Review and special articleBridging Research and Practice: Models for Dissemination and Implementation Research
Section snippets
Context
Vast resources are invested in the development of interventions to prevent and treat disease; however, only a fraction of research products are translated to practice and policy in order to affect population health.1, 2, 3 Dissemination and implementation (D&I) science seeks to understand how to systematically facilitate deployment and utilization of evidence-based approaches to improve the quality and effectiveness of health promotion, health services, and health care.4 Although this
Evidence Acquisition
Dissemination and implementation research is described using several terms, many of which are used interchangeably, for example, knowledge translation, knowledge exchange, and knowledge utilization.16 The diverse range of disciplines contributing models to D&I research leads to a tremendously wide range of sources. These factors prohibited establishing a scope for this review that would comply with traditional systematic review guidelines. Therefore, a narrative approach was determined to be
Evidence Synthesis
From a total of 109 models, 26 were excluded due to a focus on practitioners, rather than researchers; 12 were excluded because they were not applicable to local-level dissemination (communities or organizations); and eight were excluded because they focused on dissemination at the end of a research study rather than D&I research. Two models were identified as duplicates, and combined for inclusion. A total of 61 models were included in this review. A complete list of the models, including all
Discussion
The importance of using models in D&I studies cannot be overstated. Use of models not only makes a study more likely to be successful, but if an existing model is used, this application also contributes to the literature on a particular model and enables continued distillation and better understanding of model constructs.10, 11, 12, 13 This paper presents 61 existing models (as well as information regarding the settings and approaches to which these models are suited) to assist researchers
Acknowledgments
The authors are grateful to numerous model developers who commented on their models and the variables used for classification. The authors also appreciate the feedback of the Washington University Network for Dissemination and Implementation Research (WUNDIR).
This project was funded in part by cooperative agreement number U48/DP001903 from the CDC, Prevention Research Centers Program, and Grant 1R01CA124404-01 from the National Cancer Institute at the NIH. It was also supported in part by the
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