A network analysis of dissemination and implementation research expertise across a university: Central actors and expertise clusters. Issue 1 (7th March 2022)

• Record Type: Journal Article
• Authors: Yousefi Nooraie, Reza; Roman, Gretchen; Fiscella, Kevin; McMahon, James M.; Orlando, Elissa; Bennett, Nancy M.
• Is Part Of: Journal of clinical and translational science. Volume 6:Issue 1(2022)
• Publication Date: 2022-03-07
• Subjects: Capacity Building -- Clinical & Translational Science Award (CTSA) -- Dissemination & Implementation Science -- Program Assessment -- Social Network Analysis; Clinical medicine -- Research -- Periodicals; Medicine, Experimental -- Periodicals; Human experimentation in medicine -- Periodicals; 616.027
• DOI: 10.1017/cts.2022.8
• Languages: English
• ISSNs: 2059-8661

Abstract

Abstract: Background: Although dissemination and implementation (D&I) science is a growing field, many health researchers with relevant D&I expertise do not self-identify as D&I researchers. The goal of this work was to analyze the distribution, clustering, and recognition of D&I expertise in an academic institution. Methods: A snowball survey was administered to investigators at University of Rochester with experience and/or interest in D&I research. The respondents were asked to identify their level of D&I expertise and to nominate others who were experienced and/or active in D&I research. We used social network analysis to examine nomination networks. Results: Sixty-eight participants provided information about their D&I expertise. Thirty-eight percent of the survey respondents self-identified as D&I researchers, 24% as conducting D&I under different labels, and 38% were familiar with D&I concepts. D&I researchers were, on average, the most central actors in the network (nominated most by other survey participants) and had the highest within-group density, indicating wide recognition by colleagues and among themselves. Researchers who applied D&I under different labels had the highest within-group reciprocity (25%), and the highest between-group reciprocity (29%) with researchers familiar with D&I. Participants significantly tended to nominate peers within their departments and within their expertise categories. Conclusions: Identifying and engaging unrecognized clusters of expertise related to D&I research may provide opportunities for mutual learning and dialog and will be critical to bridging across departmental and topic area silos and building capacity for D&I in academic settings.