Tobacco use cessation services provided by dentists and dental hygienists in Manitoba: part 1. Influence of practitioner demographics and psychosocial factors.
Bibliographic record
Abstract
OBJECTIVE: Despite high rates of tobacco use, overwhelming evidence of detrimental effects on oral health, smokers" desire to stop using tobacco and the availability of efficacious brief intervention counselling (BIC) strategies, the delivery of cessation services by dental practitioners is, at best, inconsistent. The purpose of this part of our study was to assess BIC practice patterns among dentists and dental hygienists in Manitoba and to determine whether demographic or psychosocial factors influence BIC delivery. METHODS: A pre-piloted survey was mailed to all licensed dentists (547) and registered dental hygienists (566) in the province. RESULTS: In all, 514 oral health practitioners responded for a 46.2% response rate. Most oral health practitioners in Manitoba are not providing consistent BIC; however, 54.9% (279/508) of survey respondents advise smokers to quit. Women clinicians are more likely to ask, assess and assist patients and tend to advise against smoking more frequently than men; younger practitioners are more likely to ask and assess readiness to quit smoking than older practitioners; dental hygienists are more likely to provide assistance to quit than dentists. Assisting is the service least frequently provided by practitioners. The barriers to providing BIC are different for male and female practitioners and for dentists and dental hygienists; practitioners with more psychosocial barriers provide BIC less frequently than those reporting fewer barriers. Only 36.9% (188/510) of practitioners report feeling adequately prepared to assist smokers to quit.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".