Accident; analysis and prevention · 2016
Examining links between cognitive markers, movement initiation and change, and pedestrian safety in older adults.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Geraghty Jennifer, Holland Carol, Rochelle Kim
Аннотация
OBJECTIVE: The purpose of this study was to determine the extent to which mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function, specifically executive functions, including spatial planning, visual attention, and within participant variability, differentially predicted collisions in the near and far sides of the road with increasing age.
METHODS: Adults aged over 45 years participated in cognitive tests measuring executive function and visual attention (using Useful Field of View; UFoV(®)), mobility assessments (walking speed, sit-to-stand, self-reported mobility, and postural sway assessed using motion capture cameras), and gave road crossing choices in a two-way filmed real traffic pedestrian simulation.
RESULTS: A stepwise regression model of walking speed, start-up delay variability, and processing speed) explained 49.4% of the variance in near-side crossing errors. Walking speed, start-up delay measures (average and variability), and spatial planning explained 54.8% of the variance in far-side unsafe crossing errors. Start-up delay was predicted by walking speed only (explained 30.5%).
CONCLUSION: Walking speed and start-up delay measures were consistent predictors of unsafe crossing behaviours. Cognitive measures, however, differentially predicted near-side errors (processing speed), and far-side errors (spatial planning). These findings offer potential contributions for identifying and rehabilitating at-risk older pedestrians.
METHODS: Adults aged over 45 years participated in cognitive tests measuring executive function and visual attention (using Useful Field of View; UFoV(®)), mobility assessments (walking speed, sit-to-stand, self-reported mobility, and postural sway assessed using motion capture cameras), and gave road crossing choices in a two-way filmed real traffic pedestrian simulation.
RESULTS: A stepwise regression model of walking speed, start-up delay variability, and processing speed) explained 49.4% of the variance in near-side crossing errors. Walking speed, start-up delay measures (average and variability), and spatial planning explained 54.8% of the variance in far-side unsafe crossing errors. Start-up delay was predicted by walking speed only (explained 30.5%).
CONCLUSION: Walking speed and start-up delay measures were consistent predictors of unsafe crossing behaviours. Cognitive measures, however, differentially predicted near-side errors (processing speed), and far-side errors (spatial planning). These findings offer potential contributions for identifying and rehabilitating at-risk older pedestrians.