Advancing a programme theory for community-level oral health promotion programmes for humanitarian migrants: a realist review protocol
Bibliographic record
Abstract
INTRODUCTION: Humanitarian migrants often suffer from poor health, including oral health. Reasons for their oral health conditions include difficult migration trajectories, poor nutrition and limited financial resources. Oral health promotion is crucial for improving oral health-related quality of life of humanitarian migrants. While community-level oral health promotion programmes for humanitarian migrants have been implemented (eg, in host countries and refugee camps), there is scant literature evaluating their transferability or effectiveness. Given that these programmes yield unique context-specific outcomes, the purpose of this study is to understand how community-level oral health promotion programmes for humanitarian migrants work, in which contexts and why. METHODS AND ANALYSIS: Realist review, a theory-driven literature review methodology, incorporates a causal heuristic called context-mechanism-outcome configurations to explain how programmes work, for whom, and under which conditions. Using Pawson's five steps of realist review (clarifying scope and drafting an initial programme theory; identifying relevant studies; quality appraisal and data extraction; data synthesis; and dissemination of findings), we begin by developing an initial programme theory using the references of a scoping review on the oral health of refugees and asylum seekers and through hand searching in Google Scholar. Following stakeholder validation of our initial programme theory, we will locate additional evidence by searching in four databases (Ovid Medline, Ovid Embase, Cochrane Library and Cumulative Index to Nursing and Allied Health Literature (CINAHL)) to test and refine our initial programme theory into a middle-range realist programme theory. The resultant theory will explain how community-level oral health promotion programmes for humanitarian migrants work, for whom, in which contexts and why. ETHICS AND DISSEMINATION: Since this study is a review and no primary data collection will be involved, institutional ethics approval is not required. The findings of this study will be disseminated in peer-reviewed journals, local and international conferences, and via social media. TRIAL REGISTRATION NUMBER: CRD42021226085.
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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 | 0.199 | 0.201 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.060 | 0.010 |
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".