Comparing physical activity and sedentary time among overweight and nonoverweight preschoolers enrolled in early learning programs: a cross-sectional study
Bibliographic record
Abstract
Establishing appropriate physical activity and sedentary behaviours during early childhood is important to ensure children accrue the many associated health benefits. While physical activity levels have been reported as low within early learning programs, little research has explored the physical activity and sedentary time of Canadian preschoolers classified as overweight within these facilities. The purpose of this study was to compare objectively measured physical activity and sedentary time among preschoolers classified as overweight and nonoverweight in early learning programs. Direct assessment of physical activity and sedentary time of 216 preschool-aged children was collected via Actical accelerometers during early learning hours, while body mass index percentile was calculated based on preschoolers' objectively measured height and weight. Results of three 3-way ANOVAs suggest that rates of moderate to vigorous physical activity, total physical activity, and sedentary time (p > 0.05) did not significantly differ based on weight status, sex, and type of early learning facility. This study is one of few that has examined differences in overweight and nonoverweight preschoolers' sedentary time, and adds to the limited research exploring physical activity levels among overweight and nonoverweight preschoolers during early learning hours. Given the high rates of sedentary time reported, programming within early learning facilities is necessary to support preschoolers, regardless of weight status, to achieve increased physical activity levels and decreased sedentary time.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".