Clinical guidelines for Western clinicians engaged in primary care medical service trips in <scp>L</scp>atin <scp>A</scp>merica and the <scp>C</scp>aribbean: an integrative literature review
Bibliographic record
Abstract
OBJECTIVE: Participation in primary care-focused medical service trips (MSTs) by North American providers is increasingly common, with many of these being conducted in Latin America. The literature has yet to comprehensively explore the nature of MST practice, including the use of evidence-based clinical guidelines. This integrative review presents an analysis of guidelines employed in MSTs in Latin America. METHODS: MEDLINE and LILACs were searched using the terms 'medical brigades', 'Latin America', 'primary health care' and related terms. The search was limited to articles published between 2000 and 2015 in any language. Qualitative or quantitative articles were subsequently included if they described management protocols in the context of patient care on an MST occurring in Latin America. Additional publications were identified by searching the citations of articles reviewed in full. Themes were extracted to an Excel file, and objective instruments were used to evaluate article quality (Mixed Methods Assessment Tool) and the quality of guidelines (Appraisal of Guidelines for Research & Evaluation II). RESULTS: Of 391 abstracts screened, eight met inclusion criteria. All described MSTs operating in rural settings in Central America. Five were qualitative descriptive, including two travel reports, an ethics thesis paper, and a description of a dermatologic MST. Four described subjective clinician experiences while describing non-evidence-based treatment suggestions or practices. Only one described evidence-supported primary care interventions. Three studies were quantitative descriptive, including two epidemiological articles, one of which used case definitions for select diagnoses. One described the application of American Family Physician guidelines to the description of UTI prevalence on a MST. Article scores in MMAT quality domains were variable, and only one article achieved a positive overall AGREE II score for guideline quality. CONCLUSIONS: Existing literature demonstrates minimal development or use of clinical guidelines on MSTs in Latin America. Future work must focus on the development, implementation, and evaluation of culturally sensitive, evidence-based guidelines for the management of patients receiving care from MSTs.
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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 | 0.020 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".