Evidence map›Paper›PMID 38243756›Full record

SynthesisJournal of the American Geriatrics Society2024

Driving among individuals with chronic conditions: A systematic review of applied research using kinematic driving sensors.

Srijani Mukherjee, Anthony D McDonald, Shelli R Kesler, Heather Cuevas, Chad Swank, Alan Stevens, Thomas K Ferris, Valerie Danesh

Open access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in Journal of the American Geriatrics Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 6% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Dementia and driving: A scoping review of family caregiver involvement in driving cessation research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    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

8 authors at 3 institutions in 1 country.

Srijani MukherjeeDepartment of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, USA.
Anthony D McDonaldDepartment of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0001-7827-8828
Shelli R KeslerSchool of Nursing, The University of Texas at Austin, Austin, Texas, USA.
Heather CuevasSchool of Nursing, The University of Texas at Austin, Austin, Texas, USA.
Chad SwankBaylor Scott & White Institute for Rehabilitation, Dallas, Texas, USA.
Alan StevensBaylor Scott & White Research Institute, Dallas, Texas, USA.
Thomas K FerrisDepartment of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, USA.
Valerie DaneshBaylor Scott & White Research Institute, Dallas, Texas, USA.ORCID 0000-0002-2078-2578
Texas A&M University · USThe University of Texas at Austin · USUniversity of Wisconsin System · US

Funding

Driving Rehabilitation and Innovation for Evaluating Risk in Post-Intensive Care Unit Survivors (DRIVE-PICS)R21AG080339 · NIA · BAYLOR RESEARCH INSTITUTE · PI DANESH, VALERIE, MCDONALD, ANTHONY D. · 2023 to 2024
$457k
NIA NIH HHS 1R21AG080339-01NIA NIH HHS R21 AG080339
6 · The paper itself

Abstract

backgroundKinematic driving data studies are a novel methodology relevant to health care, but prior studies have considerable variance in their methods, populations, and findings suggesting a need for critical analysis and appraisal for feasibility and methodological guidelines.

methodsWe assessed kinematic driving studies of adults with chronic conditions for study feasibility, characteristics, and key findings, to generate recommendations for future study designs, and to identify promising directions for applications of kinematic driving data. PRISMA was used to guide the review and searches included PubMed, CINAHL, and Compendex. Of 379 abstract/titles screened, 49 full-text articles were reviewed, and 29 articles met inclusion criteria of analyzing trip-level kinematic driving data from adult drivers with chronic conditions.

resultsThe predominant chronic conditions studied were Alzheimer's disease and related Dementias, obstructive sleep apnea, and diabetes mellitus. Study objectives included feasibility testing of kinematic driving data collection in the context of chronic conditions, comparisons of simulation with real-world kinematic driving behavior, assessments of driving behavior effects associated with chronic conditions, and prognostication or disease classification drawn from kinematic driving data. Across the studies, there was no consensus on devices, measures, or sampling parameters; however, studies showed evidence that driving behavior could reliably differentiate between adults with chronic conditions and healthy controls.

conclusionsVehicle sensors can provide driver-specific measures relevant to clinical assessment and interventions. Using kinematic driving data to assess and address driving measures of individuals with multiple chronic conditions is positioned to amplify a functional outcome measure that matters to patients.

Indexed as

Automobile DrivingAgedAlzheimer DiseaseBiomechanical PhenomenaChronic DiseaseDiabetes MellitusHumansSleep Apnea, Obstructivechronic conditionsdriving safetyfunctional outcomeskinematic data

Identifiers

PMID38243756
PMCPMC11018482
OpenAlexW4391053653

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.