Driving Pattern Changes Help Detect Early Cognitive Decline: Study
Researchers have found in a new study that subtle alterations in driving frequency, route complexity, spatial range, trip distance, speeding, and destination variability were strongly linked to mild cognitive impairment (MCI) in older adults. Researchers noted that continuous, real-world driving data may identify early cognitive decline before safety events occur. The study was published in the journal of Neurology by Ling Chen and fellow researchers.
This was a prospective, observational cohort study of 298 community-dwelling older drivers (MCI, n = 56; NC, n = 242; mean age 75.1 years; 45.6% female) enrolled in the Driving Real-World In-Vehicle Evaluation System Project at Washington University. The participants underwent annual Clinical Dementia Rating assessments, neuropsychological testing, and APOE ε4 genotyping. Driving behaviors were continuously captured for up to 40 months using GPS-enabled in-vehicle dataloggers, which recorded trip frequency, duration, distance, time of day, speeding, hard braking, and spatial mobility measures, including entropy, maximum distance, and radius of gyration. Linear mixed-effects models were used to evaluate changes longitudinally, adjusting for age, sex, race, education, and APOE ε4 status. Discrimination between participants with MCI and NC was evaluated with logistic regression using receiver operator curve analysis.
Results
The MCI and NC groups were well matched for age, sex, race, APOE ε4 prevalence, and most driving behaviors at baseline.
Over time, participants with MCI showed significant reductions in key driving metrics compared to NC:
Monthly trip count decreased (MCI: −0.501, SE: 0.21, 95% CI [−0.923 to −0.083] vs NC: −0.523, SE: 0.09, 95% CI [−0.709 to −0.337]; p < 0.001)
Nightly trips decreased (MCI: −0.334, SE: 0.17, 95% CI [−0.675 to 0.001] versus NC: −0.339, SE: 0.07, 95% CI [−0.480 to −0.197]; p < 0.001 )
Random entropy was decreased; MCI: −0.008, SE: 0.004, 95% CI [−0.016 to −0.001]; NC: −0.014, SE: 0.002, 95% CI [−0.017 to −0.011]; p < 0.001
Key driving features, including medium trip distance, speeding events, entropy, and maximum distance differentiated MCI from NC with an AUC of 0.82 (95% CI 0.75-0.89).
In a combination model that incorporated demographics, APOE ε4 status, and cognitive composite scores, the AUC significantly increased to 0.87 (95% CI 0.81-0.93), reflecting a highly discriminative accuracy.
Naturalistic driving data provide a scalable, low-burden approach to the early detection of functional changes associated with cognitive impairment. Given that this study was performed in a predominantly White, highly educated cohort without external validation, these results support the integration of continuous monitoring technologies into geriatric and neurocognitive care. Naturalistic driving data can detect early cognitive decline in older adults, differentiating those with mild cognitive impairment from normal cognition.
Reference:
Chen, L., Carr, D. B., Singh, R. K., Bekena, S., Zhu, Y., Taylor, K., Trani, J.-F., & Babulal, G. M. (2025). Association of daily driving behaviors with mild cognitive impairment in older adults followed over 10 years. Neurology, 105(12). https://doi.org/10.1212/wnl.0000000000214440
