How to Motivate Childcare Workers to Engage Preschoolers in Physical Activity
Bibliographic record
Abstract
BACKGROUND: Data available indicate that numerous childcare workers are not strongly motivated to engage children aged 3-5 in physical activity. Using the theory of planned behavior as the main theoretical framework, this study has 2 objectives: to identify the determinants of the intention of childcare workers to engage preschoolers in physical activity and to identify the variables that could be used to develop an intervention to motivate childcare workers to support preschoolers' physical activity. METHODS: 174 childcare workers from 60 childcare centers selected at random in 2 regions of Quebec completed a self-administered questionnaire assessing the constructs of the theory of planned behavior as well as past behavior, descriptive norm and moral norm. RESULTS: Moral norm, perceived behavioral control and subjective norm explained 85% of the variance in intention to engage the children in physical activity. CONCLUSIONS: To motivate childcare workers, it is necessary that they perceive that directors, children's parents and coworkers approve of their involvement in children's physical activity. In addition, their ability to overcome perceived barriers (lack of time, loaded schedule, inclement weather) should be developed. Access to a large outdoor yard might also help motivate childcare workers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".