An Exploratory, Cluster Randomised Control Trial of the PAX Good Behaviour Game
Bibliographic record
Abstract
This article presents the findings of an exploratory randomised controlled trial of the PAX Good Behaviour Game (PAX GBG) in Northern Ireland. The PAX GBG is an evidence‐based universal prevention programme designed to improve mental health by increasing self‐regulation, academic engagement, and decreasing disruptive behaviour in children. The study was designed in line with the Medical Research Council guidance on the development of complex interventions and is based on the Medical Research Council framework, more specifically within a Phase 2 exploratory trial. The study used a cluster randomised controlled trial design with a total of 15 schools (19 classes) randomised to intervention and control. This article reports specifically on the outcome of self‐regulation with 355 elementary school pupils in year 3 (age M = 7.40, SD = 0.30). Participating schools in the trial were located in areas of socio‐economic disadvantage. The teachers in the intervention group received training in the delivery of the PAX GBG and implemented the PAX GBG intervention for 12 weeks. A range of pre‐ and post‐test measures, including child reported behaviours, were undertaken. After the 12 weeks of implementation, this exploratory trial provided some evidence that the PAX GBG may help improve self‐regulation (d = .42) in participating pupils, while the findings suggest that it may offer a feasible mental health prevention and early intervention approach for Northern Ireland classrooms. However, a larger definitive trial would be needed to verify the findings in this study.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".