A Three-Tiered Comprehensive Driving Evaluation Integrating a Driving Simulator Test for Drivers with Borderline Cognitive Fitness-to-Drive: Proof of Concept
Bibliographic record
Abstract
Comprehensive driving evaluations for older adults with cognitive impairment are time-consuming, expensive, and involve risk. To minimize these challenges, we evaluated a three-tiered driving evaluation process incorporating cognitive tests (Step 1), a driving simulator test (Step 2), and a road test (Step 3). Participants in this study were referred to a driving assessment center for concerns about cognitive fitness-to-drive. Each participant completed all three evaluation steps. Their fitness-to-drive was determined independently by an occupational therapist and an experienced driving evaluator with a driver instructor background. Our main objective was to examine the agreement between the occupational therapist's determination of fitness-to-drive after each step and the driving evaluator's determination of fitness-to-drive after the road test. As a secondary objective, the occupational therapist's confidence in their determinations was also examined. Results showed agreement for 38.8% of participants after Step 1, 46.5% after Step 2, and 92.3% after Step 3. The mean occupational therapist's confidence rating in their determination (scale of 0 to 100; higher is better) was 36.15 after Step 1, 49.54 after Step 2, and 90.54 after Step 3. All drivers deemed to have passed the evaluation had been identified as such after the driving simulator test. These results suggest that the best agreement between the occupational therapist and the driving evaluator was reached after the final step. However, the results also indicate that for some participants, a road test may not be required following a driving simulator test. Eliminating the road test in some instances may create efficiencies and reduce cost and risk while maintaining accurate determinations of fitness-to-drive.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".