ORAL HEALTH STATUS OF IMMIGRANT AND REFUGEE CHILDREN IN NORTH AMERICA: A SCOPING REVIEW.
Bibliographic record
Abstract
OBJECTIVES: The aim of this scoping review was to assess the oral health status of the children of refugees and immigrants ("newcomers"); the barriers to appropriate oral health care and use of dental services; and clinical and behavioural interventions for this population in North America. METHODS: Explicit inclusion and exclusion criteria were used in searching electronic databases to identify North American studies between 2007 and 2014 that reported oral health status, behaviours and environment of children of newcomers. Additional studies from 1995-2008 were found in a recently published review. Pertinent data from all selected studies were summarized. RESULTS: Overall, 32 relevant North American studies were identified. In general, children of newcomers exhibit poorer oral health compared with their non-newcomer counterparts. This population faces language, cultural and financial barriers that, consequently, limit their access to and use of dental services. Intervention programs, such as educational courses and counseling, targeting newcomer parents or their children are helpful in improving the oral health status of this population. CONCLUSIONS: Children of newcomers are suffering from poor oral health and face several barriers to use of dental care services. The disparity in dental caries between children of newcomers and their counterparts can be reduced by improving their parents' literacy in the official language(s) and educating parents regarding good oral health practices. An appropriate oral health policy remains crucial for marginalized populations in general and newcomer children in particular.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".