Driving Down Daily Step Counts: The Impact of Being Driven to School on Physical Activity and Sedentary Behavior
Bibliographic record
Abstract
This study investigated whether being driven to school was associated with lower weekday and weekend step counts, less active out-of-school leisure pursuits, and more sedentary behavior. Boys aged 10-13 years (n = 384) and girls aged 9-13 years (n = 500) attending 25 Australian primary schools wore a pedometer and completed a travel diary for one week. Parents and children completed surveys capturing leisure activity, screen time, and sociodemographics. Commute distance was objectively measured. Car travel was the most frequent mode of school transportation (boys: 51%, girls: 58%). After adjustment (sociodemographics, commute distance, and school clustering) children who were driven recorded fewer weekday steps than those who walked (girls: -1,393 steps p < .001, boys: -1,569 steps, p = .009) and participated in fewer active leisure activities (girls only: p = .043). There were no differences in weekend steps or screen time. Being driven to and from school is associated with less weekday pedometer-determined physical activity in 9- to 13-year-old elementary-school children. Encouraging children, especially girls, to walk to and from school (even for part of the way for those living further distances) could protect the health and well-being of those children who are insufficiently active.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".