Use of and Access to Deep Sedation and General Anesthesia for Dental Patients: A Survey of Ontario Dentists.
Bibliographic record
Abstract
OBJECTIVE: This study aims to assess barriers to the use of deep sedation/general anesthesia (DS/GA) identified by dentists in Ontario. METHODS: An email invitation to a web-based survey was distributed to all licensed dentists and specialists who have provided an email address to the provincial regulator (n = 5507). Descriptive and regression analyses were performed to explore practice and demographic factors associated with the use of DS/GA. RESULTS: The response rate was 18.3%. A quarter (24.8%) of respondents reported inadequate access to DS/GA. Access was poorest in rural communities and greatest in the Greater Toronto Area (GTA). Overall, 74.5% of dentists indicated that they had used DS/GA in the past 12 months. Use was defined as having provided the service or referred a patient in the past 12 months. Non-use was most likely among general dentists, part-time dentists, dentists > 64 years and dentists in urban locations. Wait times and travel distances were reported as longer for medically complex patients. The most common reasons for non-use of DS/GA were a lack of perceived demand and additional costs to patients. For DS/GA users, the greatest barrier was additional costs to patients. CONCLUSION: Access to DS/GA in Ontario is not uniform; it remains a challenge in rural communities and regions outside the GTA, especially in the north. Use is lowest among general dentists and urban dentists despite adequate access, with dentists' perception of need for DS/GA and cost to the patient acting as major barriers. Education for dentists and better insurance coverage for patients may improve access for these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".