Older Driver Training Using Video and Global Positioning System Technology--a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: There is emerging evidence that older driver training programs with on-road instruction are more effective than driver education programs that are conducted only in the classroom. Although most programs have provided this additional in-vehicle training with a driving instructor and a dual-braked vehicle, technology could assist in providing this feedback. It was hypothesized that participants who received video and global positioning system (GPS) feedback (Video group) in addition to classroom education would improve to a greater extent than those who received a classroom-based course alone (Education) or Control participants. METHODS: Fifty-four participants (32 men and 22 women), 70-89 years old, randomized to one of the three groups, completed the study. All participants underwent pre- and postintervention driving tests, in their own vehicle, on a standardized route, that were recorded with video and GPS equipment. The Video group met with a driving instructor to receive feedback on their driving errors in their preintervention driving test. A blinded assessor scored all driving tests in random order. RESULTS: The Video group significantly reduced their driving errors by 25% (p < .05) following the intervention, whereas the other two groups did not change significantly. Fifty-two percent of participants from the Video group improved their global safety rating, whereas only 5.3% in the Control and 22.2% in the Education groups did. CONCLUSIONS: This study suggests that direct driving feedback using video and GPS technology could be an effective and novel means to provide older driver education.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".