Systematic Review of School‐Based Interventions to Modify Dietary Behavior: Does Intervention Intensity Impact Effectiveness?
Bibliographic record
Abstract
BACKGROUND: Owing to the associations between diet and health, it is important that effective health promotion strategies establish healthful eating behaviors from an early age. We reviewed the intensity of school-based interventions aimed to modify dietary behavior in preadolescent and adolescents and related intervention characteristics to effectiveness. METHODS: Our systematic literature search of 8 databases sought to identify interventions measuring dietary intake in school settings to students aged 9 to 18. We evaluated these studies for effectiveness, intensity, intervention category, and follow-up measures. RESULTS: Of the 105 interventions 81 were found to be effective immediately postintervention, irrespective of intensity. Studies that were 6 weeks to 5 months in duration, targeted students' environment or group (alone or in combination), and reached students only in schools were more effective. Only one-fifth of interventions conducted a follow-up measure, and a majority showed a loss of effectiveness from postintervention to follow-up. CONCLUSIONS: We identified characteristics of effective interventions. These findings may inform the development of future interventions targeting dietary behavior in preadolescents and adolescents in the school-based setting.
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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 | 0.019 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.009 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".