'Many voices, one song': a model for an oral health programme as a first step in establishing a health promoting school
Bibliographic record
Abstract
Four health promoting (HP) schools were established in rural communities in Uganda by a joint Ugandan/Canadian university team. The model was based on a successful Canadian health promotion initiative designed to address poor oral health in Aboriginal children in rural and remote communities. Careful situation analysis, orientation of partner schools and collaborative development of educational materials and evaluation methodology preceded implementation. The intervention had three elements: inclusion of health topics by teachers in regular classroom activities; health education delivered by the university team to reinforce key educational concepts; and daily in-school tooth brushing to develop healthy practices. All children entering Grade 1 at four schools were recruited for 4 years; evaluation included year 1 pre-intervention and annual end-of-year data collection of quantitative and qualitative measures. Principal findings at 4 years included: an increase from baseline in the original cohort (n = 600) in those brushing at least once daily (p < 0.05) and before bed (p < 0.05); improved oral health (less 'bad breath', pain and absences for emergency dental treatment); more comprehensive health knowledge. Other positive observations were change in the schools' health culture; children sharing new health knowledge and advocating for health practices learned; and evolution of health promotion activity to address other community-identified issues following success with the initial oral health component. University faculty and students learned from participation in programme delivery and community-based educational opportunities. School-based health promotion using this oral health model was readily accepted, implemented, sustained and evaluated; all communities took ownership, and all schools continue their programmes. Addressing oral health through HP schools is novel in Africa, and several lessons learned are of potential value for similar health promotion initiatives in sub-Saharan Africa.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".