Dental health in primary care; experience, education and attitudes of primary care physicians in Newfoundland and Labrador
Bibliographic record
Abstract
Introduction: Primary care physicians in Canada are often tasked with assessing dental issues despite reporting limited training in this area. Knowledge and attitudes around dental health in primary care in Newfoundland and Labrador (NL) have not previously been documented. Thus, we developed a survey for family physicians in NL with the goal of understanding the dental care education received by family physicians, comfort levels with providing dental care, and to identify potential gaps in training. Methods: Three semi-structured interviews with family physicians were used to guide the development of the survey, which was disseminated to all family physicians working in NL. Questions included demographic information, education in dental care, frequency, and confidence in providing dental care, and views on dental care within the scope of family medicine. The survey was circulated online through the provincial medical association and family practice networks. Results: A total of 63 family physicians responded to the survey. Of the respondents, 78% reported receiving less than 2 hours of dental care training throughout medical school, and 84% received less than 2 hours throughout residency. Notably, none of the physicians felt that their dental knowledge was above average when compared to their colleagues. Almost all family physicians felt that basic oral health should be within the scope of practice for family physicians. Conclusion: Our survey found that family physicians frequently see patients regarding a variety of dental complaints, yet they reported very little formal education in this area of practice throughout all stages of their training. The results of this study can be used to inform undergraduate and postgraduate medical education curriculum in Newfoundland and Labrador.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".