Do Restricted Driver's Licenses Lower Crash Risk Among Older Drivers? A Survival Analysis of Insurance Data From British Columbia
Bibliographic record
Abstract
PURPOSE: Faced with an aging driving population, interest is increasing in the use of restricted licenses or "graduated delicensing" for older drivers to allow them to safely retain a driver's license. The primary purpose of this study was to determine whether restricted licenses are successful at mitigating number of crashes per year and whether they can extend the period of crash-free driving for aging adults. DESIGN AND METHODS: Using a cohort study design, licensing and insurance claims crash records of all drivers aged 66 years and older in British Columbia were examined for the years 1999-2006. Nonparametric and Cox proportional hazards survival analyses were used to compare restricted vs. unrestricted drivers and to estimate crash risks. RESULTS: The risk of causing a crash for restricted drivers was 89% (or 11% lower risk) compared with unrestricted drivers after controlling forage and gender.[corrected]. The most common restriction was a combination of daylight driving only plus a speed maximum of 80 km/hr. Restricted drivers retained a driver's license for a longer period of time than unrestricted drivers and continued to drive crash free longer than unrestricted drivers. There was no difference in severity of collisions, and results suggest a high level of compliance with daylight-only restrictions. IMPLICATIONS: These findings suggest that driving restrictions may be effective for prolonging the crash-free driving of some aging drivers, thus supporting their continued independence and delaying institutionalization. Further studies are needed to determine which drivers are most likely to benefit from restricted licenses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".