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Abstract/Summary
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Background!#!The Collaboration for Evidence-based Healthcare and Public Health in Africa (CEBHA+) is a research consortium concerned with the prevention, diagnosis and treatment of non-communicable diseases. CEBHA+ seeks to engage policymakers and practitioners throughout the research process in order to build lasting relationships, enhance evidence uptake, and create long-term capacity among partner institutions in Ethiopia, Malawi, Rwanda, South Africa and Uganda in collaboration with two German universities. This integrated knowledge translation (IKT) approach includes the formal development, implementation and evaluation of country specific IKT strategies.!##!Methods!#!We have conceptualised the CEBHA+ IKT approach as a complex intervention in a complex system. We will employ a comparative case study (CCS) design and mixed methods to facilitate an in-depth evaluation. We will use quantitative surveys, qualitative interviews, quarterly updates, and a policy document analysis to capture the process and outcomes of IKT across the African CEBHA+ partner sites. We will conduct an early stage (early 2020) and a late-stage evaluation (early 2022), triangulate the data collected with various methods at each site and subsequently compare our findings across the five sites.!##!Discussion!#!Evaluating a complex intervention such as the CEBHA+ IKT approach is complicated, even more so when undertaken across five diverse countries. Despite conceptual, methodological and practical challenges, our comparative case study addresses important evidence gaps: While involving decision-makers in the research process is gaining traction worldwide, we still know very little regarding (i) whether this approach really makes a difference to evidence uptake, (ii) the mechanisms that make IKT successful, and (iii) relevant differences across socio-cultural contexts. The evaluation described here is intended to provide relevant insights on all of these aspects, notably in countries in Sub-Saharan Africa, and is expected to contribute to the science of IKT overall.
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1000
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Hinweis
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DeepGreen-ID: 5c74dd41e6694fe29a420a586ae62cec ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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