‘We're Not in a Place Where We Can Thrive Yet’: A Qualitative Exploration of Systems of Health Promotion in Primary Schools in the Aftermath of the COVID‐19 Pandemic
Bibliographic record
Abstract
BACKGROUND: Health promotion in schools can be defined as any activity undertaken to improve the health of all school users. This qualitative study aimed to explore the systems of health promotion in primary schools in the aftermath of the COVID-19 pandemic, from the perspectives of teachers and principals in the Republic of Ireland. METHODS: Participants were recruited using snowball and convenience sampling techniques via a larger quantitative study. Participants joined 45-min online focus groups informed by a semi-structured interview guide. A reflexive thematic approach was taken to analysis. RESULTS: Thirty teachers participated, and most (n = 26) identified as female. Teaching experience across the sample ranged from 2 to 38 years. School sizes ranged from 20 to 850 students. All types of eligible publicly funded schools were represented. Three themes were generated: rebuilding the foundation, choosing within our limits and drawing the line. CONCLUSION: Findings indicate that systems of health promotion in primary schools were severely challenged during the COVID-19 pandemic and that recovery will be lengthy. School communities are well-positioned to have a leading role in primary and secondary disease prevention, but investment is needed to establish resilient frameworks for health promotion as child health issues provoked by the pandemic are addressed over the coming years.
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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 | 0.032 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.026 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".