Canadian Psychiatrists' Current Attitudes, Practices, and Knowledge regarding Fitness to Drive in Individuals with Mental Illness: A Cross-Canada Survey
Bibliographic record
Abstract
OBJECTIVES: To assess current attitudes, practices, and knowledge of Canadian psychiatrists regarding fitness to drive in individuals with mental illness and to explore variations according to provincial legislation. METHOD: We carried out a national cross-sectional survey, using a random sample of psychiatrists. We used a mail survey to collect data. RESULTS: In total, 248 psychiatrists participated; the response rate was 54.2% on traced subjects. The majority (64.1%) reported that they strongly agreed or agreed that addressing patients' fitness to drive is an important issue. However, only 18.0% of respondents were always aware of whether their patients were active drivers. One-fourth strongly agreed or agreed that they were confident in their ability to evaluate fitness to drive. In discretionary provinces, 29.3% of psychiatrists reported not knowing their provincial legislation, as did 14.6% of psychiatrists in mandatory provinces; of those responding, 54.0% from discretionary provinces and 2.8% from mandatory provinces gave incorrect answers. DISCUSSION: Psychiatrists' responses demonstrate a broad range of attitudes, practices, and knowledge. There appears to be a large gap between what is expected of psychiatrists and their readiness and self-perceived ability to make informed clinical decisions related to driving safety. CONCLUSION: There is a clear need for education and guidelines to assist psychiatrists in decision making about driving fitness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".