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Record W4200491809 · doi:10.1186/s12961-021-00804-z

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

2021· article· en· W4200491809 on OpenAlexaboutno aff
Lawrence Ulu Ogbonnaya, Ijeoma Nkem Okedo‐Alex, Ifeyinwa Chizoba Akamike, Benedict Ndubueze Azuogu, Henry Chukwuemeka Uro-Chukwu, Ogbonnaya Ogbu, Chigozie Jesse Uneke

Bibliographic record

VenueHealth Research Policy and Systems · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityOperationalizationKnowledge translationContext (archaeology)Health policyLikert scaleStakeholderPolicy analysisPolitical scienceHealth services researchPublic relationsPublic administrationMedicineKnowledge managementPsychologyNursingPublic healthComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.585
GPT teacher head0.563
Teacher spread0.022 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

MetaresearchScholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
DomainMethods
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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