Survey of ophthalmologists-in-training in Eastern, Central and Southern Africa: A regional focus on ophthalmic surgical education
Bibliographic record
Abstract
Background: There are 2.7 ophthalmologists per million population in sub-Saharan Africa, and a need to train more. We sought to analyse current surgical training practice and experience of ophthalmologists to inform planning of training in Eastern, Central and Southern Africa. Methods: This was a cross-sectional survey. Potential participants included all current trainee and recent graduate ophthalmologists in the Eastern, Central and Southern African region. A link to a web-based questionnaire was sent to all heads of eye departments and training programme directors of ophthalmology training institutions in Eastern, Central and Southern Africa, who forwarded to all their trainees and recent graduates. Main outcome measures were quantitative and qualitative survey responses. Results: Responses were obtained from 124 (52%) trainees in the region. Overall level of satisfaction with ophthalmology training programmes was rated as ‘somewhat satisfied’ or ‘very satisfied’ by 72%. Most frequent intended career choice was general ophthalmology, with >75% planning to work in their home country post-graduation. A quarter stated a desire to mainly work in private practice. Only 28% of junior (first and second year) trainees felt surgically confident in manual small incision cataract surgery (SICS); this increased to 84% among senior trainees and recent graduates. The median number of cataract surgeries performed by junior trainees was zero. 57% of senior trainees were confident in performing an anterior vitrectomy. Only 29% of senior trainees and 64% of recent graduates were confident in trabeculectomy. The mean number of cataract procedures performed by senior trainees was 84 SICS (median 58) and 101 phacoemulsification (median 0). Conclusion: Satisfaction with post-graduate ophthalmology training in the region was fair. Most junior trainees experience limited cataract surgical training in the first two years. Focused efforts on certain aspects of surgical education should be made to ensure adequate opportunities are offered earlier on in ophthalmology training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".