Newcomers' perceptions of their experiences with oral health care in Canada and the United States.
Bibliographic record
Abstract
Background: Recently, an increasing number of immigrants and asylum seekers and refugees (ASRs) have settled in both Canada and the United States. The poor oral health status prevalent among this population is a significant issue. Oral health professionals in both countries should understand newcomers' experiences with oral health care services to become more culturally competent. This narrative review aims to explore the experiences of immigrants and ASRs with oral health care in Canada and the United States and identify research gaps for future qualitative studies. Methods: This review was conducted from January to April 2024 using Arksey and O'Malley's framework and the PRISMA-ScR guideline. Four electronic databases (PubMed, CINAHL, DOSS, and EMBASE) were searched using keywords grouped under 2 themes: "immigrants" and "oral health service." Only peer-reviewed qualitative articles published in English within the last 10 years were selected. Results: Of 1349 original studies identified, 8 articles were included and reviewed. Three main themes emerged from newcomers' perspectives on their experience with oral health care in Canada and the United States: quality of care and professional behaviours, concerns about pediatric oral health care, and challenges in accessing care. Discussion and Conclusion: There is a need to improve cultural sensitivity and cross-cultural communication skills curricula in professional oral health education. Furthermore, making dental insurance more affordable, clarifying coverage for newcomers, and promoting collaboration between stakeholders and policymakers are essential to addressing the oral health concerns of immigrants and ASRs. Future research should prioritize primary interviews to gain more insights into newcomers' experiences when accessing oral health care.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".