Laparoscopy in Low- and Middle-Income Countries: A Survey Study
Bibliographic record
Abstract
INTRODUCTION: An increasing shift towards non-communicable diseases and an existing high surgical burden of disease in low-middle-income countries (LMICs) has impelled the need for implementing laparoscopic surgery, a safe and cost-effective surgical service. However, despite countless benefits, laparoscopic surgery programs remain limited throughout LMICs, and limited understanding is known of healthcare professionals' views regarding the implementation of laparoscopic surgery in their local healthcare environments. Therefore, the purpose of this study is to better understand the perceived challenges and barriers to implementing long-term laparoscopic surgery programs from the perspective of healthcare professionals. METHODS: Upon receiving ethical approval from the McGill University Health Center (MUHC), a nine-question survey (concerning attributes required to establish a successful laparoscopic program in LMICs and to gain insight into what surgeons from LMICs believed were the necessary next steps) was pilot tested amongst faculty members, and subsequently disseminated to healthcare professionals practicing in LMICs. Explicit consent was obtained from the participants before answering the survey. Results: Thirty-four participants representing a total of 35 countries participated in the survey with the majority having received laparoscopic surgery training. Overall, participant responses were characterized by two major themes. Highlighted in the first theme, Laparoscopic Experience and Training Curriculum, were responses concerning current laparoscopic training and education, improved career opportunities provided by laparoscopic training, and a particular existing potential to incorporate laparoscopic surgery into the current surgical curriculum at various levels of training. Emphasized in the second theme, Challenges and Next Steps, were responses concerning barriers to the implementation of laparoscopic surgery, current institutional capabilities, and the need for improving mentorship through existing surgical societies such as the College of Surgeons of East, Central, and Southern Africa (COSECSA), West African College of Surgeons (WACS), and The Pan-African Academy of Christian Surgeons (PAACS). CONCLUSIONS: A buy-in from the government, hospitals, staff, and industry is crucial for the long-term implementation of laparoscopic surgery in LMICs, which can only be accomplished through increased advocacy and the dissemination of the benefits of minimally invasive surgery both economically and socially.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".