The impact of coaches providing healthy snacks at junior sport training
Bibliographic record
Abstract
OBJECTIVE: Sports clubs provide an opportunity to tackle childhood obesity rates through targeted interventions. Our study aimed to investigate if coaches providing healthy snacks to participants before junior netball sessions at five clubs in Melbourne, Australia, increased consumption of healthy foods and influenced coach perceptions of participants' attention/participation levels. METHODS: Coaches provided healthy snacks to participants before each netball session for one school term. Children's food consumption was observed at one session before, during and after the intervention. Parents attending the observed session completed pre- and post-intervention questionnaires. Coaches rated participants' attention/participation at the observed sessions before and during the intervention, and completed a questionnaire post-intervention. RESULTS: Baseline: Ice cream and cake were the most frequently consumed snacks. During intervention: Fruit, cheese and crackers and vegetables were the most frequently consumed snacks. Coaches ratings of participants' attention/participation increased significantly (baseline: 6.4 ± 0.17, intervention: 7.5 ± 0.36; p=0.02) where the same coach undertook ratings at both time points. CONCLUSIONS: Coaches providing healthy snacks before sessions at sports clubs increased consumption of nutrient-dense foods at the session, and may have positively affected participants' attention/participation. Implications for public health: This study highlights how a simple intervention could improve the diet of Australian children.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".