Gender disparity and the impact of COVID-19 on surgical training in New Zealand ophthalmology
Bibliographic record
Abstract
AIM: To evaluate the impact of the COVID-19 pandemic on New Zealand ophthalmology surgical training, focusing on surgical volume, case-mix, trainee involvement and gender disparities. METHODS: Analysis of logbook data for New Zealand based trainees of the Royal Australian and New Zealand College of Ophthalmologists (RANZCO) from 1 January 2017 to 31 December 2022 was conducted comparing trainee-involved and trainee-performed case volumes between pre-pandemic (2017-2019) and pandemic (2020-2022) years, normalised by full-time equivalents (FTE). RESULTS: Analysis of 41,370 trainee-involved surgeries revealed that while the total number of trainee-involved procedures remained stable during the pandemic, trainee-performed surgeries decreased significantly by 11.8%. This was driven by a significant gender disparity (p=0.045), with a 24.9% decline for female trainees, concentrated among those in urban centres, while male trainee numbers remained stable (+0.74%). Provincial trainees performed twice as many surgeries as urban counterparts. A significant case-mix shift also occurred, with greater glaucoma (+27.6%) and fewer oculoplastic (-20.8%) surgeries. CONCLUSION: The pandemic was associated with a significant gender disparity in surgical training, driven by a reduction in procedures performed by female trainees predominantly in urban centres. The findings underscore the need to ensure equitable access to surgical training.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".