P.011 Standardized Processes for Addressing Driving Cessation in the Memory Clinic
Bibliographic record
Abstract
Background: Discussions around driving cessation between clinicians and dementia patients are challenging. Patients view giving up their license as losing their independence. We sought to develop a tool that enables standardized and consistent driving messaging across clinicians working in a specialist memory clinic, across the span of cognitive disorders Methods: We developed a driving recommendations generator that allows clinicians to produce information handouts personalized to individual patient capabilities and needs. Clinicians select from a list of established recommendations that were developed with neurologist and geriatrician input, and consistent with provincial requirements. Recommendations cover patients’ current driving ability, road safety examinations, alternate transportation, and license revocation. Early driving retirement is emphasized and encouraged, to proactively support patients’ choices, safety and independence. Recommendation and handouts are printed for the patients. Results: Patients reported that the recommendations were easy to read and understand, and helped them to implement physician suggestions. All surveyed clients recommended continuing to provide such recommendations to future patients and families. Clinicians agreed that the tool helped them to save time, and simplified the process of finding accurate information to provide patients. Conclusions: Clinicians have found the system timesaving and useful for simplifying the process of providing helpful, informative resources for patients.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; 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".