Problems with Sleep Do Not Predict Self-Reported Driving Factors and Perception in Older Drivers: Evidences from the Candrive II Prospective Cohort
Bibliographic record
Abstract
Given that sleep problems and serious motor vehicle collisions are increasingly prevalent in older adults, even minor drowsiness could potentially contribute to driving patterns in older drivers. To date, it is unknown whether less serious problems with sleep influence driving frequency and ability in older adults. We investigated the influence of everyday sleep disturbances on driving practices and driver perceptions in a large cohort of healthy older drivers. Selfreported measures of sleep problems were used to investigate the influence of sleep disturbance on self-reported driving practices and perceived driving abilities. On two measures of self-reported driving outcomes, participants with problems with rated themselves more poorly. However, this relationship disappeared when health and demographic variables were entered prior in hierarchical regression analyses. Our results show that the relationship between sleep problems, driving frequency and perceived abilities is better explained by mediating demographic, health, and cognitive factors.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".