Evidence synthesis to policy: development and implementation of an impact-oriented approach from the Eastern Mediterranean Region
Bibliographic record
Abstract
BACKGROUND: Despite the importance of evidence syntheses in informing policymaking, their production and use remain limited in the Eastern Mediterranean region (EMR). There is a lack of empirical research on approaches to promote and use policy-relevant evidence syntheses to inform policymaking processes in the EMR. OBJECTIVE: This study sought to describe the development of an impact-oriented approach to link evidence synthesis to policy, and its implementation through selected case studies in Lebanon, a middle-income country in the EMR. METHODS: This study followed a multifaceted and iterative process that included (i) a review of the literature, (ii) input from international experts in evidence synthesis and evidence-informed health policymaking, and (iii) application in a real-world setting (implementation). We describe four selected case studies of implementation. Surveys were used to assess policy briefs, deliberative dialogues, and post-dialogue activities. Additionally, Kingdon's stream theory was adopted to further explain how and why the selected policy issues rose to the decision agenda. RESULTS: The approach incorporates three interrelated phases: (1) priority setting, (2) evidence synthesis, and (3) uptake. Policy-relevant priorities are generated through formal priority setting exercises, direct requests by policymakers and stakeholders, or a focusing event. Identified priorities are translated into focused questions that can be addressed via evidence synthesis (phase 1). Next, a scoping of the literature is conducted to identify existing evidence syntheses addressing the question of interest. Unless the team identifies relevant, up-to-date and high-quality evidence syntheses, it proceeds to conducting SRs addressing the priority questions of interest (phase 2). Next, the team prepares knowledge translation products (e.g., policy briefs) for undertaking knowledge uptake activities, followed by monitoring and evaluation (phase 3). There are two prerequisites to the application of the approach: enhancing contextual awareness and capacity strengthening. The four case studies illustrate how evidence produced from the suites of activities was used to inform health policies and practices. CONCLUSIONS: To our knowledge, this is the first study to describe both the development and implementation of an approach to link evidence synthesis to policy in the EMR. We believe the approach will be useful for researchers, knowledge translation platforms, governments, and funders seeking to promote evidence-informed policymaking and practice.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.033 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 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 | 0.000 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".