Changes in Physical Activity in the School, Afterschool, and Evening Periods During the Transition From Elementary to Middle School
Bibliographic record
Abstract
BACKGROUND: We examined longitudinal changes in children's physical activity during the school day, afterschool, and evening across fifth, sixth, and seventh grades. METHODS: The analytical sample included children who had valid accelerometer data in fifth grade and at least one other time-point, and provided complete sociodemographic information (N = 768, 751, and 612 for the 3 time-periods studied). Accelerometer-derived total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) were expressed in minutes per hour for the school day (∼7:45 am to 3:30 pm), afterschool (∼2:25 to 6:00 pm), and evening (6:00 to 10:00 pm) periods. We used growth curve analyses to examine changes in TPA and MVPA. RESULTS: School day TPA and MVPA declined significantly; we observed a greater decrease from fifth to sixth grades than from sixth to seventh grades. Afterschool TPA declined significantly, but MVPA increased significantly among girls and remained stable for boys. Evening TPA decreased significantly and MVPA declined significantly in girls and remained stable among boys. CONCLUSIONS: To inform the development of effective intervention strategies, research should focus on examining factors associated with the decline in physical activity during the transition from elementary to middle school, particularly during the hours when children are in school.
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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) | 0.000 | 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 | 0.001 |
| 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".