Oral health guidelines in the primary care policies of five selected countries: An integrative review
Bibliographic record
Abstract
Background: Oral conditions remain a major health problem worldwide. Primary Health Care (PHC) has been recognized as a strategy to construct integrated health systems in order to produce the best health outcomes and reduce inequities through its attributes. Nevertheless, oral health integration in PHC remains unclear due to a lack of systematic knowledge. Aim: To summarize oral health guidelines focused on the comprehensiveness component of PHC in the health system and on the intersectoral component of health promotion and disease prevention actions in five selected countries. Methods: An integrative review of scientific and grey literature was led. Australia, Canada, New Zealand, United Kingdom and Brazil were selected. Content analysis was performed based on the comprehensiveness of care and health promotion and disease prevention categories. Results: Forty-one studies were selected to compose the review. Regarding the comprehensiveness of care, the horizontal dimension was more prominent, suggesting that oral care should be provided in cooperation with other health areas. Health promotion and disease prevention actions in intersectoral contexts are complex but seem to be effective. Programs for spreading access to fluorides and actions with the education sector are the most established ones. Conclusion: The integration of oral health in PHC policies is recommended in the guidelines of all countries, however, it stills represents a major challenge for the health care systems. These guidelines represent an important source to support decision-makers, policy-makers and stakeholders.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".