Dissemination and implementation of a policy on school health in public schools: A systematic review
Bibliographic record
Abstract
BACKGROUND: The need to achieve school health and promote well-being that would transcend children's school life has been highlighted in several studies. Promotion of health and well-being of children has not been achieved despite the prescripts of the World Health Organization and national mandates. OBJECTIVES: The purpose of this systematic review was to explore and describe the current evidence on the dissemination and implementation of a policy on school health in public schools. METHODS: Five steps of a systematic review were used to achieve the purpose of the study. The steps include framing a clear review question, developing a search approach through gathering and classifying evidence, conducting a critical appraisal, evidence summary as well as the results. Ebscohost, SAE publications, Web of Science and JSTOR databases were used to identify articles written between 2013 and 2018 and to enable access to current studies on the promotion of school health. Keywords included the following: dissemination; implementation; school health policy; and public schools. The search yielded n = 1995 articles. From this figure, 1976 articles were ineligible and only 19 articles met the inclusion criteria. RESULTS: Seven themes emerged from the findings of this systematic review as follows: shared information, training and development of key role-players, programme development and research, commitment from key role-players, monitoring activities, executive support and collaborative partnerships. CONCLUSION: The findings show that it is possible for a policy on school health to be disseminated and implemented effectively in public schools.
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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 | 0.126 | 0.338 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| 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".