How older adults drive may indicate early signals of disease.
Columbia University/Mailman School of Public Health and Fu Foundation School of Engineering and Applied ScienceResearchers have developed what they call highly accurate algorithms that can be used as a screening tool for early detection and management of mild cognitive impairment and dementia in older adults. A new analysis, based on naturalistic driving data and machine learning techniques, suggests that driving behavior can harbor early signals of disease.
The findings were announced late last month by Columbia University Mailman School of Public Health and Columbia’s Fu Foundation School of Engineering and Applied Science.
“Driving is a complex task involving dynamic cognitive processes and requiring essential cognitive functions and perceptual motor skills,” Guohua Li, professor of epidemiology and anesthesiology at Columbia Mailman School and Vagelos College of Physicians and Surgeons, and senior author of the study, said in a statement. “Our study indicates that naturalistic driving behaviors can be used as comprehensive and reliable markers for mild cognitive impairment and dementia.”
Naturalistic driving data refer to those captured through in-vehicle recording devices or other technologies in the real-world setting, according to the study, which was published in April in the journal Geriatrics.
During the evaluation, which spanned the time period from August 2015 through March 2019, in-vehicle recording devices were installed in the cars of 2977 participants of the Longitudinal Research on Aging Drivers (LongROAD) project, a study sponsored by the AAA Foundation for Traffic Safety, a nonprofit research and education association.
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The participants at the time of enrollment were active drivers aged 65-79 years and had no significant cognitive impairment and degenerative medical conditions.
By the end of the study, 33 were newly diagnosed with mild cognitive impairment and 31 were diagnosed with dementia.
Researchers said the statistical technique used performed “exceptionally well.” They found that the model based on driving variables and demographic characteristics had a high level of accuracy (88%) compared to models based on demographic characteristics only (29% ) and driving variables only (66%).
Using variables like age, sex, race/ethnicity and education level, “we could predict mild cognitive impairment and dementia with 88% accuracy, ” Sharon Di, associate professor of civil engineering and engineering mechanics at Columbia Engineering and the study’s lead author, said in a statement.
Age, not surprisingly, was found to be most predictive of mild cognitive impairment and dementia. Other factors that played a role included: percentage and length of car trips, race/ethnicity, and number of hard braking incidences.
“If validated, the algorithms developed in this study could provide a novel, unobtrusive screening tool for early detection and management of mild cognitive impairment and dementia in older drivers,” Dr. Li added.
For more information and to access the study, click here and here.
The Link LonkMay 31, 2021 at 01:17AM
https://www.forbes.com/sites/tanyamohn/2021/05/30/its-what-older-drivers-fear-behaviors-behind-the-wheel-harbor-early-signals-of-dementia-new-study-finds/
It’s What Older Drivers Fear: Behaviors Behind The Wheel Harbor Early Signals Of Dementia, New Study Finds - Forbes
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