Serial Trichotomization to Determine Fitness to Drive: Results From a Cohort of Clients Referred to a Neurology Program
Bibliographic record
Abstract
IMPORTANCE: Determining cognitive fitness to drive is challenging. A previous study used serial trichotomization with five cognitive tests to determine whether drivers should continue driving, undergo further evaluation, or stop driving. OBJECTIVE: To examine agreement between serial trichotomization and fitness-to-drive determinations made by occupational therapists. DESIGN: Drivers referred for cognitive screens completed all tests used in the previous study. Occupational therapists provided fitness-to-drive recommendations (safe, indeterminate, or unsafe) using all clinical information available. We examined the agreement between the tests' results (using cut points from the previous study) and occupational therapists' recommendations. SETTING: Outpatient neurology program at a chronic care and rehabilitation hospital. PARTICIPANTS: 279 clients (M age = 66.35 yr; SD = 13.25). OUTCOMES AND MEASURES: Tests included the Trail Making Tests A and B, the Clock Drawing Test (CDT), the Montreal Cognitive Assessment, and the Motor-Free Visual Perception Test, using a road test as the gold standard. The previous study used dual cut points with 100% sensitivity and specificity to reduce false positives and false negatives. RESULTS: Weighted κs ranged from .03 (95% confidence interval [CI] [-.01, .08]) for the CDT to .54 (95% CI [.46, .62]) for the Trail Making Test, Part B. Although the agreement between serial trichotomization and the final recommendations was moderate (κ = .59; 95% CI [.50, .67]), serial trichotomization appeared useful for identifying unsafe drivers. CONCLUSIONS AND RELEVANCE: These results remind us of the variability inherent in stand-alone cognitive tests, even within a serial trichotomization framework, and the importance of clinical judgement and road tests in decision making about driving. Plain-Language Summary: It can be challenging for occupational therapists to accurately determine a client's cognitive fitness to drive. Many occupational therapists lack the time, have limited training, or do not have access to comprehensive driving evaluation tools. A serial testing approach can support occupational therapists in assessing a client's cognitive fitness to drive. This study used an approach based on a series of five cognitive tests to determine whether a client should continue driving, undergo further evaluation, or stop driving. The series of tests were used to classify drivers as safe, indeterminate, or unsafe. In principle, a driver would take the second test only if the driver was classified as indeterminate on the basis of first test, and so on. By applying the tests in sequence, few drivers should remain classified as indeterminate at the end of the series of tests. This serial approach has the potential to streamline the decision-making process for occupational therapists by classifying the more extreme unsafe cases while still providing an accurate assessment of cognitive fitness to drive.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".