Relationships between public health faculty and decision makers at four governmental levels: a social network analysis. (31st August 2018)

• Record Type: Journal Article
• Authors: Jessani, Nasreen S; Babcock, Carly; Siddiqi, Sameer; Davey-Rothwell, Melissa; Ho, Shirley; Holtgrave, David R
• Is Part Of: Evidence & policy. Volume 14:Number 3(2018)
• Page Start: 499
• Page End: 522
• Publication Date: 2018-08-31
• Subjects: SOCIAL NETWORK ANALYSIS -- EVIDENCE-INFORMED DECISION MAKING -- SCHOOL OF PUBLIC HEALTH -- KNOWLEDGE BROKER; Policy sciences -- Periodicals; Social policy -- Research -- Periodicals; Public welfare -- Research -- Periodicals; Social service -- Decision making -- Periodicals; 320.6
• DOI: 10.1332/174426418X15230282334424
• Languages: English
• ISSNs: 1744-2648

Abstract

Abstract : 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 dynamic quality of these relationships often remains unknown therefore rendering the potential for influence untapped, uncoordinated, redundant or inefficient. Methods We mapped the relationships between faculty at the Johns Hopkins Bloomberg School of Public Health and decision makers at the city, state, federal and global levels. In 2016, 211 of 627 eligible full-time faculty participated in a sociometric survey. Common metrics for social network analysis were modified to provide reliable indicators of network characteristics. UCINet was used for network visualisation. 'Highly connected' individuals included: faculty with ≥5 contacts at any one government level; those appearing in the top 10% in total across all four levels; decision makers appearing in the top 2% of frequently mentioned people. Results Results revealed faculty relationships spanning >100 government departments, ~700 decision makers, and 45 country governments. The majority of respondents (72%) mentioned at least one decision maker; 49 faculty and 24 decision makers appeared as 'highly connected'. While the School of Public Health (SPH) demonstrates a diversity of relationships within and across government agencies, there were also identifiable gaps. Conclusion This study provides further support for using Network Analysis to explore size, reach, diversity and density of relationships between academic faculty and decision makers, with network maps serving as a proxy for potential influence. Academic institutions and government agencies should nurture a variety of relationships in order to enhance engaged scholarship and further informed decision making.