The Landscape of Predoctoral Endodontic Education in the United States and Canada: Results of a Survey
Bibliographic record
Abstract
Few recent surveys have examined the contemporary landscape of predoctoral endodontic education in the United States and Canada, but anecdotal reports suggest that current dental students have difficulty obtaining adequate clinical endodontic experiences. The aims of this study were to quantify the clinical endodontic experiences of current U.S. and Canadian dental students, to explore the issues surrounding their clinical endodontic competence, and to ask more broadly if current graduating dentists are competent to perform endodontic procedures. In August 2014, a hyperlink to a web-based survey with 27 questions was emailed to the 67 predoctoral endodontic directors of U.S. and Canadian dental schools using a list provided by the American Association of Endodontists. Out of these 67 possible participants, 40 responded, for a response rate of 60%. The findings were varied. The average 2014 graduate completed 5.9 (± 2.4) root canal treatments on live patients, and 69% of the respondents voiced concern regarding a shortage of patient experiences. A majority (59%) of the respondents reported thinking that the supply of endodontic patients has decreased and that students have an inadequate supply of endodontic patients. This study found that a clear majority of predoctoral endodontics directors perceived a shortage of patient experiences for their students although, in reality, the number of completed clinical cases appeared to be unchanged since 1975. In addition, 36% of the respondents reported feeling that their 2014 graduates were not competent to perform molar endodontic treatment in their practices.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".