[Determinants of collaborative practices in schools in promoting healthy eating and physical activity and role of the nurse in these practices].
Bibliographic record
Abstract
CONTEXT: Overweight and obesity rates have more than doubled among 12 to 17 year-olds over the past 25 years. To date, few studies have documented collaborative practices in activities aimed at promoting healthy eating and physical activity in schools, although collaboration is a key element in health promotion. OBJECTIVES: To identify the determinants that influence collaborative practices in secondary schools. To define the role of the school nurse in these practices. METHOD: A descriptive multiple case study was conducted in three Quebec secondary schools. The methods used were: focus group; interviews (21); observation (5); and document review (3). Qualitative analysis was conducted by more than one researcher. RESULTS: Determinants of collaborative practices relate to the individual, team and organization. The time needed to adapt to a role is a determinant that influences the contribution a newly appointed school nurse can make to collaborative practices in a school setting. CONCLUSION: Understanding the determinants that influence collaborative practices paves the way to establishing the conditions conducive to various stakeholders becoming involved in promoting the health of young people.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".