Barriers to and facilitators of living guidelines use in low-income and middle-income countries: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Living guidelines provide reliable, ongoing evidence surveillance and regularly updated recommendations for healthcare decision-making. As a relatively new concept, most of the initial application of living approaches has been undertaken in high-income countries. However, in this scoping review, we looked at what is currently known about how living guidelines were developed, used and applied in low-income and middle-income countries. METHODS: Searches for published literature were conducted in Medline, Global Health, Cochrane Library and Embase. Grey literature was identified using Google Scholar and the WHO website. In addition, the reference lists of included studies were checked for missing studies. Studies were included if they described or reflected on the development, application or utility of living guideline approaches for low-income and middle-income countries. RESULTS: After a full-text review, 21 studies were included in the review, reporting on the development and application of living recommendations in low-income and middle-income countries. Most studies reported living guideline activities conducted by the WHO (15, 71.4%), followed by China (4, 19%), Chile (1, 4.8%) and Lebanon (1, 4.8%). All studies based on WHO reports relate to living COVID-19 management guidelines. CONCLUSIONS: Most of the studies in this review were WHO-reported studies focusing solely on COVID-19 disease treatment living guidelines. However, there was no clear explanation of how living guidelines were used nor information on the prospects for and obstacles to the implementation of living guidelines in low-income and middle-income countries.
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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 | 0.035 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".