The Effectiveness and Challenges of E-learning in Surgical Training in Low- and Middle-Income Countries: A Systematic Review
Bibliographic record
Abstract
E-learning encompasses the use of electronic media, online tools, and technologies in education and has been shown to be generally effective and satisfying for students, compared to traditional methods such as didactic lectures. Within surgical education, there is growing demand for e-learning platforms in low- and middle-income countries (LMICs). A systematic review was conducted to evaluate the effectiveness and challenges of e-learning for surgical trainees in LMICs. Out of 87 studies, five studies met the inclusion criteria and reported either neutral or positive improvements in cognitive and procedural skills, compared to baselines or controls for surgical trainees in LMICs. Using a qualitative synthesis approach, the researchers identified common challenges and barriers, such as low bandwidth, limited connectivity, and poor surgical details, which led to poor knowledge synthesis. This suggests that more emphasis needs to be placed on developing a strong online foundation that could be easily accessed and is user-friendly and intuitive, especially in LMICs. However, the research was limited by the lack of literature surrounding surgical e-learning interventions in LMICs and more research is required in this area.
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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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".