A scoping review of researchers’ involvement in health policy dialogue in Africa
Bibliographic record
Abstract
BACKGROUND: Improving evidence-informed policy dialogue to support the development and implementation of national health policies is vital, but there is limited evidence on researchers' roles in policy dialogue processes in Africa. The objective of this study is to examine researchers' involvement in health policy dialogue in Africa. METHODS: The database search of this scoping review was conducted from inception to January 24, 2021, by an expert searcher/librarian to determine the extent of evidence, barriers, and facilitators of researchers' involvement in health policy dialogues in Africa. PROSPERO, Wiley Cochrane Library, OVID Medline, OVID EMBASE, OVID PsycINFO, OVID Global Health, EBSCO CINAHL, BASE (Bielefeld Academic Search Engine), and Google/Google Scholar were searched using key words representing the concepts "policy dialogue", "health", and "Africa". No limits were applied. A narrative summary of results was presented. RESULTS: There were 26 eligible studies representing 21 African countries. Significant discrepancies in researchers' involvement existed across countries. In 62% of the countries, there was suboptimal involvement of researchers in policy dialogues due to no or partial participation in policy dialogues. Major barriers included limited funding, lack of evidence in the public health field of interest, and skepticism of policymakers. The presence of an interface for exchange, demand for scientific evidence, and donors' funding were the most reported facilitators. CONCLUSIONS: To improve the uptake of evidence in health policy-making processes, an environment of trust and communication between policymakers and researchers must be established. Policymakers need to demonstrate that they value research, by providing adequate funding, promoting knowledge translation activities, and supporting personal and professional development opportunities for researchers.
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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 | 0.123 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".