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      Towards a common terminology: a simplified framework of interventions to promote and integrate evidence into health practices, systems, and policies

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          Abstract

          Background

          A wide range of diverse and inconsistent terminology exists in the field of knowledge translation. This limits the conduct of evidence syntheses, impedes communication and collaboration, and undermines knowledge translation of research findings in diverse settings. Improving uniformity of terminology could help address these challenges. In 2012, we convened an international working group to explore the idea of developing a common terminology and an overarching framework for knowledge translation interventions.

          Findings

          Methods included identifying and summarizing existing frameworks, mapping together a subset of those frameworks, and convening a multi-disciplinary group to begin working toward consensus. The group considered four potential approaches to creating a simplified framework: melding existing taxonomies, creating a framework of intervention mechanisms rather than intervention strategies, using a consensus process to expand one of the existing models/frameworks used by the group, or developing a new consensus framework.

          Conclusions

          The work group elected to draft a new, simplified consensus framework of interventions to promote and integrate evidence into health practices, systems and policies. The framework will include four key components: strategies and techniques (active ingredients), how they function (causal mechanisms), how they are delivered (mode of delivery), and what they aim to change (intended targets). The draft framework needs to be further developed by feedback and consultation with the research community and tested for usefulness through application and evaluation.

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          Most cited references35

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          Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

          Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.
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            The behaviour change wheel: A new method for characterising and designing behaviour change interventions

            Background Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. Methods A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Results Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity. Conclusions Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.
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              Developing and evaluating complex interventions: the new Medical Research Council guidance

              Evaluating complex interventions is complicated. The Medical Research Council's evaluation framework (2000) brought welcome clarity to the task. Now the council has updated its guidance
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                Author and article information

                Contributors
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central
                1748-5908
                2014
                1 May 2014
                : 9
                : 51
                Affiliations
                [1 ]Clinical Epidemiology Program, Ottawa Hospital Research Institute. Ottawa Hospital – General Campus, 501 Smyth Road, C.P. 711, K1H 8 L6 Ottawa, ON, Canada
                [2 ]School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
                [3 ]Research Department of Clinical, Educational, and Health Psychology, University College London, 1-19 Torrington Place, WC1E 7HB, London, UK
                [4 ]Department of Clinical Epidemiology and Biostatistics, Health Information Research Unit, McMaster University, CRL Building, 1280 Main Street West, L8S 4 K1, Hamilton, ON, Canada
                [5 ]National Trauma Research Institute, Monash University and The Alfred Hospital, Level 4, 89 Commercial Road, 3004 Melbourne, VIC, Australia
                [6 ]RAND Corporation, 1776 Main Street, m4339, Santa Monica 90407, CA, USA
                [7 ]Methology & Statistics of the Faculty of Psychology, Open University of the Netherlands, P.O. box 2960, 6401 DL Heerlen, The Netherlands
                [8 ]Academic Center for Evidence-Based Practice, University of Texas Health Science Center, San Antonio, 7703 Floyd Curl Drive, 78229-3900 San Antonio, TX, USA
                [9 ]Department of Clinical Epidemiology and Biostatistics, and The McMaster Health Forum, Centre for Health Economics and Policy Analysis, McMaster University, CRL 223, 1280 Main Street West, L8S 4 K1, Hamilton, ON, Canada
                [10 ]Department of Medicine, University of Ottawa, Ottawa Hospital – General Campus, 501 Smyth Road, C.P. 711, K1H 8 L6 Ottawa, ON, Canada
                Article
                1748-5908-9-51
                10.1186/1748-5908-9-51
                4021969
                24885553
                67e58616-81ff-4c61-9367-4bb624ae1a5e
                Copyright © 2014 Colquhoun et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 18 September 2013
                : 22 April 2014
                Categories
                Short Report

                Medicine
                knowledge translation,implementation science,classification,consensus,dissemination,implementation

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