Assessing the usefulness of policy brief and policy dialogue as knowledge translation tools towards contextualizing the accountability framework for routine immunization at a subnational level in Nigeria
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that implementing an accountability mechanism such as the accountability framework for routine immunization in Nigeria (AFRIN) will improve routine immunization (RI) performance. The fact that the AFRIN, which was developed in 2012, still had not been operationalized at the subnational level (Ebonyi State) by 2018 may in part account for the poor RI coverage (33%) in 2017. Knowledge translation (KT) is defined as the methods for closing the gaps from knowledge to practice. Policy briefs (useful in communicating research findings to policy-makers) and policy dialogues (that enable stakeholders to understand research evidence and create context-resonant implementation plans) are two KT tools. This study evaluated their usefulness in enabling policy-makers to contextualize AFRIN in Ebonyi State, Nigeria. METHODS: The study design was cross-sectional descriptive with mixed-methods data collection. A policy brief developed from AFRIN guided deliberations in a 1-day multi-stakeholder policy dialogue by 30 policy actors. The usefulness of the KT tools in contextualizing policy recommendations in the AFRIN was assessed using validated questionnaires developed at McMaster University, Canada. RESULTS: At the end of the policy dialogue, the policy options in the policy brief were accepted but their implementation strategies were altered to suit the local context. The respondents' mean ratings (MNR) of the overall usefulness of the policy brief and the policy dialogue in contextualizing the implementation strategies were 6.39 and 6.67, respectively, on a seven-point Likert scale (very useful). The MNR of the different dimensions of the policy brief and policy dialogue ranged from 6.17 to 6.60 and from 6.10 to 6.83, respectively (i.e. moderately helpful to very helpful). CONCLUSION: The participants perceived the KT tools (policy brief and policy dialogue) as being very useful in contextualizing policy recommendations in a national policy document into state context-resonant implementable recommendations. We recommend the use of these KT tools in operationalizing AFRIN at the subnational level in Nigeria.
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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: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Scholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".