A cluster randomised controlled trial to assess the effectiveness of a multi-strategy sustainability intervention on teachers’ sustained implementation of classroom physical activity breaks (energisers): study protocol
Bibliographic record
Abstract
BACKGROUND: Governments internationally have invested hugely in the implementation and scale-up of school-based physical activity interventions, but have little evidence of how to best sustain these interventions once active implementation support ceases. This study will assess the effectiveness of a multi-strategy sustainability intervention on classroom teachers' sustainment of energisers (short 3-5 min physical activity breaks during class-time) scheduled across the school day from baseline to 12 and 24-month follow-up. METHODS: A cluster randomised controlled trial will be conducted in 50 primary schools within the Hunter New England, Illawarra Shoalhaven, Murrumbidgee and Northern New South Wales (NSW) Local Health Districts of NSW Australia. Schools will be randomly allocated to receive either usual support or the multi-strategy sustainability intervention that includes: centralised technical assistance from a trained project officer; formal commitment and mandated change obtained from school principals; training in-school champions; reminders for teachers; educational materials provided to teachers; capturing and sharing local knowledge; and engagement of parents, carers and the wider school community. The primary trial outcome will be measured via a teacher logbook to determine the between-group difference in the change in mean minutes of energisers scheduled across the school day at 12 and 24-month follow-up compared to baseline. Analyses will be performed using an intention to treat framework. Linear mixed models will be used to assess intervention effects on the primary outcome at both follow-up periods. DISCUSSION: This study will be one of the first randomised controlled trials to examine the impact of a multi-strategy sustainability intervention to support schools' sustainment of a physical activity intervention. The proposed research will generate new evidence needed for the partnering organisations to protect their considerable investments to date in physical activity promotion in this setting and will provide seminal evidence for the field globally. TRIAL REGISTRATION: August 2023.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".