Using Serial Trichotomization to Determine Fitness to Drive in Medically At-Risk Drivers
Bibliographic record
Abstract
IMPORTANCE: Clinical tests that identify fit and unfit drivers with 100% sensitivity and specificity would reduce uncertainty and improve efficiency of occupational therapists performing comprehensive driving evaluations (CDEs). OBJECTIVE: To examine whether serial trichotomization of clinical tests predicts pass-fail outcomes with 100% sensitivity and specificity in a sample of medically at-risk drivers and in drivers with and without cognitive impairment (CI) referred for a CDE. DESIGN: Retrospective data collection and analysis of scores on the Montreal Cognitive Assessment; Trail Making Test, Part A and Part B; and the Useful Field of View® Subtests 1 to 3 and outcomes on the CDE (pass-fail or indeterminate requiring lessons and retesting). Receiver operating characteristic curves of clinical tests were performed to determine 100% sensitivity and specificity cut points in predicting CDE outcomes. Clinical tests were arranged in order from most to least predictive to identify pass-fail and indeterminate outcomes. SETTING: A driving assessment clinic. PARTICIPANTS: Among 142 medically at-risk drivers (M age = 69.2 yr, SD = 14.1), 66 with CI, 46 passed and 39 failed the CDE; 57 were indeterminate. OUTCOMES AND MEASURES: On-road pass-fail outcomes. RESULTS: Together, the six clinical tests predicted 62 pass and 49 fail outcomes in the total sample; 21 pass and 34 fail outcomes in participants with CI; and 58 pass and 14 fail outcomes in participants without CI. CONCLUSIONS AND RELEVANCE: Serial trichotomization of clinical tests increases the accuracy of making informed decisions and reduces the number of drivers undergoing unnecessary on-road assessments. Plain-Language Summary: Clinical tests and their cut points that identify fit and unfit drivers vary substantially across settings and research studies. Serial trichotomization is one method that could help control for this variation by combining clinical test scores showing 100% sensitivity and specificity to identify pass (fit drivers) and fail outcomes (unfit drivers) and to reduce the number of drivers undergoing unnecessary on-road assessments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".