Delivery of surgical care in Samoa: perspectives on capacity, barriers and opportunities by local providers
Bibliographic record
Abstract
BACKGROUND: The Pacific Island nation of Samoa faces a number of challenges in delivering surgical care. Our group aimed to identify the barriers and opportunities to improving the delivery of safe, affordable, timely surgical care in Samoa. METHODS: A mixed-methods approach was undertaken. The quantitative analysis used a modified version of the World Health Organization Emergency and Essential Surgical Checklist while the qualitative methodology used semi-structured interviews. Respondents were asked to share their views on the capacity, quality, accessibility and future directions of surgery in Samoa. Interviews were transcribed and analysed using open and axial coding techniques. RESULTS: Stakeholders had a positive outlook on the delivery of surgical care, but it was suggested that existing services were not meeting needs. Respondents cited limited access to equipment and resources, compounded by insufficient organizational and logistical infrastructure. Shortage of medical staff and retention was identified as a key issue. Shortcomings in primary care and poor health literacy were seen as significant barriers to accessing care. CONCLUSION: Documenting locally identified barriers and solutions to surgical care in Samoa is an important first step towards the development of formal strategies for improving surgical services nationally.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".