A Meta-Synthesis Study on International Studies on School Health Education
Bibliographic record
Abstract
School health education is an important tool in sustaining the health of societies and is increasingly being included in studies. The aim of this study is to systematically identify and bring together school health education studies conducted in the last 10 years at the international level and to conduct a meta-synthesis. In this context, 25 journal articles conducted between 2015-2025 were analyzed with a planned meta-synthesis study within the qualitative research design. Google Scholar, ERIC and Web of Science databases were used to determine the studies to be included in the study. In the school health education studies examined in this study, more studies were reached in the fields of nutrition and oral health. In addition, in the school health education studies examined, the effects of education on the participants were generally examined using quantitative methods and data collection tools. In the studies examined, the study group generally consisted of primary and secondary school students; the studies were generally conducted over a 6-18 months study period. Finally; in the school health education studies examined in the study, more studies conducted in Indonesia, America and China were reached. It is expected that this study will provide a detailed look at the school health education studies conducted in recent years and inspire future health education studies.
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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 | 0.080 | 0.255 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".