What is known about school-based interventions for health promotion and their impact in developing countries? A scoping review of the literature
Bibliographic record
Abstract
Schools can play an important role in health promotion mainly by improving students' health literacy, behaviors and academic achievements. School-based health promotion can be particularly valuable in developing countries facing the challenges of low health literacy and high burden of disease. We conducted a scoping review of the published literature focusing on school-based interventions for health promotion and their impact in developing countries. We included 30 studies meeting specific criteria: (i) studies mainly targeted school going children or adolescents; (ii) admissible designs were randomized controlled trials, controlled before-after studies or interrupted time series; (iii) studies included at least one measure of impact and (iv) were primary studies or systematic reviews. We found that school-based interventions can be classified in two main categories: those targeting individual determinants of health such as knowledge, skills and health behaviors and those targeting environmental determinants such as the social and physical environment at the school, family and community level. Findings suggest that a comprehensive approach addressing both individual and environmental determinants can induce long-term behavior change and significantly improve health and educational outcomes. We highlight the need for further study of the long-term impact of school-based interventions on health outcomes in developing countries.
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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 | 0.014 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".