The role of scoping reviews in guideline development
Bibliographic record
Abstract
Objectives Systematic reviews have long been seen as critical in the development of trustworthy guidelines. However, as newer synthesis methodologies such as scoping reviews become more common, there is a need to discuss the potential role of these methodologies within guideline development. This article aims to summarize and provide examples of the role of scoping reviews in guideline development. Study design and setting Drawing on the expertise of the JBI scoping review group and guideline developers, this discussion article summarizes five key roles of scoping reviews in guideline development. Results Guideline developers can consider using scoping reviews when they need to: 1) know what existing guidelines could be adopted, adapted or adoloped; 2) understand the breadth of evidence that exists on a particular issue and help with the development and prioritization of questions, or identify previous systematic reviews; 3) identify contextual factors and information relevant for a clinical practice recommendation; 4) identify potential strategies for implementation and monitoring and; 5) conduct evidence surveillance and living mapping approaches. Conclusions Scoping reviews conducted and reported according to best-practice guidelines and standards can be used in conjunction with systematic reviews to support the work of guideline developers usefully.
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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 | 0.205 | 0.780 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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; both teacher heads agree on what is shown here.
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".