TY - JOUR
T1 - Relationships between public health faculty and decision makers at four governmental levels
T2 - A social network analysis
AU - Jessani, Nasreen S.
AU - Babcock, Carly
AU - Siddiqi, Sameer
AU - Davey-Rothwell, Melissa
AU - Ho, Shirley
AU - Holtgrave, David R.
N1 - Publisher Copyright:
© 2018 Policy Press.
PY - 2018/8
Y1 - 2018/8
N2 - 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. eHighly connectedf 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 'ehighly connected'f. 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.
AB - 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. eHighly connectedf 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 'ehighly connected'f. 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.
KW - Evidence-informed decision making
KW - Knowledge broker
KW - School of Public Health
KW - Social network analysis
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U2 - 10.1332/174426418X15230282334424
DO - 10.1332/174426418X15230282334424
M3 - Review article
AN - SCOPUS:85050465092
SN - 1744-2648
VL - 14
SP - 499
EP - 522
JO - Evidence and Policy
JF - Evidence and Policy
IS - 3
ER -