Ontario Dentists' Estimation of Patient Interest in Anesthesia.
Bibliographic record
Abstract
Objective: To investigate Ontario dentists’ perceptions of patient interest in sedation and general anesthesia (GA) during treatment and patient fear and avoidance of dental treatment. Methods: Using the Royal College of Dental Surgeons of Ontario roster, we randomly selected 3001 practising Ontario dentists, from among those who listed an email address, to complete a 16-question survey by mail or online. Demographic information (e.g., gender, size and type of primary practice, and years of experience) was collected as well as dentist reports of patient interest in sedation/GA and level of fear regarding treatment. Analysis included sample t-tests to compare Ontario dentist responses with patient responses to a 2002 national survey. Results: 1076 dentists participated (37.9% response rate), comprised of 69.7% males, 84.4% general practitioners, 0.5–42 years of practice (mean 20.6 years), and 40.6% from cities with a population larger than 500,000. Dentists underestimated patients’ interest in sedation/GA, with dentists and patients reporting patients “Not interested” as 66.8% and 43.9%, respectively, and “Interested depending on cost,” 19.8% v. 42.3%. Dentists also underestimated patient interest in sedation/GA for specific dental procedures including scaling, fillings/crowns, root canal therapy and periodontal surgery (p < 0.01). Dentists overestimated patient fear levels (“Somewhat afraid,” 19.9% v. 9.8%; “Very afraid,” 10.6% v. 2.0%; “Terrified,” 6.0% v. 3.5%) and the proportion of patients avoiding dental care (13.3% v. 7.6%). Conclusion: Dentists underestimate patients’ preference for sedation/GA and overestimate their fear and avoidance of dental care. The significant disparities between the views of dentists and patients may affect the availability and provision of sedation and general anesthesia in Ontario dental practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".