The relationship between transport-to-school habits and physical activity in a sample of New Zealand adolescents
Bibliographic record
Abstract
Adolescents using active transport (AT) to school have higher levels of physical activity (PA) compared with motorized transport (MT) users. This study compared school day and weekend day PA in adolescents using AT, MT, or combined AT and MT (AT + MT) to travel to school. Adolescents (n = 314; age: 14.7 ± 1.4 years; 32.8% boys) from Dunedin (New Zealand) wore an accelerometer for 7 days and completed a self-reported survey regarding mode of transport to school (73 AT, 56 AT + MT, and 185 MT). Data were analyzed using t tests, analysis of variance, and χ2 tests. Although the proportion of adolescents meeting PA guidelines significantly differed among transport groups (AT, 47.9%; AT + MT, 46.4%; MT, 33.5%; p = 0.048; overall, 39.2%), the observed differences were due mainly to girls. Compared with MT, AT and AT + MT engaged in more moderate-to-vigorous PA (MVPA) per day (AT: 61.2 ± 23.2 min; AT + MT: 59.6 ± 21.7 min; MT: 52.5 ± 19.6 min; p = 0.004; p < 0.001, adjusted for gender), per school day and before school. Immediately after school (15:00–16:00), AT engaged in significantly more MVPA compared with AT + MT and MT. No differences in MVPA between the groups were observed in the late afternoon/early evening period during school days or on weekend days. Compared with MT users, adolescent girls using AT or AT + MT accumulated more MVPA during school commute time. AT + MT to school is also a plausible way to increase adolescent girls’ PA when AT only is not feasible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".