A mixed-methods exploration of implementation of a comprehensive school healthy eating model one year after scale-up
Bibliographic record
Abstract
OBJECTIVE: To study the implementation of a school-based healthy eating (HE) model one year after scale-up in British Columbia (BC). Specifically, to examine implementation of Action Schools! BC (AS! BC) and its influence on implementation of classroom HE activities, and to explore factors associated with implementation. DESIGN: Diffusion of Innovations, Social Cognitive and Organizational Change theories guided our approach. We used a mixed-methods research design including focus group interviews (seven schools, sixty-two implementers) and a cross-sectional multistage survey to principals (n 36, 92 % response rate) and teachers of grades 4 to 7 (n 168, 70 % response rate). Self-reported implementation of classroom HE activities and reported use of specific AS! BC HE activities were primary implementation measures. Thematic analysis of focus group data and multilevel mixed-effect logistic regression analyses of survey data were conducted. SETTING: Elementary schools across BC, Canada. SUBJECTS: Thirty-nine school districts, thirty-six principals, 168 grade 4 to 7 teachers. RESULTS: Forty-two per cent of teachers in registered schools were implementing AS! BC HE in their classrooms. Users were 6·25 times more likely to have delivered a HE lesson in the past week. Implementation facilitators were school champions, technical support and access to resources; barriers were lack of time, loss of leadership or momentum. Implementation predictors were teacher training, self-efficacy, experience with the physical activity component of AS! BC, supportive school climate and parental post-secondary education. CONCLUSIONS: Our findings reinforce that continued teacher training and support are important public health investments that contribute to successful implementation of school-based HE models after scale-up.
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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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".