The impact of culture on new Asian immigrants' access to oral health care: a scoping review.
Bibliographic record
Abstract
Background: Immigration has accounted for three-quarters of Canada's population growth since 2016, more than half of which has been from Asian countries. Newcomers from Asia have been reported to experience oral health disparities. The objective of this scoping review was to examine the literature discussing how culture affects access to oral health care for new immigrants from Asia and to identify knowledge gaps. Methods: The review was conducted from December 2021 to April 2022 following the Arskey and O'Malley approach and PRISMA-ScR guideline. Five databases were searched using the search parameter "Asian+ AND Immigrant+ AND oral care+". Only peer-reviewed articles published in English between 2011 and 2021 were included. Results: The search strategy yielded 736 articles. Duplicates were removed, titles and abstracts were reviewed, and the full text of 69 articles examined, leaving 26 articles that met eligibility criteria: 18 quantitative studies, 4 qualitative studies, and 4 reviews. Discussion: Four themes were identified: language barriers, oral health care access and service utilization, oral health beliefs and behaviour, and immigrant children's oral health. Most new immigrants from Asia have limited English proficiency, are of low socioeconomic status, and have difficulty developing trusting relationships with care providers. Immigrant children's oral health is impacted by their parents' beliefs. Conclusion: More research is needed on cultural barriers to and facilitators of access to oral health care for newcomers from Asia to Canada to aid in the development and implementation of policies and to inform practice and curriculum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".