Impact evaluation of the Northern Fruit and Vegetable Pilot Programme – a cluster-randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: The purpose of this impact evaluation was to measure the influence of a government of Ontario, Canada health promotion initiative, the Northern Fruit and Vegetable Pilot Programme (NFVPP), on elementary school-aged children's psychosocial variables regarding fruit and vegetables, and fruit and vegetable consumption patterns. DESIGN: A cluster-randomised controlled trial design was used. The NFVPP consisted of three intervention arms: (i) Intervention I: Free Fruit and Vegetable Snack (FFVS) + Enhanced Nutrition Education; (ii) Intervention II: FFVS-alone; and (iii) Control group. Using the Pro-Children Questionnaire, the primary outcome measure was children's fruit and vegetable consumption, and the secondary outcome measures included differences in children's awareness, knowledge, self-efficacy, preference, intention and willingness to increase fruit and vegetable consumption. SETTING/SUBJECTS: Twenty-six elementary schools in a defined area of Northern Ontario were eligible to participate in the impact evaluation. A final sample size of 1,277 students in grades five to eight was achieved. RESULTS: Intervention I students consumed more fruit and vegetables at school than their Control counterparts by 0.49 serving/d (P < 0.05). Similarly, Intervention II students consumed more fruit and vegetables at school than Control students by 0.42 serving/d, although this difference was not statistically significant. Among students in both intervention groups, preferences for certain fruit and vegetables shifted from 'never tried it' towards 'like it'. CONCLUSIONS: The NFVPP resulted in positive changes in elementary school-aged children's fruit and vegetable consumption at school, and favourable preference changes for certain fruit and vegetables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".