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Driver Speed Profiles Index Warning Signs of MCI
GOAL: Use driver behavior profiles to screen and index early warnings of cognitive decline and Alzheimer’s disease (AD). Hypothesis: Real-world driver speed behavior profiles discriminate mild cognitive impairment (MCI). METHODS: Sensors were installed in personal vehicles of 74 legally-licensed, ac...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682412/ http://dx.doi.org/10.1093/geroni/igab046.489 |
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author | Merickel, Jennifer Wu, Ruiqian Rizzo, Matthew Zhang, Ying |
author_facet | Merickel, Jennifer Wu, Ruiqian Rizzo, Matthew Zhang, Ying |
author_sort | Merickel, Jennifer |
collection | PubMed |
description | GOAL: Use driver behavior profiles to screen and index early warnings of cognitive decline and Alzheimer’s disease (AD). Hypothesis: Real-world driver speed behavior profiles discriminate mild cognitive impairment (MCI). METHODS: Sensors were installed in personal vehicles of 74 legally-licensed, active drivers (age: 65-90 years, μ = 75.85) who completed 2, 3-month real-world driving assessments, including demographic and cognitive assessments, 1 year apart (244,564 miles driven). MCI status was indexed using 8 neuropsychological tests (spanning executive function, visuospatial skills, processing speed, and memory), relevant to MCI and driving. Driving environment was indexed from state speed limit (SL; roadway type: residential, commercial, interstate) and sunrise-sunset databases (time of day: day vs. night). Models: Data were randomly split into training (66%) and validation (33%) sets. An optimal mixed effects logistic regression model was determined from validation data AUC values. RESULTS: MCI drivers drove slower with optimal discrimination (estimated for every 5 mph decrease in speeding) in 1) residential roads (SL 25-35 mph; MCI odds increased by 6% [95% CI: 2-11%]), 2) interstate roads (SL >55 mph; MCI odds increased by 14% [95% CI: 8-20%]), and 3) night environments (MCI odds increased by 7% [95% CI: 2-12%]). CONCLUSION: Quantitative indices of real-world driver data provide “ground truth” for screening and indexing phenotypes of cognitive decline, in line with ongoing efforts to link driver behavior with age-related cognitive decline and AD biomarkers. Behavioral biomarkers for diagnosing early warnings of dementia could ultimately bolster our ability to detect and intervene in early AD. |
format | Online Article Text |
id | pubmed-8682412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86824122021-12-17 Driver Speed Profiles Index Warning Signs of MCI Merickel, Jennifer Wu, Ruiqian Rizzo, Matthew Zhang, Ying Innov Aging Abstracts GOAL: Use driver behavior profiles to screen and index early warnings of cognitive decline and Alzheimer’s disease (AD). Hypothesis: Real-world driver speed behavior profiles discriminate mild cognitive impairment (MCI). METHODS: Sensors were installed in personal vehicles of 74 legally-licensed, active drivers (age: 65-90 years, μ = 75.85) who completed 2, 3-month real-world driving assessments, including demographic and cognitive assessments, 1 year apart (244,564 miles driven). MCI status was indexed using 8 neuropsychological tests (spanning executive function, visuospatial skills, processing speed, and memory), relevant to MCI and driving. Driving environment was indexed from state speed limit (SL; roadway type: residential, commercial, interstate) and sunrise-sunset databases (time of day: day vs. night). Models: Data were randomly split into training (66%) and validation (33%) sets. An optimal mixed effects logistic regression model was determined from validation data AUC values. RESULTS: MCI drivers drove slower with optimal discrimination (estimated for every 5 mph decrease in speeding) in 1) residential roads (SL 25-35 mph; MCI odds increased by 6% [95% CI: 2-11%]), 2) interstate roads (SL >55 mph; MCI odds increased by 14% [95% CI: 8-20%]), and 3) night environments (MCI odds increased by 7% [95% CI: 2-12%]). CONCLUSION: Quantitative indices of real-world driver data provide “ground truth” for screening and indexing phenotypes of cognitive decline, in line with ongoing efforts to link driver behavior with age-related cognitive decline and AD biomarkers. Behavioral biomarkers for diagnosing early warnings of dementia could ultimately bolster our ability to detect and intervene in early AD. Oxford University Press 2021-12-17 /pmc/articles/PMC8682412/ http://dx.doi.org/10.1093/geroni/igab046.489 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Merickel, Jennifer Wu, Ruiqian Rizzo, Matthew Zhang, Ying Driver Speed Profiles Index Warning Signs of MCI |
title | Driver Speed Profiles Index Warning Signs of MCI |
title_full | Driver Speed Profiles Index Warning Signs of MCI |
title_fullStr | Driver Speed Profiles Index Warning Signs of MCI |
title_full_unstemmed | Driver Speed Profiles Index Warning Signs of MCI |
title_short | Driver Speed Profiles Index Warning Signs of MCI |
title_sort | driver speed profiles index warning signs of mci |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682412/ http://dx.doi.org/10.1093/geroni/igab046.489 |
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