This interactive webtool is designed to help researchers and practitioners develop a ‘logic model’ or diagram for their research or practice question, select the dissemination and implementation (D&I) Model(s) that best fit(s) their research question or practice problem, combine multiple D&I Models, adapt the D&I model(s) to the study or practice context, use the D&I Model(s) throughout the research or practice process, and find existing measures to assess the key constructs of the D&I Model(s) selected. The term ‘Model’ is used to refer to both theories and frameworks that make the dissemination and implementation of evidence-based interventions more likely
The Dissemination and Implementation Models in Health Research and Practice webtool was developed and is maintained as a collaborative effort of colleagues from the ACCORDS Dissemination and Implementation Science Program at the University of Colorado, Denver, the Dissemination and Implementation Research Core (DIRC) at the Washington University Institute for Clinical and Translational Science and the Dissemination and Implementation Science Center (DISC) at UC San Diego.
- Borsika Rabin, PhD, Project lead, UC San Diego and University of Colorado, Denver
- Russ Glasgow, PhD, University of Colorado, Denver
- Rachel Tabak, PhD, Washington University in St. Louis
- Ross Brownson, PhD, Washington University in St. Louis
- Amy Huebschmann, MD, MS, University of Colorado, Denver
- Sara Malone, LCSW, Washington University in St. Louis
- Bryan Ford, University of Colorado, Denver
The initial set of models for this website were selected from two reviews of the D&I literature:
Each model is categorized using an expanded criteria developed based on the original Tabak and colleagues paper:
- Model: Includes both theories and frameworks that enhance dissemination and implementation research by making the spread of evidence-based interventions more likely.
- D and/or I: The focus on dissemination and/or implementation activities. D-only focuses on an active approach of spreading evidence-based interventions to target audience via determined channels using planned strategies. D=I, D>I, and I>D means there is some focus on both dissemination and implementation. I-only focuses on process of putting to use or integrating evidence-based interventions within a setting.
- Construct Flexibility: The definition/flexibility of the model constructs. Construct flexibility is measured on a 1-5 scale, with Broad (1) meaning constructs are loosely outlined and defined allowing for greater flexibility to apply the model to a wide array of D&I activities and contexts, or Operational (5) meaning constructs are detailed with step-by-step actions for completion of D&I research.
- Socio-Ecological Levels:
The level of the framework at which the model operates. Individual includes personal characteristics; Organization includes hospitals, service organizations, and factories; Community includes local government and neighborhoods; System includes hospital systems and government; Policy includes changes in policy.
- Field of Origin:
The field of study in which the model originated.
Whether the models is for the use of practitioners or researchers.
List of components of the website based on abstractions of all elements and their classification based on larger common construct categories used in this webtool.
Weblink to website associated with the model when applicable.
- Number of Times Cited:
The # of times the original publication for the model was cited as indicated by Google Scholar since 2016.
Reference of the lead publication(s) describing the model.
Reference to publications that used the model.
- User ratings:
Ratings and comments provided by users on the webtool.
See the Glossary for additional defintions used throughout the site.
An abstraction form was developed to abstract information about additional models. Each model was categorized by two experts and a consensus was reached. For further model abstractions, a lead expert trained a research assistant to abstract models and did additional validations.
Constructs and subconstructs (i.e., elements) were abstracted from each model and a modified Delphi approach was used to create meta-constructs. Meta-constructs were then assigned to models based on their elements. Measures are linked to outside measure databases based on constructs.
Funding for the development of the current version of this webtool was provided by:
- the ACCORDS Dissemination and Implementation Science Program at the University of Colorado, Denver
- the Colorado Implementation Science Center for Cancer Control (ISC3) (NIH/NCI award P50CA244688)
- the Washington University Institute for Clinical and Translational Science (NIH/NCATS award UL1TR002345)
- the Prevention Research Center in St. Louis (CDC award U48DP006395)
- the Washington University Implementation Science Center for Cancer Control (ISC3) (NIH/NCI award P50CA244431)
We would like to thank Mary Hook for developing the example for the Adapt and Use sections of the webtool based on her study.