A qualitative narrative review of protocols for women’s health on short-term medical missions in Latin America and the Caribbean
Bibliographic record
Abstract
BACKGROUND: Women's health conditions are commonly encountered on short-term medical missions (STMMs) in Latin America and the Caribbean. There have been no previous attempts to describe women's health protocols used by volunteer clinicians. This qualitative study aimed to describe areas of agreement between unpublished women's health protocols from different North American STMM organizations and assess their concordance with published WHO guidelines. METHODS: A systematic web search was used to identify North American STMM sending organizations. Clinical protocols were downloaded from their websites and organizations were contacted to request protocols that were not published online. The protocols obtained were summarized, analysed thematically and compared to existing WHO guidelines. RESULTS: Of 225 organizations contacted, 112 (49.8%) responded and 31 of these (27.7%) had clinical protocols, of which 20 were obtained and analysed. Nine (45%) discussed sexually transmitted infections, six (30%) discussed pelvic inflammatory disease, two (10%) discussed prenatal care and two (10%) discussed menstrual disorders. None were the product of systematic literature searches and most were not referenced. CONCLUSIONS: To avoid ineffective treatment and related harms to women, volunteer clinicians would benefit from the adaptation and distribution of guidelines for STMMs that are based on existing WHO guidance and acceptable to clinicians, patients and organizations.
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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 | 0.136 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".