to accident involvement. Using a range of laboratory measures, we found that motorcyclists chose faster speeds than the car drivers, overtook more, and pulled into smaller gaps in traffic, though they did not travel any closer to the vehicle in front. The speed and following distance findings were replicated by two further studies involving unobtrusive roadside observation. We suggest that the increased risk-taking behavior of motorcyclists was only likely to account for a small proportion of the difference in accident risk between motorcyclists and car drivers. A second group of motorcyclists was asked to complete the simulator tests as if driving a car. They did not differ from the non-motorcycling car drivers on the risk-taking measures but were better at hazard perception. There were also no differences for sensation seeking, mild social deviance, and attitudes to riding/driving, indicating that the risk-taking tendencies of motorcyclists did not transfer beyond motorcycling, while their hazard perception skill did. (C) 2002 Elsevier Science Ltd. All rights reserved.

Could in-home sensors surpass human observation of people with Parkinson’s at high risk of falling? An ethnographic study

Self-report underpins our understanding of falls among people with Parkinson’s (PwP) as they largely happen unwitnessed at home. In this qualitative study, we used an ethnographic approach to investigate which in-home sensors, in which locations, could gather useful data about fall risk. Over six weeks, we observed five independently mobile PwP at high risk of falling, at home. We made field notes about falls (prior events and concerns) and recorded movement with video, Kinect, and wearable sensors. The three women and two men (aged 71 to 79 years) having moderate or severe Parkinson’s were dependent on others and highly sedentary. We most commonly noted balance protection, loss, and restoration during chair transfers, walks across open spaces and through gaps, turns, steps up and down, and tasks in standing (all evident walking between chair and stairs, e.g.). Our unobtrusive sensors were acceptable to participants: they could detect instability during everyday activity at home and potentially guide intervention. Monitoring the route between chair and stairs is likely to give information without invading the privacy of people at high risk of falling, with very limited mobility, who spend most of the day in their sitting rooms.