COVID-19 Restrictions Presented Opportunities and Challenges for Plastic Surgery Residents
Bibliographic record
Abstract
Background: Restrictions placed during the COVID-19 pandemic to prevent viral spread led to substantial changes in surgical resident education. The aim of this study was to assess the positive and negative impact of COVID-19 on plastic surgery education and training and provide recommendations for continued competency. Methods: A cross-sectional online survey of plastic surgery residents across Canada was used to evaluate the impact of COVID-19 on clinical exposure, experience with virtual education, and long-term impact of COVID-19 on surgical training. Results: This study included 61 plastic surgery residents (40% participation rate). Common educational modalities used during COVID-19 included online seminars (95%) and workshops (58%). Teaching sessions were effective if structured around patient cases (72%), recorded (66%), and limited to 1 hour (64%). There were mixed reactions towards online education sessions; residents reported feeling grateful (54%), motivated (38%), enthusiastic (28%), overwhelmed (41%), pressured to participate (23%), and anxious (13%). There were significantly less residents who felt that their clinical exposure was sufficient during (21%) versus before (72%) pandemic restrictions ( P < .001). Overall, 87% of residents felt that the pandemic had a negative impact on their training, surgical skill development, fellowship plans, and job prospects. Conclusions: During the initial wave of COVID-19, residents faced altered educational opportunities, which elicited positive and negative emotions with concern regarding surgical skill development and impact on future career plans. Characterizing early educational impact on residency training to identify opportunities for change is worthwhile as the overall effect of the pandemic is ongoing and remains uncertain.
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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 | 0.001 | 0.174 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".