Impact Evaluation of an After-school Cooking Skills Program in a Disadvantaged Community: Back to Basics
Bibliographic record
Abstract
PURPOSE: Few efficacious child obesity interventions have been converted into ongoing community programs in the after-school setting. The aim of this study was to evaluate the impact of phase 2 of the Back to Basics cooking club on dietary behaviours and fruit and vegetable variety in a population at risk of obesity at a low income school with > 10% indigenous population. METHODS: Baseline and 3-month dietary intake and social cognitive theory (SCT) constructs were collected in 51 children, mean age 9 years, 61% female. McNemar tests were used for comparison of proportions between categorical variables. Cohen's d was used to compare effect sizes across different measures. RESULTS: Consumption of one or more fruit servings per day significantly increased from 41% to 67% (P = 0.02, d = 0.13) and there was a trend for increasing the weekly variety of fruit and vegetables. The SCT constructs assessed within the current study improved significantly (P < 0.05), with moderate to large effect sizes (d = 0.33-0.78). CONCLUSION: This study documents that a previous efficacious healthy lifestyle program can be adapted for use as an obesity prevention program addressing improvements in vegetable and fruit intakes in a low income community with a relatively high indigenous population.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".