Brazilian immigrants’ oral health literacy and participation in oral health care in Canada
Bibliographic record
Abstract
BACKGROUND: Inadequate functional health literacy is a common problem in immigrant populations. The aim of this study was to investigate the association between oral (dental) health literacy (OHL) and participation in oral health care among Brazilian immigrants in Toronto, Ontario, Canada. METHODS: The study used a cross-sectional design and a convenience sample of 101 Brazilian immigrants selected through the snowball sampling technique. Data were analyzed using descriptive statistics and logistic regression modeling. RESULTS: Most of the sample had adequate OHL (83.1 %). Inadequate/marginal OHL was associated with not visiting a dentist in the preceding year (OR = 3.61; p = 0.04), not having a dentist as the primary source of dental information (OR = 5.55; p < 0.01), and not participating in shared dental treatment decision making (OR = 1.06; p = 0.05; OHL as a continuous variable) in multivariate logistic regressions controlling for covariates. A low average annual family income was associated with two indicators of poor participation in oral health care (i.e., not having visited a dentist in the previous year, and not having a dentist as regular source of dental information). CONCLUSION: Limited OHL was linked to lower participation in the oral health care system and with barriers to using dental services among a sample of Brazilian immigrants. More effective knowledge transfer will be required to help specific groups of immigrants to better navigate the Canadian dental care system.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".