Canadian immigrants' oral health and oral health care providers' cultural competence capacity.
Bibliographic record
Abstract
Background: Immigrants to Canada count among the socially disadvantaged groups experiencing higher rates of oral disease. Culturally competent oral health care providers (OHCPs) stand to be allies for immigrant oral health. The literature reveals limited knowledge of practising OHCPs' cultural competency, and little synthesis of the topic has been completed. A scoping review is warranted to identify and map current knowledge of OHCPs' understanding of culturally competent care along with barriers and facilitators to developing capacity. Methods: This study was conducted between December 2022 and April 2023 using Arksey and O'Malley's 5-step framework and PRISMA-ScR checklist. Four databases were searched using keywords related to 4 themes: population, provider, oral health, and cultural competence. Peer-reviewed articles published in English in the last 10 years were included. Results: Search results yielded 74 articles. Title and abstract review was completed and an author-developed critical appraisal tool was applied. Forty-six (46) articles were subject to full-text review and 14 met eligibility criteria: 7 qualitative and 7 quantitative. Six barriers and six facilitators at individual and systemic levels were identified, affecting oral care for immigrants and providers' ability to work cross-culturally. Discussion: Lack of cultural or linguistically appropriate resources, guidance, and structural supports were identified as contributing to low utilization of services and to lack of familiarity between providers and immigrants. Conclusion: OHCPs' cultural competency development is required to improve oral health care access and outcomes for diverse populations. Further research is warranted to identify factors impeding OHCPs' capacity to provide culturally sensitive care. Intentional policy development and knowledge mobilization are needed.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".