Knowledge, attitude, willingness and readiness of primary health care providers to provide oral health services to children in Niagara, Ontario: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Most children are exposed to medical, but not dental, care at an early age, making primary health care providers an important player in the reduction of tooth decay. The goal of this research was to understand the feasibility of using primary health care providers in promoting oral health by assessing their knowledge, attitude, willingness and readiness in this regard. METHODS: Using the Dillman method, a mail-in cross-sectional survey was conducted among all family physicians and pediatricians in the Niagara region of Ontario who have primary contact with children. A descriptive analysis was performed. RESULTS: Close to 70% (181/265) of providers responded. More than 90% know that untreated tooth decay could affect the general health of a child. More than 80% examine the oral cavity for more than 50% of their child patients. However, more than 50% are not aware that white spots or lines on the tooth surface are the first signs of tooth decay. Lack of clinical time was the top reason for not performing oral disease prevention measures. INTERPRETATION: Overall, survey responses show a positive attitude and willingness to engage in the oral health of children. To capitalize on this, there is a need to identify mechanisms of providing preventive oral health care services by primary health care providers; including improving their knowledge of oral health and addressing other potential barriers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".