Building capacity in dissemination and implementation research: the presence and impact of advice networks

Abstract

Background: As dissemination and implementation (D&I) research increases, we must continue to expand training capacity and research networks. Documenting, understanding, and enhancing advice networks identifies key connectors and areas where networks are less established. In 2012 Norton et al. mapped D&I science advice and collaboration networks. The current study builds on this work and aims to map current D&I research advice networks.

Methods: D&I researchers in the United States (US) and Canada were identified through a combination of publication metrics, and key persons identified networks and were invited to participate (n = 1,576). In this social network analysis study, participants completed an online survey identifying up to 10 people from whom they sought and/or gave advice on D&I research. Participants identified four types of advice received: research methods, grant, career, or another type (e.g., work/life balance). We used descriptive statistics to characterize the sample and network metrics and visualizations to describe the composition of advice networks.

Results: A total of 482 individuals completed the survey. Eighty-six (18%) worked in Canada and 396 (82%) in the US. Respondents had varying D&I research expertise levels; 14% beginner expertise, 45% intermediate, 29% advanced, and 12% expert. The advice network included 978 connected nodes/individuals. For all research types, out-degree, or advice giving, was higher for those with advanced or expert-level expertise (6.9 and 11.9, respectively) than those with beginner or intermediate expertise (0.8 and 2.2, respectively). Respondents reporting White race reported giving (out-degree = 5.2) and receiving (in-degree = 6.1) more advice compared to individuals reporting Asian (out-degree = 2.9, in-degree = 5.3), Black (out-degree = 2.3, in-degree = 5.2), or other races (out-degree = 2.5, in-degree = 5.4). Assortativity analyses revealed 98% of network ties came from individuals within the same country. The top two reasons for advice seeking were trusting the individual to give good advice (78%) and the individual's knowledge/experience in specific D&I content (69%).

Conclusions: The D&I research network is becoming more dispersed as the field expands. Findings highlight opportunities to further connect D&I researchers in the US and Canada, individuals with emerging skills in D&I research, and minoritized racial groups. Expanding peer mentoring opportunities, especially for minoritized groups, can enhance the field's capacity for growth.

Keywords: Capacity building; Dissemination research; Implementation science; Knowledge mobilization; Knowledge translation; Mentoring; Social network analysis; Training.

Fig. 1

Theoretical directed network. This theoretical network displays the bi-directional nature of data collection. Each circle, or node/individual, is labeled with a letter-#, where the number indicates the individual’s out-degree value. For example, A-2 indicates person A gave advice to two other individuals. All gray arrows indicate the node of origin reported giving advice to the end node (e.g., C reported giving advice to D). All red arrows indicate the end node reported receiving advice from the origin node (e.g., A reported receiving advice from H). Individuals received a tally for their out-degree when they reported giving advice to an individual and when an individual reported receiving advice from them, which is considered bi-directional data

Fig. 2

Advice networks by level of D&I expertise

Fig. 3

Advice networks by country

Fig. 4

Example ego network