Evidence map›Paper›PMID 41220789›Full record

ArticleIEEE journal of translational engineering in health and medicine2025

Characterizing Navigational Changes in Preclinical Alzheimer's Disease: A Route Complexity Metric Derived From Naturalistic Driving Data.

Kelly Long, Ganesh M Babulal, Sayeh Bayat

Abstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kelly LongDepartment of Biomedical EngineeringUniversity of Calgary Calgary AB T2N 1N4 Canada.ORCID 0009-0007-7973-9842
Ganesh M BabulalDepartment of NeurologyWashington University School of Medicine St. Louis MO 63110 USA.ORCID 0000-0001-7966-3509
Sayeh BayatDepartment of Biomedical EngineeringUniversity of Calgary Calgary AB T2N 1N4 Canada.ORCID 0000-0003-2554-2140

Funding

Naturalistic driving as a functional neurobehavioral marker of preclinical and symptomatic Alzheimer diseaseR01AG068183 · NIA · WASHINGTON UNIVERSITY · PI BABULAL, GANESH M · 2020 to 2024
$6.7M
The Impact of Depression and Preclinical Alzheimer Disease on Driving Among Older AdultsR01AG067428 · NIA · WASHINGTON UNIVERSITY · PI BABULAL, GANESH M · 2020 to 2024
$4.0M
Aging Research Characterizing Health Exposome via Social drivers (ARCHES)R01AG074302 · NIA · WASHINGTON UNIVERSITY · PI BABULAL, GANESH M · 2021 to 2025
$3.7M
NIA NIH HHS R01 AG067428NIA NIH HHS R01 AG068183NIA NIH HHS R01 AG074302
6 · The paper itself

Abstract

objectiveTo examine how early pathophysiological changes in Alzheimer's disease (AD) affect navigational decision-making by analyzing the complexity of driving routes in older adults with and without preclinical AD.

methodsWe developed a novel route complexity metric based on the number of left and right turns and the deviation from the most direct path, accounting for cognitive load during navigation. Naturalistic GPS driving data were collected for a year from 111 older adults aged 65-85, with preclinical AD status determined via cerebrospinal fluid amyloid biomarkers. A multiple linear regression model was used to assess the relationship between age, preclinical AD status, and route complexity.

resultsThe findings of this study indicate that preclinical AD may influence the navigational abilities of older adults. After controlling for age, participants with preclinical AD chose routes with higher baseline complexity than the control group. It further revealed that participants with preclinical AD selected routes with lower complexity as they aged-a trend not observed in healthy controls.

conclusionPreclinical AD is associated with changes in spatial decision-making that are observable in real-world driving behaviours. The age-related decline in route complexity among those with preclinical AD may reflect compensatory strategies or progressive cognitive changes. CLINICAL IMPACT: This study presents a non-invasive, behaviour-based metric that could support early detection of cognitive decline. It may also inform the design of personalized mobility interventions and dementia-friendly mobility systems.

Indexed as

Alzheimer DiseaseAutomobile DrivingSpatial NavigationAgedAged, 80 and overFemaleHumansMaleAlzheimer’s diseasecognitive impairmentdigital biomarkersdrivingGPS trajectory analysishuman mobilitynaturalistic datanavigational behaviourroute complexity

Identifiers

PMID41220789
PMCPMC12599902

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.