Realist evaluation of intersectoral oral health promotion interventions for schoolchildren living in rural Andean communities: a research protocol
Bibliographic record
Abstract
BACKGROUND: Intersectoral collaboration, known to promote more sustainable change within communities, will be examined in an oral health promotion program (OHPP). In Peru, an OHPP was implemented by the Ministry of Health, to reduce the incidence of caries in schoolchildren. In rural Andean communities, however, these initiatives achieved limited success. The objectives of this project are: (1) to understand the context and the underlying mechanisms associated with Peruvian OHPP's current effects among school children living in rural Andean communities and (2) to validate a theory explaining how and under which circumstances OHP intersectoral interventions on schoolchildren living in rural Andean communities produce their effects. METHODS AND ANALYSIS: Through a realist evaluation, the context, underlying mechanisms and programme outcomes will be identified. This process will involve five different steps. In the first and second steps, a logic model and an initial theory are developed. In the third step, data collection will permit measurement of the OHHP's outcomes with quantitative data, and exploration of the elements of context and the mechanisms with qualitative data. In the fourth and fifth steps, iterative data analysis and a validation process will allow the identification of Context-Mechanism-Outcome configuration, and validate or refine the initial theory. ETHICS AND DISSEMINATION: This research project has received approval from the Comité d'éthique de la recherche en santé chez l'humain du Centre hospitalier universitaire de Sherbrooke. The initial theory and research results will be published in relevant journals in public health and oral health. They will also be presented at realist evaluation and health promotion international conferences.
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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 | 0.092 | 0.061 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.004 |
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".