Review of the evidence for oral health promotion effectiveness
Bibliographic record
Abstract
Dental caries, periodontal diseases, tooth loss and oral cancers have significant burden of disease effects * , quality of life and cost implications for the Australian community. Oral health promotion is a key approach to addressing these conditions endorsed as part of the National Oral Health Plan. Understanding the evidence for effectiveness of oral health promotion is integral to strategic planning for both oral and general health settings. Objective: The objective of this article is to report the key findings of a systematic review of the evidence for oral health promotion commissioned by the Victorian Department of Human Services in 2006. Methods: Evidence was collected and evaluated using a combined approach incorporating the Cochrane Public Health and Health Promotion Field Handbook and the Health Gains Notation in order to a develop a synthesis approach to reporting, framed around the Ottawa Charter. Findings: Findings included evidence supporting the continued fluoridation of water supplies, interventions aimed at early childhood and aged care settings, smoking cessation and capacity building with non-oral health care providers. Emerging evidence supporting multi-strategy community based approaches is also reported along with gaps in the evidence. General Conclusions: The authors conclude that, while there is good support for the incorporation of oral health into general health promotion, it will be important to monitor the outcomes in oral health terms.
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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 | 0.019 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".