Children’s Oral Health Initiative: workers’ perspectives on its impact in First Nations communities
Bibliographic record
Abstract
INTRODUCTION: Since 2004, the Children's Oral Health Initiative (COHI) has been working in many First Nations and Inuit communities in Canada to address oral health disparities, specifically early childhood caries (ECC). The COHI community-based approach improves early childhood oral health (ECOH) by balancing prevention with minimally invasive dentistry. The goal is to reduce the burden of oral disease, mainly by minimizing the need for surgery. We investigated program success in First Nations communities in the province of Manitoba, from the perspective of COHI staff. METHODS: First Nations community-based dental therapists and dental worker aides participated in three focus groups and an in-depth semistructured interview. The collected data were thematically analyzed. RESULTS: Data from 22 participants yielded converging and practitioner-specific themes. Participants reported that dental therapists and dental worker aides provide access to basic oral care in their communities including oral health assessments, teeth cleaning, fluoride varnish applications and sealants. The participants agreed that education, information sharing and culturally appropriate parental engagement are crucial for continuous support and capacity building in the community programs. Low enrolment, difficulty accessing homes and getting consent, limited human resources as well as lack of educational opportunities for dental worker aides were identified challenges. CONCLUSION: Overall, the participants reported that the COHI program positively contributes to ECOH in First Nations communities. However, increased community-based training for dental workers, community awareness about the program, and engagement of parents to facilitate culturally appropriate programming and consent processes are critical to improving program outcomes.
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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 | 0.022 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.009 |
| 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".