What happened in the ‘Move for Well-being in School’: a process evaluation of a cluster randomized physical activity intervention using the RE-AIM framework
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to address the gap in the translation of research into practice through an extensive process evaluation of the Move for Well-being in School programme using the RE-AIM framework. The purpose was to gain insight into the extent by which the intervention was adopted and implemented as intended and to understand how educators observed its effectiveness and maintenance. METHODS: Public schools located in seven municipalities in Denmark were invited to enroll their 4th to 6th grade classes in the project. Of these, 24 school decided to participate in the project in the school-year 2015-16 and were randomly (cluster) allocated to either intervention or control group. A process survey was completed online by school personnel at the start, at midterm, and at the end of the school year. Additionally, informal interviews and observations were conducted throughout the year. RESULTS: At the 12 intervention schools, a total of 148 educators were involved in the implementation of the programme over the school-year. More than nine out of ten educators integrated brain breaks in their lessons and practically all the physical education teachers used the physical education lesson plans. The educators delivered on average 4.5 brain breaks per week and up to 90% of the physical education teachers used the project lesson plans for at least half of their classes. Half of the educators initiated new recess activities. A total of 78%, 85% and 90% of the educators believed that the implemented recess, brain break and physical education components 'to a high degree' or 'to some degree' promoted the pupils' well-being, respectively. CONCLUSIONS: This study shows that it is possible to design a school-based PA intervention that educators largely adopt and implement. Implementation of the PA elements was stable throughout the school year and data demonstrate that educators believed in the ability of the intervention to promote well-being among the pupils. Finally, the study show that a structured intervention consisting of competence development, set goals for new practices combined with specific materials, and ongoing support, effectively reached a vast majority of all teachers in the enrolled schools with a substantial impact. TRIAL REGISTRATION: Date of registration: retrospectively registered on 24 April 2015 at Current Controlled Trials (DOI 0.1186/ ISRCTN12496336 - named: "The role of physical activity in improving the well-being of children and youth").
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".