Multidisciplinary Assessment of Fitness to Drive in Brain Tumour Patients in Southwestern Ontario: A Grey Matter
Bibliographic record
Abstract
BACKGROUND: Neurocognitive impairments from brain tumours may interfere with the ability to drive safely. In 9 of 13 Canadian provinces and territories, physicians have a legal obligation to report patients who may be medically unfit to drive. To complicate matters, brain tumour patients are managed by a multidisciplinary team; the physician most responsible to make the report of unfitness is often not apparent. The objective of the present study was to determine the attitudes and reporting practices of physicians caring for these patients. METHODS: A 17-question survey distributed to physicians managing brain tumour patients elicited Respondent demographicsKnowledge about legislative requirementsExperience of reportingBarriers and attitudes to reporting Fisher exact tests were performed to assess differences in responses between family physicians (fps) and specialists. RESULTS: Of 467 physicians sent surveys, 194 responded (42%), among whom 81 (42%) were specialists and 113 (58%) were fps. Compared with the specialists, the fps were significantly less comfortable with reporting, less likely to consider reporting, less likely to have patients inquire about driving, and less likely to discuss driving implications. A lack of tools, concern for the patient-physician relationship, and a desire to preserve patient quality of life were the most commonly cited barriers in determining medical fitness of patients to drive. CONCLUSIONS: Legal requirements to report medically unfit drivers put physicians in the difficult position of balancing patient autonomy and public safety. More comprehensive and definitive guidelines would be helpful in assisting physicians with this public health issue.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".