Physical activity in Ontario preschoolers: prevalence and measurement issues
Bibliographic record
Abstract
Early childhood is a critical period for the development of active living behaviours; however, very little is known about the physical activity levels of preschoolers from Canada. The objectives of this study were to (i) examine physical activity in a sample of Ontario preschoolers by using high-frequency accelerometry to determine activity and step counts; (ii) assess the relationship between step counts and physical activity; (iii) examine the influence of epoch length or sampling interval on physical activity; and (iv) compare measured physical activity to existing recommendations. Thirty 3- to 5-year-old children wore accelerometers to monitor habitual physical activity in 3-s epochs over a 7-day period. Preschoolers engaged in an average of 220 min of daily physical activity, 75 min of which were spent in moderate-to-vigorous physical activity (MVPA), and they accumulated 7529 ± 1539 steps·day(-1). Preschoolers who engaged in more MVPA also took more steps on a daily basis (r = 0.81, p < 0.001). Compared with a 3-s epoch, sampling intervals of 15, 30, and 60 s resulted in an average of 2.9, 9.0, and 16.7 missed minutes of MVPA per day, respectively. All 30 preschoolers met the National Association for Sport and Physical Education recommendation of at least 120 min of total physical activity per day for preschool-age children. Our data highlight important methodological considerations when measuring physical activity in preschoolers and the need for preschool-specific physical activity guidelines for Canadian children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".