Global survey of endodontic practice and adoption of newer technologies
Bibliographic record
Abstract
AIM: To investigate current endodontic practices, adoption of technologies and continuing education attendance within specialist endodontic practice globally and to identify geographic trends. METHODOLOGY: A web-based survey of endodontic association members in Australia, Britain, Canada, Italy, New Zealand and the USA on routine treatment preferences, armamentarium and education attendance was conducted. Chi-squared, independent sample t-tests, Cochran's Q test and McNemar's test were performed. RESULTS: The survey was completed by 543 endodontists or endodontic post-graduate students. Almost all respondents used the dental operating microscope (DOM, 91.3%), engine-driven nickel-titanium instruments (NiTi, 97.6%), electronic apex locators (EAL, 93.0%), cone-beam computed tomography (CBCT, 91.2%) and calcium silicate-based materials (CSBMs, 93.7%). Dental dam was always used by 99.1%. Over half used irrigation adjuncts (81.8%), warm vertical compaction (74.6%) and heat-treated NiTi (60.2%). Geographic comparison between AP (Asia-Pacific, n = 78), AM (Americas, n = 402) and EM (Europe and Middle East, n = 63) was performed. AM and EM preferred single-visit treatment more (p < .001) and used higher sodium hypochlorite concentrations than AP. AM had more access to CBCT in the workplace (86.6%) than AP (65.4%, p < .001) and used CBCT for routine preoperative assessment (39.6%) more than EM (7.3%, p < .001). Almost all of EM used irrigation adjuncts (95.2%), more than AM (78.1%, p = .001). AP used steroid/antibiotic medicaments most (p < .001) and had the highest attendance at continuing education programmes. CONCLUSION: Several endodontic-specific armamentaria have reached almost complete adoption within global specialist endodontic practice, whilst the continued uptake of newer technologies should be followed over time. Some practising philosophies varied significantly across different geographic regions.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.002 | 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".