Cognitive Decline and Older Driver Crash Risk
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To examine automobile crash risk associated with cognition in older drivers without dementia. DESIGN: Retrospective secondary analysis of longitudinal cohort study. SETTING: Our study used data from the Adult Changes in Thought (ACT) Study merged with Washington State crash reports and licensure records. Data were available from 2002 to 2015. PARTICIPANTS: Group Health enrollees from Washington State aged 65 and older with active driver's licenses (N=2,615). MEASUREMENTS: Cognitive function was assessed using the Cognitive Abilities Screening Instrument scored using item response theory (CASI-IRT). The study outcome was police-reported motor vehicle crash. We used a negative binomial mixed-effects model with robust standard errors clustered on the individual and considered associations between crash risk, level of cognition, and amount of decline since the previous study visit. Covariates included age, sex, education, alcohol, depression, medical comorbidities, eyesight, hearing, and physical function. Individuals were censored at dementia diagnosis, death, or failure to renew their license. RESULTS: Over an average of 7 years of follow-up, 350 (13%) people had at least one crash. A 1-unit lower CASI-IRT score was associated with a higher adjusted incidence rate ratio of crash of 1.26 (95% confidence interval=1.08-1.51). Beyond level of cognition, amount of cognitive decline between study visits was not associated with crash risk. CONCLUSION: This study suggests that, in older drivers, poorer performance on the CASI-IRT may be a risk factor for motor vehicle crashes, even in individuals without diagnosed dementia. Further research is needed to understand driving behavior and inform driving decisions for older adults with poor cognitive function.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it