Mapping the Growing Discipline of Dissemination and Implementation Science in Health

Abstract

Background: The field of dissemination and implementation (D&I) research in health has grown considerably in the past decade. Despite the potential for advancing the science, limited research has focused on mapping the field.

Methods: We administered an online survey to individuals in the D&I field to assess participants' demographics and expertise, as well as engagement with journals and conferences, publications, and grants. A combined roster-nomination method was used to collect data on participants' advice networks and collaboration networks; participants' motivations for choosing collaborators was also assessed. Frequency and descriptive statistics were used to characterize the overall sample; network metrics were used to characterize both networks. Among a sub-sample of respondents who were researchers, regression analyses identified predictors of two metrics of academic performance (i.e., publications and funded grants).

Results: A total of 421 individuals completed the survey, representing a 30.75% response rate of eligible individuals. Most participants were White (n = 343), female (n = 284, 67.4%), and identified as a researcher (n = 340, 81%). Both the advice and the collaboration networks displayed characteristics of a small world network. The most important motivations for selecting collaborators were aligned with advancing the science (i.e., prior collaborators, strong reputation, and good collaborators) rather than relying on human proclivities for homophily, proximity, and friendship. Among a sub-sample of 295 researchers, expertise (individual predictor), status (advice network), and connectedness (collaboration network) were significant predictors of both metrics of academic performance.

Conclusions: Network-based interventions can enhance collaboration and productivity; future research is needed to leverage these data to advance the field.

Keywords: Network science; dissemination science; implementation science; network analysis; scientometrics.

Figure 1. Sociogram of Individuals with the Top 10 In-Degree Scores (Popularity) in the Advice Network

Note. Top 10 individuals with the highest number of incoming ties from other actors (i.e., highest number of in-degrees) in the advice network are reference by color in the legend above (n = 10). Node size is proportional to the number of advice links received for named individual. For ease of visualization, we show the largest component in the advice network, comprised of 215 respondents.

Figure 2. Sociogram of Individuals with the Top 10 Degree Scores (Popularity) in the Collaboration Network

Note. The top 11 individuals (two had same score) with the highest number of incoming ties from other actors (i.e., highest number of degrees) in the collaboration network are reference by color in the legend above. Node size is proportional to the number of collaboration links for named individual. For ease of visualization, we show the largest component in the advice network, comprised of 140 respondents.