Pilot Efficacy of a DriveFocus™ Intervention on the Driving Performance of Young Drivers
Bibliographic record
Abstract
Road traffic injuries are the leading cause of death for youth between the ages of 15 to 29 around the world. A need remains for evidence-based interventions that can improve the underlying skills of young drivers, including hazard perception and anticipation. This pilot study investigated the preliminary impact of a six session DriveFocus™ intervention on the ability of young novice drivers (mean age= 18.6, SD= 2.12) to detect (visual scanning), and respond (adjustment to stimuli) to critical roadway information. Using a CDS-200 DriveSafety™ simulator, drives were recorded and sent to a blinded evaluator (occupational therapist), who scored the recorded drives for number and type (visual scanning and adjustment to stimuli) of errors. We observed a statistically significant decline in the number of visual scanning (t(34) = 2.853, p= .007), adjustment to stimuli (t(34) = 3.481, p= .001), and total driving errors (t(34) = 3.481, p= .002), among baseline and post-test 2.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".