Seeing the forest and the trees: Using social network analysis to understand academic-community collaboration in health promotion

Background/significance: While academic institutions and communities are increasingly being urged to collaborate in resolving complex health issues, little is known about what factors influence the creation, evolution,structure, and functioning of a viable academic-community coalition. Social network analysis (SNA) allows researchers to describe, integrate, and analyze multiple and substantive dimensions of coalition structures formed between diverse partners. Objectives/purpose: Demonstrate the value of using SNA for health program evaluation, share the experience of designing a SNA evaluation plan for the NYU Prevention Research Center (PRC), and present the findings of the analysis. Methods: We adopted a multi-level, longitudinal, whole network approach in collecting data from all PRC partnership programs/organizations. The network survey questionnaire was pilot-tested before administration to individuals/organizations significantly involved in the NYU PRC. The instrument collected organizational level data on information and resource sharing, and collaboration on community events and research. Data is collected semiannually to gain a thorough understanding of coalition initiation, operation, and sustainability. The current study presents findings based on data from the first wave of the administered survey. Results: Findings presented will include an assessment of the following: 1) What factors influence the formation and functioning of a network? 2) What are the situational dynamics of the newly established NYU PRC network? 3) How do the network's multiple ties influence its members' behaviors and attitude? Conclusions/Discussion: The analysis provides an objective dynamic process analysis of information exchange, relationship quality, and evidence of collaboration within an academic-community coalition.