Visual Correlates of Fitness to Drive in Adults With Multiple Sclerosis
Bibliographic record
Abstract
The impact of visual and visual-cognitive impairments on fitness to drive in persons with multiple sclerosis (PwMS) are not well studied. We quantified visual correlates of fitness to drive in 30 PwMS. PwMS completed visual ability and visual attention assessments, and a standardized on-road assessment, and were compared with 145 older volunteer drivers. PwMS (vs. older volunteer drivers) made more total ( W = 12,139, p = .03) and critical driving errors (predictive of crashes) in adjustment to stimuli ( W = 11,352, p < .0001), vehicle positioning ( W = 11,449, p < .0001), and wide lane turns ( W = 9,932, p < .0001). PwMS who failed (vs. passed) made more total ( W = 325, p = .04), adjustment to stimuli ( W = 321.5, p = .02), and gap acceptance errors ( W = 333, p = .03). For PwMS, adjustment to stimuli errors moderately correlated with visual acuity (ρ = .50, p = .006), and gap acceptance errors moderately correlated with visual processing speed (ρ = .40, p = .03). Visual-cognitive impairments may be indicative of critical driving errors and help identify PwMS at-risk for 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".