Confidence Among Graduating Dental Students on Their Competencies During the COVID‐19 Pandemic
Bibliographic record
Abstract
OBJECTIVE: To assess the confidence of graduating dental students affected by the COVID-19 pandemic's clinic closure and restrictions and again after their first year of practice. METHODS: Previously validated online surveys were sent to the University of Toronto classes of 2021 (n = 118, "21S") and 2022 (n = 120, "22S") at graduation and after 1 year of practice as dentists ("21D," "22D"), asking about their confidence in performing competencies of the Association of Canadian Faculties of Dentistry. Analyses included demographics, mean values of Likert scale responses, independent samples t-tests for comparison between groups, one-way ANOVA for comparison between multiple groups, followed by post hoc pairwise comparison using Tukey's tests using statistical significance of p < 0.05. RESULTS: Response rates were 43% (21S), 44% (22S), 30.5% (21D), and 17.5% (22D). Students (21S) were more confident than 22S (x̄21S = 3.67, x̄22S = 3.25, p < 0.01). Dentists were statistically more confident "practicing general dentistry" than when they were students (x̄22D = 3.71, x̄22S = 3.25, p < 0.05). There were no statistical differences between dentist groups "practicing general dentistry" (x̄21D = 3.83, x̄22D = 3.71) in this study. Within students (22S), males were more confident than females for "prosthodontic competencies" (p < 0.05) and "practicing general dentistry" (p < 0.01), and as dentists, they were more confident in performing surgeries (p < 0.05). For prosthodontics, students (22S) were less confident than 2021 (21S) (p < 0.05); however, after a year in practice, there were no significant differences between groups. CONCLUSION: These graduates demonstrated a lower confidence in the competencies expected of a new Canadian dentist and after 1 year, there were no differences in confidence in "practicing general dentistry" between groups.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".