Evaluating the scaling up of an effective implementation intervention (PACE) to increase the delivery of a mandatory physical activity policy in primary schools
Bibliographic record
Abstract
BACKGROUND: Physically Active Children in Education (PACE) is an effective implementation intervention for increasing the number of minutes classroom teachers schedule physical activity each week. To date, evaluations of PACE have included a smaller number of schools from only one region in New South Wales Australia. If PACE is to have population-wide benefits we must be able to deliver this support to a larger number of schools across multiple regions. This study aimed to evaluate the scale-up of PACE. METHODS: An uncontrolled before and after study, with 100 schools from three regions was conducted. Participating schools received PACE for approximately 12 months. We assessed the following outcomes: delivery of the evidence-based intervention (EBI) (i.e. minutes of physical activity scheduled by classroom teachers per week); delivery of the implementation strategies (i.e. reach, dose delivered, adherence and indicators of sustainability); and key determinants of implementation (i.e. acceptability of strategies and cost). Data were collected via project officer records, and principal and teacher surveys. Linear mixed models were used to assess EBI delivery by evaluating the difference in the mean minutes teachers scheduled physical activity per week from baseline to follow-up. Descriptive data were used to assess delivery of the implementation strategies and their perceived acceptability (i.e. PACE). A prospective, trial-based economic evaluation was used to assess cost. RESULTS: Delivery of the EBI was successful: teachers increas their average minutes of total physical activity scheduled across the school week by 26.8 min (95% CI: 21.2, 32.4, p < 0.001) after receiving PACE. Indicators for delivery of implementation strategies were high: 90% of consenting schools received all strategies and components (reach); 100% of strategies were delivered by the provider (dose); >50% of schools adhered to the majority of strategies (11 of the 14 components); and acceptability was > 50% agreement for all strategies. The incremental cost per additional minute of physical activity scheduled per week was $27 per school (Uncertainty Interval $24, $31). CONCLUSIONS: PACE can be successfully delivered across multiple regions and to a large number of schools. Given the ongoing and scalable benefits of PACE, it is important that we continue to extend and improve this program while considering ways to reduce the associated cost.
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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 | 0.049 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".