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Record W3007153854 · doi:10.1093/inthealth/ihz109

A qualitative narrative review of protocols for women’s health on short-term medical missions in Latin America and the Caribbean

2019· article· en· W3007153854 on OpenAlexaff
Christopher Dainton, Charlene H. Chu

Bibliographic record

VenueInternational Health · 2019
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of TorontoMcMaster UniversityGrand River Hospital
Fundersnot available
KeywordsLatin AmericansMedicineConcordanceFamily medicineQualitative researchAlternative medicineNursingPolitical sciencePathologySocial science

Abstract

fetched live from OpenAlex

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 This qualitative study aimed to describe areas of agreement between unpublished women's health protocols from different North American STMM organizations and assess their concordance with published WHO guidelines.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.

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 imitation

Not 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.

metaresearch head score (Codex)0.136
metaresearch head score (Gemma)0.193
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.136
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1360.193
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.009
Science and technology studies0.0090.008
Scholarly communication0.0060.008
Open science0.0040.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.065
GPT teacher head0.508
Teacher spread0.443 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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