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Record W4401423547 · doi:10.1186/s12961-024-01169-9

Research evidence communication for policy-makers: a rapid scoping review on frameworks, guidance and tools, and barriers and facilitators

2024· article· en· W4401423547 on OpenAlexaff
Jorge Otávio Maia Barreto, Roberta Crevelário de Melo, Letícia Aparecida Lopes Bezerra da Silva, Bruna Carolina de Araújo, Cintia de Freitas Oliveira, Tereza Setsuko Toma, Maritsa Carla de Bortoli, Peter DeMaio, Tanja Kuchenmüller

Bibliographic record

VenueHealth Research Policy and Systems · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcMaster UniversityHamilton Health Sciences
FundersWorld Health Organization
KeywordsKnowledge translationHealth services researchHealth policyPublic relationsHealth administrationEvidence-based practiceProcess (computing)Health communicationPublic healthKnowledge managementPolitical scienceMedicineNursingComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Communication is a multifaceted process, ranging from linear, one-way approaches, such as transmitting a simple message, to continuous exchanges and feedback loops among stakeholders. In particular the COVID-19 pandemic underscored the critical need for timely, effective and credible evidence communication to increase awareness, levels of trust, and evidence uptake in policy and practice. However, whether to improve policy responses in crises or address more commonplace societal challenges, comprehensive guidance on evidence communication to decision-makers in health policies and systems remains limited. Our objective was to identify and systematize the global evidence on frameworks, guidance and tools supporting effective communication of research evidence to facilitate knowledge translation and evidence-informed policy-making processes, while also addressing barriers and facilitators. METHODS: We conducted a rapid scoping review following the Joanna Briggs Manual. Literature searches were performed across eight indexed databases and two sources of grey literature, without language or time restrictions. The methodological quality of included studies was assessed, and a narrative-interpretative synthesis was applied to present the findings. RESULTS: We identified 16 documents presenting either complete frameworks or framework components, including guidance and tools, aimed at supporting evidence communication for policy development. These frameworks outlined strategies, theoretical models, barriers and facilitators, as well as insights into policy-makers' perspectives, communication needs, and preferences. Three primary evidence communication strategies, comprising eleven sub-strategies, emerged: "Health information packaging", "Targeting and tailoring messages to the audience", and "Combined communication strategies". Based on the documented barriers and facilitators at micro, meso and macro levels, critical factors for successful communication of evidence to policy-makers were identified. CONCLUSIONS: Effective communication is indispensable for facilitating knowledge translation and evidence-informed policy-making. Nonetheless gaps persist in frameworks designed to enhance research communication to policy-makers, particularly regarding the effectiveness of multiple communication strategies. To advance in this field, the development of comprehensive frameworks incorporating implementation strategies is warranted. Additionally, barriers and facilitators to implementing effective communication must be recognized and addressed taking diverse contexts into consideration. Registration https://zenodo.org/record/5578550.

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
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptScholarly communication
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
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)0.076
metaresearch head score (Gemma)0.083
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0760.083
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.908
GPT teacher head0.783
Teacher spread0.125 · 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.

Scholarly communication

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

Study designSystematic review
Domainnot available
GenreReview

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

Citations13
Published2024
Admission routes1
Has abstractyes

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