Determining Fitness to Drive in Older Persons: A Survey of Medical and Surgical Specialists
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Many specialists encounter issues related to fitness to drive in their practices. We sought to determine the attitudes and practices of Canadian specialists regarding the assessment of medical fitness to drive in older persons. METHODS: We present data from a postal survey of 842 physicians certified in cardiology, endocrinology, geriatric medicine, neurology, neurosurgery, orthopaedic surgery, physical medicine and rehabilitation, or rheumatology regarding their attitudes and practices relating to the assessment of their patients' fitness to drive. RESULTS: Overall response rate was 55.1%. Except for rheumatologists (18%), most specialists reported that fitness to drive is an important issue in their practices (68%). Confidence in the ability to assess fitness to drive was low (33%), and the majority (73%) felt they would benefit from further education. There were significant differences (p < .05) in responses between physicians from different provinces, owing to reporting policies. More geriatricians than neurologists report drivers with mild Alzheimer disease to authorities regardless of reporting policy (mandatory 90.7% vs. 56.0%; non-mandatory 84.1% vs. 40.0%) (p < .05). CONCLUSIONS: Canadian specialists accept the responsibility of determining their patients' fitness to drive but are not fully confident in their ability to do so. However, they are receptive to education to improve their skills in this area.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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