Making sense of implementation theories, models and frameworks
TLDR
A taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science is proposed to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers.Abstract:
Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers. Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited “how-to” support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.read more
Citations
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Research methods in the social sciences
TL;DR: Loads of the research methods in the social sciences book catalogues in this site are found as the choice of you visiting this page.
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Making sense of complexity in context and implementation: the Context and Implementation of Complex Interventions (CICI) framework
Lisa M. Pfadenhauer,Ansgar Gerhardus,Kati Mozygemba,Kristin Bakke Lysdahl,Andrew Booth,Bjørn Hofmann,Philip Wahlster,Stephanie Polus,Jacob Burns,Louise Brereton,Eva Rehfuess +10 more
TL;DR: The CICI framework addresses and graphically presents context, implementation and setting in an integrated way and aims at simplifying and structuring complexity in order to advance the understanding of whether and how interventions work.
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Scaling up physical activity interventions worldwide: stepping up to larger and smarter approaches to get people moving
Rodrigo Siqueira Reis,Rodrigo Siqueira Reis,Deborah Salvo,David Ogilvie,Estelle V. Lambert,Shifalika Goenka,Ross C. Brownson +6 more
TL;DR: A mixed-methods approach is used to comprehensively examine the factors that could help to achieve scale up interventions that are capable of increasing levels of physical activity in populations across the varying cultural, geographic, social, and economic contexts worldwide.
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Systematic review of the Exploration, Preparation, Implementation, Sustainment (EPIS) framework
TL;DR: This systematic review enumerated multiple settings and ways the EPIS framework has been applied in implementation research projects, and summarized promising characteristics and strengths of the framework, illustrated with examples.
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When complexity science meets implementation science: a theoretical and empirical analysis of systems change
TL;DR: What implementation science can learn from complexity science is discussed, and some of the properties of healthcare systems that enable or constrain the goals the authors have for better, more effective, more evidence-based care are teased out.
References
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