The oral health of refugees and asylum seekers: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Improving the oral health of refugees and asylum seekers is a global priority, yet little is known about the overall burden of oral diseases and their causes for this population. OBJECTIVE: To synthesize available evidence on the oral health of, and access to oral health care by this population. METHODS: Using a scoping review methodology, we retrieved 3321 records from eight databases and grey literature; 44 publications met the following inclusion criteria: empirical research focused on refugees and/or asylum seekers' oral health, published between 1990 and 2014 in English, French, Italian, Portuguese, or Spanish. Analysis included descriptive and thematic analysis, as well as critical appraisal using the Critical Appraisal Skills Programme (CASP) criteria for quantitative and qualitative studies. RESULTS: The majority of publications (86 %) were from industrialized countries, while the majority of refugees are resettled in developing countries. The most common study designs were quantitative (75 %). Overall, the majority of studies (76 %) were of good quality. Studies mainly explored oral health status, knowledge and practices; a minority (9 %) included interventions. The refugee populations in the studies showed higher burden of oral diseases and limited access to oral health care compared to even the least privileged populations in the host countries. Minimal strategies to improve oral health have been implemented; however, some have impressive outcomes. CONCLUSIONS: Oral health disparities for this population remain a major concern. More research is needed on refugees in developing countries, refugees residing in refugee camps, and interventions to bridge oral health disparities. This review has utility for policymakers, practitioners, researchers, and other stakeholders working to improve the oral health of this population.
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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 | 0.012 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| 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".