Background: Relationships between academic faculty and decision makers have been documented as an important factor in the evidence-to policy process. However, knowledge about the breadth, depth and quality of these relationships often remains unknown therefore rendering the potential for influence untapped, inefficient, uncoordinated or redundant.
Objectives: The purpose of this study was to explore Social Network Analysis (SNA) as a means to map and understand the size, breadth, depth and variety of city, state, federal and global government networks held by faculty at The Johns Hopkins Bloomberg School of Public Health (JHSPH), USA.
Methods: Between May 2016 and December 2016, 211 (32%) of 651 eligible full-time faculty across all 10 departments at JHSPH participated in a sociometric survey. The survey elicited faculty relationships with decision-makers at the various government levels. SNA permitted mapping of networks using UCINet. Descriptive data and tests of association were conducted in STATA.
Results: Preliminary results indicate significant depth as well as breadth of faculty relationships with networks across over 100 government departments at city, state, national, and international levels, close to 700 individual decision makers, and 45 country governments. These varied by department as well as by government level. Factors affecting the size, breadth and depth of networks included: structural (faculty roles and positions), professional (research expertise, approach), and experiential (practice-based environments) amongst others.
Conclusions: Mapping relationships using SNA is a useful first step to understand the depth and breadth of networks of academic faculty with decision makers. It provides some insight with respect to an institution’s overall potential to influence and impact policy and practice. Where networks are dense, the opportunities to have influence is likely greater and sustained. Where there are gaps in the network, institutions such as JHSPH can be strategic about building relationships that may lead to policy influence.