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Record W4382501305 · doi:10.1111/jgs.18493

Driving predictors in a cohort of cognitively impaired Mexican American and non‐Hispanic White individuals

2023· article· en· W4382501305 on OpenAlexaboutno aff
Madelyn Malvitz, Darin B. Zahuranec, Wen Chang, Steven G. Heeringa, Emily M. Briceño, Roshanak Mehdipanah, Xavier F. Gonzales, Deborah A. Levine, Kenneth M. Langa, Nelda Garcia, Lewis B. Morgenstern

Bibliographic record

VenueJournal of the American Geriatrics Society · 2023
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Institute on AgingNational Institutes of HealthAlzheimer's Association
KeywordsMedicineMontreal Cognitive AssessmentDementiaCohortGerontologyCognitionPopulationCohort studyLogistic regressionCognitive declineOdds ratioDemographyCognitive impairmentDiseasePsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Individuals with Alzheimer's disease and Alzheimer's disease-related dementias may lose the ability to drive safely as their disease progresses. Little is known about driving prevalence in older Latinx and non-Hispanic White (NHW) individuals. We investigated the prevalence of driving status among individuals with cognitive impairment in a population-based cohort. METHODS: This was a cross-sectional analysis of the cohort BASIC-Cognitive study in a community of Mexican American (MA) and NHW individuals in South Texas. Participants scored ≤25 on the Montreal Cognitive Assessment (MoCA), indicating a likelihood of cognitive impairment. Current driving status was assessed by the Harmonized Cognitive Assessment Protocol informant interview. Logistic regression was used to assess driving versus non-driving adjusted for pre-specified covariates. Chi-square and Mann-Whitney U tests were used to compare NHW and MA differences in driving outcomes from the American Academy of Neurology (AAN) questions for evaluating driving risk in dementia. RESULTS: There were 635 participants, 77.0 mean age, 62.4% women, and 17.3 mean MoCA. Of these, 360 (61.4%) were current drivers with 250 of 411 (60.8%) MA participants driving, and 121 of 190 (63.70%) NHW participants driving (p = 0.50). In fully adjusted models age, sex, cognitive impairment, language preference, and Activities of Daily Living scores were significant predictors for the likelihood of driving (p < 0.0001). Severity of cognitive impairment was inversely associated with odds of driving, but this relationship was not found in those preferring Spanish language for interviews. Around one-third of all caregivers had concerns about their care-recipient driving. There were no significant differences in MA and NHW driving habits and outcomes from the AAN questionnaire. CONCLUSIONS: The majority of participants with cognitive impairment were currently driving. This is a cause for concern for many caregivers. There were no significant ethnic driving differences. Associations with current driving in cognitively impaired persons require further research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.341
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Geriatrics SocietySame topicOlder Adults Driving StudiesFrench-language works237,207