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• W3016783441 startingPage "e002269" @default.
• W3016783441 abstract "In global health, researchers and decision makers, many of whom have medical, epidemiology or biostatistics background, are increasingly interested in evaluating the implementation of health interventions. Implementation science, particularly for the study of public policies, has existed since at least the 1930s. This science makes compelling use of explicit theories and analytic frameworks that ensure research quality and rigour. Our objective is to inform researchers and decision makers who are not familiar with this research branch about these theories and analytic frameworks. We define four models of causation used in implementation science: intervention theory, frameworks, middle-range theory and grand theory. We then explain how scientists apply these models for three main implementation studies: fidelity assessment, process evaluation and complex evaluation. For each study, we provide concrete examples from research in Cuba and Africa to better understand the implementation of health interventions in global health context. Global health researchers and decision makers with a quantitative background will not become implementation scientists after reading this article. However, we believe they will be more aware of the need for rigorous implementation evaluations of global health interventions, alongside impact evaluations, and in collaboration with social scientists." @default.
• W3016783441 created "2020-04-24" @default.
• W3016783441 creator A5000656520 @default.
• W3016783441 creator A5063378460 @default.
• W3016783441 creator A5070464718 @default.
• W3016783441 date "2020-04-01" @default.
• W3016783441 modified "2023-10-12" @default.
• W3016783441 title "Using implementation science theories and frameworks in global health" @default.
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• W3016783441 doi "https://doi.org/10.1136/bmjgh-2019-002269" @default.
• W3016783441 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7199704" @default.
• W3016783441 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32377405" @default.
• W3016783441 hasPublicationYear "2020" @default.
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