Technical quality of root canal treatment performed by undergraduate students using hand instrumentation: a meta‐analysis
Bibliographic record
Abstract
The technical quality of root canal treatment (RCT) may impact on the outcome. The quality of education received during undergraduate school may be linked to the quality of treatment provided in general dental practice. In this context, the aim of this systematic review was to answer the following focused questions: (i) What is the frequency of acceptable technical quality of root fillings, assessed radiographically, performed by undergraduate students? (ii) What are the most common errors assessed radiographically and reported in these treatments? For this purpose, articles that evaluated the quality of root fillings performed by undergraduate students were selected. Data were collected based on predetermined criteria. The key features from the included studies were extracted. GRADE-tool assessed the quality of the evidence. MAStARI evaluated the methodological quality, and a meta-analysis on all studies was conducted. At the end of the screening, 24 articles were identified. Overall frequency of acceptable technical quality of root fillings was 48%. From this total, 52% related to anterior teeth, 49% to premolars and 26% to molars. The main procedural errors reported were ledge formation, furcation perforation, apical transportation and apical perforation. The heterogeneity amongst the studies was high (84-99%). Five studies had a high risk of bias, eight had a moderate risk, and 11 had low risk. The overall quality of evidence identified was very low. The conclusion was that technical quality of root fillings performed by undergraduate students is low, which may reveal that endodontic education has limited achievement at undergraduate level. A plan to improve the quality of root fillings, and by extrapolation the overall quality of root canal treatment, should be discussed by the staff responsible for endodontic education and training.
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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 | 0.022 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.050 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".