Abstract
Background: The number of older adults in the United States will double by 2056. Additionally, the number of licensed drivers will increase along with extended driving-life expectancy. Motor vehicle crashes are a leading cause of injury and death in older adults. Alzheimer's disease (AD) also negatively impacts driving ability and increases crash risk. Conventional methods to evaluate driving ability are limited in predicting decline among older adults. Innovations in GPS hardware and software can monitor driving behavior in the actual environments people drive in. Commercial off-the-shelf (COTS) devices are affordable, easy to install and capture large volumes of data in real-time. However, adapting these methodologies for research can be challenging. This study sought to adapt a COTS device and determine an interval that produced accurate data on the actual route driven for use in future studies involving older adults with and without AD. Methods: Three subjects drove a single course in different vehicles at different intervals (30, 60 and 120 seconds), at different times of day, morning (9:00-11:59AM), afternoon (2:00-5:00PM) and night (7:00-10pm). The nine datasets were examined to determine the optimal collection interval. Results: Compared to the 120-second and 60-second intervals, the 30-second interval was optimal in capturing the actual route driven along with the lowest number of incorrect paths and affordability weighing considerations for data storage and curation. Discussion: Use of COTS devices offers minimal installation efforts, unobtrusive monitoring and discreet data extraction. However, these devices require strict protocols and controlled testing for adoption into research paradigms. After reliability and validity testing, these devices may provide valuable insight into daily driving behaviors and intraindividual change over time for populations of older adults with and without AD. Data can be aggregated over time to look at changes or adverse events and ascertain if decline in performance is occurring.
Highlights
The number of older adults in the United States will double by 2056
Vehicle Name: Participant ID via Vehicle Make and Model; Vehicle Speed: Vehicle speed; Latitude: The angular distance of a place north or south of the earth’s equator; Longitude: The angular distance of a place east or west of the earth’s equator; Event Type: Type of event coded by the global positioning data acquisition system (GPDAS) device; Timestamp: Date and Time; Odometer Reading: Vehicle odometer reporting the number of miles
This study investigated the optimal time interval for data collection using a GPDAS device to accurately capture a driven route while weighing the considerations of cost associated with data storage and post-processing efforts
Summary
The number of older adults in the United States will double by 2056. the number of licensed drivers will increase along with extended driving-life expectancy. Coupled with the growth of the aging population and the increasing prevalence of dementias like Alzheimer disease (AD), being able to predict when driving performance will decline may prevent crashes and deaths among older adult drivers and others who share the roadway[3,4,5]. Driving is an overlearned task and controlled conditions like the road test and simulator may not reflect driving as it occurs on a daily basis or expose errors made by experienced or cognitively-normal drivers outside of these controlled conditions[13] Other limitations of both methods include rater subjectivity, anxiety (poorer performance), Hawthorne effect, dedicated single site measures, simulator sickness and high equipment cost, maintenance, and programming[13,14,15,16]
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