Enhancing translational team effectiveness: The Wisconsin Interventions in Team Science framework for translating empirically informed strategies into evidence-based interventions. Issue 1 (21st July 2021)

• Record Type: Journal Article
• Authors: Rolland, Betsy; Hohl, Sarah D.; Johnson, LaKaija J.
• Is Part Of: Journal of clinical and translational science. Volume 5:Issue 1(2021)
• Publication Date: 2021-07-21
• Subjects: Framework -- team science -- translational teams; Clinical medicine -- Research -- Periodicals; Medicine, Experimental -- Periodicals; Human experimentation in medicine -- Periodicals; 616.027
• DOI: 10.1017/cts.2021.825
• Languages: English
• ISSNs: 2059-8661

Abstract

Abstract: Achieving the clinical, public health, economic, and policy benefits of translational science requires the integration and application of findings across biomedical, clinical, and behavioral science and health policy, and thus, collaboration across experts in these areas. To do so, translational teams need the skills, knowledge, and attitudes to mitigate challenges and build on strengths of cross-disciplinary collaboration. Though these competencies are not innate to teams, they can be built through the implementation of effective strategies and interventions. The Science of Team Science (SciTS) has contributed robust theories and evidence of empirically-informed strategies and best practices to enhance collaboration. Yet the field lacks methodological approaches to rigorously translate those strategies into evidence-based interventions to improve collaborative translational research. Here, we apply lessons from Implementation Science and Human-Centered Design & Engineering to describe the Wisconsin Interventions in Team Science (WITS) framework, a process for translating established team science strategies into evidence-based interventions to bolster translational team effectiveness. To illustrate our use of WITS, we describe how University of Wisconsin's Institute for Clinical and Translational Research translated the existing Collaboration Planning framework into a robust, scalable, replicable intervention. We conclude with recommendations for future SciTS research to refine and test the framework.