Evaluating a Fruit and Vegetable Program: In Eastern Ontario Schools
Bibliographic record
Abstract
PURPOSE: Effectiveness was evaluated for a fruit and vegetable program developed to encourage Canadian elementary school children to eat the recommended number of daily servings. Also examined was whether the program modified children's personal factors, perceived social environment, and perceived physical environment. METHODS: A prospective, quasi-experimental trial was conducted to compare the eight schools receiving the intervention curriculum (Freggie Friday schools [FFS]) with six control schools (CS). A food frequency questionnaire was used to measure differences in fruit and vegetable consumption. Personal factors, perceived social environment, and perceived physical environment supporting fruit and vegetable consumption were assessed with an adapted version of the validated Pro Children study questionnaire. RESULTS: Of the 942 children who completed the baseline assessment, 807 also completed the follow-up questionnaire (FFS, 450; CS, 357). A mixed-effects regression model indicated no significant intervention effects on fruit or vegetable consumption, snack food consumption, or knowledge or attitudes related to fruit and vegetable consumption. CONCLUSIONS: The results suggest that an intervention based on a single visit from an external group, followed by teacher-led programming, may be an ineffective method of eliciting dietary behaviour change in this population. Future programs may need to implement multicomponent intervention designs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".