Cardiovascular health promotion in schools of Delhi, India: A baseline evaluation of environment and policies
Bibliographic record
Abstract
Background: Cardiovascular diseases (CVDs) are one of the most common causes of morbidity and mortality. Most of the risk factors of CVDs develop early in childhood. Schools immensely influence the thinking pattern of students and can thus shape their behavior. However, no amount of knowledge and awareness can change health behaviours of students until they get support from enabling environment in the schools. The Ottawa charter has also emphasized on building healthy public policy and creating supportive environments for health promotion in schools. Materials and Methods: The present study was conducted in 10 schools in Delhi, India. School policies, environment, community participation and approach of school health agency were assessed by interviewing authorities, review of related documents and direct observation in schools. Results: It was found that none of the schools had any written health policy. Environment in most of the schools was not conducive for cardiovascular health promotion. Conclusion: The study highlights that the schools lack health policies and environment for cardiovascular health and also points out the approach of school health agency, focusing on medical check-ups and treatment of minor illnesses.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".