What influences physical activity provision in after-school childcare in the absence of policy guidance? A qualitative exploration
Bibliographic record
Abstract
Objective: This study explored factors affecting the implementation of good-quality physical activity provision in after-school childcare delivered in a Canadian jurisdiction without specific policy, standards or active interventions aimed at increasing physical activity underway. Design: Case study design theoretically guided by the implementation literature. Method: Of the 80 childcare centres in Victoria, British Columbia, Canada, 50 were eligible or available to participate. Managers from centres who agreed to participate responded to direct recruitment ( n = 9); an additional seven staff were recruited through snowball sampling (n = 7). Semi-structured interviews explored macro-, organisational- and individual-level factors influencing implementation. Coding strategies suggested by grounded theory (open, axial and selective), constant comparison with the literature and an a priori conceptual framework were used to analyse the data. Results: Three primary themes (‘Being confined’, ‘Working together to pull it off’ and ‘It takes skill’) and three subthemes (‘It’s a moving target’, ‘We have to make do’ and ‘Centre rules and routines dictate practice’) emerged from the analysis. Conclusion: The study contributes to the understanding of facilitators and barriers to the implementation of good-quality physical activity provision in typical after-school childcare centres. This information can inform guideline and implementation resource development.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".