Evidence map›Paper›PMID 41965639›Full record

ArticleHealth research policy and systems2026

A rapid tool for understanding how knowledge users engage with research findings in research-for-development contexts.

Steven Lam, Vivian Hoffmann, Lilian Otoigo, Hung Nguyen-Viet

Abstract read
In one paragraph

Article in Health research policy and systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Steven LamInternational Livestock Research Institute, Naivasha Road, P.O. box 30709-00100, Nairobi, Kenya. thestevenlam@gmail.com.
Vivian HoffmannInternational Food and Policy Research Institute, Washington, United States of America.
Lilian OtoigoInternational Livestock Research Institute, Naivasha Road, P.O. box 30709-00100, Nairobi, Kenya.
Hung Nguyen-VietInternational Livestock Research Institute, Hanoi, Vietnam. h.nguyen@cgiar.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Promoting the use of research findings in development projects is essential but often overlooked during study design. Existing frameworks for research use tend to focus on clinical settings and offer questionable applicability to development contexts, which are typically nonlinear, dynamic and cross-sectoral. As a result, there remains a gap in tools that can capture how evidence is intended to be applied by diverse knowledge users in real-world development settings. To address this gap, and drawing on over a decade of experience implementing research-to-action strategies, our objective is to develop a simple research uptake and use tool to better understand and support the use of evidence in research-for-development. We piloted the tool immediately after or 1 month following dissemination workshops, engaging 206 participants across nine sessions in five countries - Kenya, Ethiopia, Bangladesh, Malawi, and Vietnam - to gather insights on which evidence was most relevant, how participants intended to apply it and why they valued it. Although conceptualized with a focus on agriculture and global health research, this framework is broadly applicable across the wider development sector in low- and middle-income countries.

Indexed as

Developing CountriesKnowledgeResearch DesignTranslational Research, BiomedicalBangladeshEthiopiaGlobal HealthHumansKenyaMalawiVietnamAfricaAsiaKnowledge translationOne healthResearch evaluationResearch impact

Identifiers

PMID41965639
PMCPMC13185264

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.