Driving behaviors in early stage dementia: A study using in-vehicle technology
Introduction
According to the Alzheimer's Association (2011), (1) in 8 people aged 65 and older, and about one-half of people age 85 and older, have Alzheimer's disease (AD) in the United States (US). The number of people age 65 and older will more than double in the next 25 years, with a threefold increase for those age 80 and older (Herbel et al., 2006). In the next 4 decades, those age 80 and older are expected to increase from 15 percent of all older people in the United States to 24 percent of older Americans (Alzheimer's Association, 2011). This increase is projected to result in 15 million more oldest-old people living in the US and these individuals are the ones most at risk for developing Alzheimer's disease (Alzheimer's Association, 2011).
While it might be assumed that individuals with dementia would stop driving after onset of symptoms, it is estimated that around one-third of drivers with dementia continue to drive (Silverstein, 2008). Most drivers are early in the disease process when cognitive deficits are generally mild (Adler and Kuskowski, 2003) and changes to driving performance are minimal. Nonetheless, drivers with dementia are one of the groups considered at greatest risk for unsafe driving performance (Langford et al., 2007). Yet, decisions to enforce driving cessation are not straightforward and pose a difficult challenge to family members, licensing authorities, and health care professionals.
Compared to the general driving population, drivers with dementia are at an increased risk of unsafe motor vehicle operation (Man-Son-Hing et al., 2007). Problematic driving behaviors include becoming lost in familiar areas (Silverstein et al., 2002, Uc et al., 2004), incorrect turning (Uc et al., 2005), impaired signaling (Duchek et al., 2003), decreased comprehension of traffic signs (Carr et al., 1998), and lane deviation (Uc et al., 2005). Crashes, while infrequent, are also of concern for drivers with dementia, whose crash risk is two to five times that of unimpaired older drivers (Charlton et al., 2003). Furthermore, driving skills predictably worsen (Adler et al., 1999) and will ultimately require individuals with dementia to stop driving (Adler et al., 2005).
Driving decisions need to be made not on diagnosis but on an assessment of the dementia's progress and the disease's effects on functional abilities (Duchek et al., 2003, Eby et al., 2009a, Eby and Molnar, 2010). Unfortunately, there is little consensus on the means to make this assessment. A review of studies that measured driving competency of drivers with dementia found a wide array of different assessment approaches; even where common protocols were used, there were different conclusions about their usefulness and validity (Reger et al., 2004). Road tests seem essential to evaluating driving ability; however, on-road evaluations by themselves have not been able to fully answer questions of driving competency. Because driving is an over learned task, standard road tests with step-by-step instructions do not necessarily test the skills or expose errors commonly made by an experienced driver (Odenheimer, 1993). Another approach to assessing driving skills in individuals with dementia uses a driving simulator. Learning to use a simulator, however, can be difficult for drivers with dementia even when given time to adapt to the setting (Cox et al., 1998). An additional complication of using a simulator to assess driving skills is the fact that older adults, in general, are more likely than younger people to experience simulator sickness (Brooks et al., 2010). Furthermore, individuals with dementia retain abilities that are over learned and thus, actual driving skills may be better than those assessed under the artificial conditions of a simulator. Neuropsychological tests have frequently been used to predict fitness to drive, often in studies that incorporate on-road or simulator evaluation, although their association with driving impairment and crash risk is at best moderate. Such studies often report statistically significant associations, but their size and variability suggest that no single protocol can confidently indicate for a specific patient the impairment threshold for non-driving (Reger et al., 2004). As a result of current assessment inconsistencies and shortcomings, some drivers with dementia may remain on the road longer than is safe while other drivers may cease prematurely. Improved procedures for assessing driving risk are urgently needed (Reger et al., 2004).
Recent advances in sensor, computer, and telecommunication technologies provide a method for automatically collecting detailed, objective information about a person's driving performance (e.g., LeBlanc et al., 2006, LeBlanc et al., 2007). This technology, placed unobtrusively in a driver's vehicle, can be used to study the driving behavior of individuals diagnosed with early stage dementia. The objective of this project was to use in-vehicle technology to describe a set of driving behaviors that may be common in individuals with early stage dementia (i.e., a diagnosis of memory loss) and compare these behaviors to a group of drivers without a diagnosis of cognitive impairment.
Section snippets
Participants
A convenience sample of older adults participated in the project. All participants met the following inclusion criteria: held a valid driver's license; had been told by a health professional that they had early stage dementia; passed a comprehensive driving evaluation provided free of charge and which included clinical and on-road testing; were willing to have their personal vehicle installed with unobtrusive, in-vehicle technology for at least 1 month; were willing to leave their vehicle at
Data collection
Once data collection equipment was installed in the vehicles, participants were asked to drive as they normally would for a period of up to 2 months, depending on scheduling. Participants were contacted after 1 week in order to answer any questions from the participants and to schedule a time to check the in-vehicle technology was functioning properly. The technology was inspected and some data downloaded from the DAS to ensure that the sensors were functional and data were being collected
Onboard data pre-processing
Over 10,800 miles of data were collected from the 17 drivers with early stage dementia and these data were compared to data from an existing archive of 26 comparison older drivers (23,000 miles). The main processing of the data included an integrated series of automatic calculations and analyst reviews of video, audio, and other sensor data. Analysts reviewed over 15,000 events/trips for this study (over 8000 for drivers with memory loss, nearly 7000 for the comparison group). The video reviews
Results
The number of participants (N), mean score, confidence interval, and probability level of the Wilcoxon Signed Rank Sum test (p-value) for each variable investigated in the study can be found in Table 2. Note that some variables could not be investigated in the comparison group sample. In addition, for two variables, 17 comparison subjects were randomly selected from the 26 for analysis, as these variables required labor-intensive analysis of video. p-Values shown in bold indicate a
Discussion
This report describes a study using custom in-vehicle technology to objectively measure driving behaviors of people with early stage dementia and to compare these behaviors with existing data on similar measures from a sample of older drivers. The study revealed several differences in driving behaviors between participants with early stage dementia and the comparison sample of older drivers. Foremost, few safety-related errors were found for either group. However, the early stage dementia group
Acknowledgments
This work was supported in part by grant number IIRG-06-25387 from the Alzheimer's Association; Task Orders under Contracts DTNH22-02-D-15338 and DTNH22-07-D-00052 from the National Highway Traffic Safety Administration (NHTSA); and a grant from the Michigan Center for Advancing Safe Transportation throughout the Lifespan (M-CASTL.org), a University Transportation Center sponsored by the US Department of Transportation (US DOT) and the University of Michigan. The contents of this report reflect
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