Smoking cessation services provided by dental professionals in a rural Ontario health unit.
Bibliographic record
Abstract
PURPOSE: This study was undertaken to determine what smoking cessation services dental professionals in Ontario's Wellington-Dufferin-Guelph Health Unit (WDGHU) provide before disseminating a smoking cessation information package. METHODS: Data were collected with 540 self-administered questionnaires mailed to 60 local dental offices. Replies were requested from all dentists, dental hygienists, dental assistants and other dental staff working in each dental office. RESULTS: Completed responses were obtained from 126 dental personnel in 28 (47%) of the 60 dental offices surveyed. The proportion of dental offices, dentists and hygienists providing cessation services to most patients was as follows: asking patients about tobacco-use status, 46%, 31% and 32%; advising tobacco users to quit, 46%, 32% and 29%; assessing tobacco users' interest in quitting, 46%, 25% and 19%; and assisting interested patients to quit, 25%, 6% and 13%, respectively. CONCLUSION: This survey indicates that most dental professionals in the WDGHU do not provide proven smoking cessation services. An opportunity exists to increase the proportion of dental professionals providing proven smoking cessation interventions as part of routine patient services.
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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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".