Which older patients are competent to drive? Approaches to office-based assessment.
Bibliographic record
Abstract
OBJECTIVE: To review three proposed approaches to office-based assessment of older drivers and to evaluate recommendations made about dementia and driving. QUALITY OF EVIDENCE: The American Medical Association's (AMA's) Physcian's Guide to Assessing and Counseling Older Drivers gives recommendations for office-based assessment of older patients' medical fitness to drive. Other approaches examined were those outlined in the sixth edition of Determining Medical Fitness to Drive produced by the Canadian Medical Association (CMA) and SAFE DRIVE. Recommendations for dementia and driving from these documents and other sources were reviewed. All evidence was level III. MAIN MESSAGE: The AMA document usefully identified ways to detect drivers at risk and key areas for assessment (vision, cognition, motor function). Recommendations on evaluating these areas require validation. .he CMA guide and SAFE DRIVE were overly broad in their recommendations. How best to detect cognitive impairment that tocld affect driving remains unclear. CONCLUSION: Office-based approaches to identifying older drivers who are either unsafe to drive or require more extensive evaluation need to be validated.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".