Taking dentistry to the social level: Are Quebec dental professionals ready?
Bibliographic record
Abstract
Objectives: This thesis aimed to understand the perspectives of dentists towards the Montreal-Toulouse model, an approach that encompasses person-centeredness and social dentistry. More specifically, we wanted to know a) how dentists perceived the Montreal-Toulouse model; and b) how ready they were to adopt it.Methods: We conducted a qualitative descriptive study based on semi-structured interviews with a sample of dentists in the Province of Quebec, Canada. We employed a combination of maximum variation and snowball sampling strategies and recruited 14 information-rich dentists; these dentists were both working in private practice and as teachers in a dental faculty. The interviews were conducted and audio-recorded through Zoom and lasted approximately two hours. After transcribing the interviews verbatim, we performed a thematic analysis with a combination of inductive and deductive coding.Results: The participants explained they valued person-centred care and, as clinicians, tried to put the individual level of the Montreal-Toulouse model into practice. However, they expressed little interest in the social dentistry aspects of the model, such as providing domiciliary dental services. They acknowledged not knowing how to organize and conduct upstream interventions and were not comfortable with political activism. According to them, advocating for better health-related policies, while a noble act, “was not their job”. They also highlighted structural challenges that dentists faced for fostering biopsychosocial approaches.Conclusions: To promote the adoption of biopsychosocial approaches in dentistry, dental schools need to reject the biomedical, disease and sometimes dentist-oriented model of practice, which perpetuates a narrow definition of professionalism. We also encourage dentistry’s governing bodies to shift their focus from a market-based healthcare system to a socially oriented one
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".