Feasibility of DriveFocus™ and Driving Simulation Interventions in Young Drivers
Bibliographic record
Abstract
Motor vehicle collisions are the leading cause of death among North American youth, with a high prevalence of distraction-related fatalities. Youth-focused interventions must address detecting (visual scanning) and responding (adjustment to stimuli) to critical roadway information. In this repeated measures study, we investigated the feasibility (i.e., recruitment and sample characteristics; data collection procedures; acceptability of the intervention; resources; and preliminary effects) of a DriveFocus™ app intervention on youth's driving performance. Thirty-four youth participated in a 9-week protocol (retention rate = 89.7%; adherence rate = 100%). No participants experienced simulator sickness. A preliminary nonparametric evaluation of the results ( n = 34) indicated a statistically significant decrease in the number of visual scanning, F(2, 68) = 3.769, p = .028, and adjustment to stimuli, F(2, 68) = 6.759, p = .002, errors between baseline, midpoint, and posttest. This study lays the foundation to support a targeted intervention trial to improve youth's attention to critical road information, building on their mobile technology preferences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".