Factors associated with implemented teacher-led movement and physical activity in early childhood education and care
Bibliographic record
Abstract
Movement and physical activity (MoPA) is critical for children’s development and health. This study aimed to explore early childhood education and care (ECEC) educators’ reported frequency of implemented gross motor and physical activities (MoPA) among children in ECEC, as well as the educators’ reported personal physical activity (PA) levels in leisure time. A cross-sectional survey was performed in 68 preschools in southern Sweden. Data were obtained from questionnaires completed by 359 ECEC educators. The participation rate was 61%. About two thirds offered MoPA once a week or more seldom, while one quarter offered MoPA at least every other day. Educators who reported personal PA three times or more per week, offered MoPA for the children at least every other day to a higher extent (37%) compared to colleagues who reported personal PA once or twice a week (26%) or colleagues who reported that they were never or seldom active (18%) (p = 0.034). The results from multiple logistic regression analysis showed that reported implemented MoPA among children in ECEC was significantly associated with the educators’ perceptions that free play improved children’s gross motor skills (OR 2.7), the educators’ perceptions of needed curricular guidelines for MoPA (OR 2.1), the educators’ own leisure PA level (OR 2.0) and the educators’ perceptions that adequate gross motor skills were not learned at home (OR 0.4). Teacher-led MoPA occurs sparingly during the preschool day and the teachers believe that the children get sufficient MoPA in free play. The children are expected to develop their motor skills to a sufficient extent during the short moments of offered outdoor play. Teachers who are physically active in their leisure-time seem to offer gross motor training for the children to a higher extent than less active or inactive colleagues.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".