School-based health promotion interventions targeting humanitarian migrant children: A narrative review
Bibliographic record
Abstract
Humanitarian migrant children frequently have health issues due to their difficult migration experiences; this is especially true regarding mental, general, and oral health. School staff in their host countries are well-placed for contributing to promoting these children's health and wellbeing. This narrative review originally aimed to understand how school staff can assist humanitarian migrant children with promoting oral health and accessing oral health services. The dearth of literature opened a broader consideration for how lessons learned from experiences with health more broadly can be applied to oral health promotion. A narrative review methodology was employed. Four databases (Ovid Medline, Ovid EMBASE, CINAHL, and ERIC) were searched with relevant MeSH terms and keywords from which we constructed a PRISMA flow diagram. Thematic analysis was used to analyze the included papers. Our final review included 43 papers. Most focused on mental health; no literature addressed oral health. School staff identified humanitarian migrant children's health issues, provided health information to these children, and referred some to health professionals inside and outside school. Challenges preventing staff from intervening effectively included their lack of health-related competence, insufficient time and resources, systemic barriers to accessing health services (e.g., legal status and logistics), cultural and linguistic barriers, and racism and discrimination. Facilitators included establishing trust and safety, involving families, bridging cultural and linguistic gaps, coordination collaboration among school staff and between school staff and health services, and integrating health services in school. Schools are important portals for humanitarian migrant children's health. School staff can make an important impact on humanitarian migrant children's health, and especially so if the many barriers are addressed. While staff may be engaged in promoting oral health, we found no literature addressing oral health. More research on oral health interventions for humanitarian migrant children in schools can shed light on processes that may be specific to oral health promotion for these children. • Schools are portals for supporting migrant children's health. • School staff help children by identifying needs, conditions and making referrals to professionals. • Barriers: staff's lack of knowledge, time, resources; systemic issues, cultural gaps, stigma. • Facilitators: trust, family engagement, bridging cultures, collaboration, school services. • More research is needed on how schools can promote oral health.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".