Evidence map›Paper›PMID 35487555›Full record

ArticleGlobal health, science and practice2022

Using a Rapid Knowledge Translation Approach for Better Sexual and Reproductive Health and Rights in Bangladesh, Burundi, Indonesia, and Jordan.

Kimberley Meijers, Anke van der Kwaak, Ibrahim Aqel, Robert Borst, Françoise Jenniskens, Aryanti Radyowijati, Arnob Chakrabarty, Eric Nzeyimana, Ely Sawitri, Noor Tromp

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Article in Global health, science and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Kimberley MeijersKIT Royal Tropical Institute, Amsterdam, Netherlands. k.meijers@kit.nl.
Anke van der KwaakKIT Royal Tropical Institute, Amsterdam, Netherlands.
Ibrahim AqelInstitute for Family Health, King Hussein Foundation, Amman, Jordan.
Robert BorstErasmus School of Health Policy & Management, Rotterdam, Netherlands.
Françoise JenniskensIndependent senior sexual and reproductive health and rights expert, Wittem, Netherlands.
Aryanti RadyowijatiResultsinHealth, Leiderdorp, Netherlands.
Arnob ChakrabartyRedOrange Media and Communications, Bangladesh.
Eric NzeyimanaEast African Community, Tanzania.
Ely SawitriRutgers WPF Indonesia, Indonesia.
Noor TrompKIT Royal Tropical Institute, Amsterdam, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTranslation of knowledge into policy and practice is important to prevent sexual reproductive health and rights (SRHR)-related morbidity and mortality and ensure access to rights. Existing approaches to knowledge translation are often relatively rigid and implicitly assume linear processes, leading to time-consuming processes that are not tailored to countries' needs. APPROACH: SRHR knowledge platforms designed and implemented a collaborative rapid improvement model for knowledge translation (CRIM-KT) in Burundi, Bangladesh, Indonesia, and Jordan. The approach consisted of learning sessions and action periods aimed at improving policies and practices addressing the prevention of child marriage and teenage pregnancies. To evaluate the approach, a participatory action learning process took place throughout the implementation (September 2017 and January 2019). An end evaluation was conducted using a desk review of project documentation, in-depth interviews, and a focus group discussion to document the process, outcomes, and lessons learned. ACHIEVEMENTS: In Indonesia, a local government policy was changed that aims to prevent child marriage by avoiding misinterpretation of a local cultural practice. In Jordan, the cabinet endorsed a national action plan to prevent child marriage and changes in practice took place. In Burundi, no tangible changes in policy and practice in SRHR were observed. In Bangladesh, practice changed by strengthening coordination for collaboration and exchange among stakeholders to prevent child marriage. In all countries, the approach considerably strengthened participants' knowledge translation capacities.

conclusionThe CRIM-KT led to improvements in policy and practice in a relatively short time frame and different contexts. This can be explained by the systematic, structured, and participatory approach, allowing for contextual adaptation and involvement of stakeholders, as well as the cross-learning on 2 levels (international and country collaboration teams). The principles of the CRIM-KT may be further developed and applied in other fields in global health to strengthen knowledge translation processes.

Indexed as

Reproductive HealthTranslational Science, BiomedicalAdolescentBangladeshBurundiChildFemaleHumansIndonesiaJordanPregnancy

Identifiers

PMID35487555
PMCPMC9053141

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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.