A Silver Fluoride Intervention to Improve Oral Health Trajectories of Young Indigenous Australians: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Indigenous Australian children and adolescents experience profound levels of preventable dental disease. The application of silver fluoride (AgF) to active dental caries is a noninvasive alternative to traditional dental treatment approaches. There is particular utility among Indigenous children and young people with dental fear, who may not have access to timely or culturally safe dental service provisions. OBJECTIVE: The aims of this study are to: (1) assess levels of active dental caries among Indigenous children and young people in 6 Australian states and territories; (2) determine if an AgF intervention reduces levels of active disease over 12-24 months; (3) measure the impact of improved oral health on social and emotional well-being (SEWB) and oral health-related quality of life; and (4) calculate the cost-effectiveness of implementing such an initiative. METHODS: The study will use a 2-arm, parallel cluster randomized controlled trial design. Approximately 1140 Indigenous children and youth aged between 2 and 18 years will be recruited. Each state or territory will have 2 clusters. The intervention group will receive the AgF intervention at the start of the study, with the delayed intervention group receiving the AgF intervention 12 months after study commencement. The primary outcome will be the arrest of active carious lesions, with arrested caries defined as nonpenetration by a dental probe. Secondary outcomes will include SEWB, oral health-related quality of life, and dental anxiety, with covariates including dental behaviors (brushing and dental visits). Effectiveness measures for the economic evaluation will include the number of children and young people managed in primary oral health care without the need for specialist referral, changes in SEWB, the numbers and types of treatments provided, and caries increments. RESULTS: Participant recruitment will commence in May 2023. The first results are expected to be submitted for publication 1 year after a 24-month follow-up. CONCLUSIONS: Our findings have the potential to change the way in which active dental disease among Indigenous children and young people can be managed through the inclusion of specifically tailored AgF applications to improve dental health and SEWB delivered by Indigenous health care workers. Desired impacts include cost savings on expensive dental treatments; improved SEWB, nutrition, social, and learning outcomes; and improved quality of life for both children and young people and their caregivers and the broader Indigenous community. The AgF application could be easily implemented into the training program of Indigenous health workers and yield critical information in the management armamentarium of health and well-being recommendations for Australia's First Peoples. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48558.
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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 | 0.024 | 0.022 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.060 | 0.007 |
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".