Need and Demand for Sedation or General Anesthesia in Dentistry: A National Survey of the Canadian Population
Bibliographic record
Abstract
The aim of this study was to assess the need and demand for sedation or general anesthesia (GA) for dentistry in the Canadian adult population. A national telephone survey of 1101 Canadians found that 9.8% were somewhat afraid of dental treatment, with another 5.5% having a high level of fear. Fear or anxiety was the reason why 7.6% had ever missed, cancelled, or avoided a dental appointment. Of those with high fear, 49.2% had avoided a dental appointment at some point because of fear or anxiety as opposed to only 5.2% from the no or low fear group. Regarding demand, 12.4% were definitely interested in sedation or GA for their dentistry and 42.3% were interested depending on cost. Of those with high fear, 31.1% were definitely interested, with 54.1% interested depending on cost. In a hypothetical situation where endodontics was required because of a severe toothache, 12.7% reported high fear. This decreased to 5.4% if sedation or GA were available. For this procedure, 20.4% were definitely interested in sedation or GA, and another 46.1% were interested depending on cost. The prevalence of, and preference for, sedation or GA was assessed for specific dental procedures. The proportion of the population with a preference for sedation or GA was 7.2% for cleaning, 18% for fillings or crowns, 54.7% for endodontics, 68.2% for periodontal surgery, and 46.5% for extraction. For each procedure, the proportion expressing a preference for sedation or GA was significantly greater than the proportion having received treatment with sedation or GA (P < 0.001). In conclusion, this study demonstrates that there is significant need and demand for sedation and GA in the Canadian adult population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".