242307 Seeing the forest and the trees: Using social network analysis to understand academic-community collaboration in health promotion

Monday, October 31, 2011: 5:30 PM

Shijian Li, PhD , MSW , School of Medicine, New York University, New York City, NY
Nadia Islam, PhD , Center for the Study of Asian American Health, NYU Institute of Community Health and Research, NYU School of Medicine, New York, NY
Smiti B. Kapadia, MPH , Health Promotion and Prevention Research Center, New York University, New York, NY
Chau-Trinh Shevrin, DrPH , Center for the Study of Asian American Health, NYU Institute of Community Health and Research, NYU School of Medicine, New York, NY
Sally Guttmacher, PHD, MPhil , Steinhardt School, Department of Nutrition, Food Studies, and Public Health, New York University, New York, NY
Simona Kwon, DrPH, MPH , Center for the Study of Asian American Health, New York University School of Medicine, New York, NY
Shao-Chee Sim, PhD , Charles B. Wang Community Health Center, New York, NY
Nancy VanDevanter, DrPH, RN , New York University College of Nursing, New York, NY
Mariano Rey, MD , Center for the Study of Asian American Health, NYU Institute of Community Health and Research, New York University School of Medicine, New York, NY
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.

Learning Areas:
Conduct evaluation related to programs, research, and other areas of practice
Planning of health education strategies, interventions, and programs
Program planning
Public health or related research
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
1. Explain social network analysis (SNA) as a valuable tool for health program evaluation 2. Demonstrate the design of a SNA study for the Prevention Research Center (PRC) at New York University 3. Present the SNA findings in diagnosing successes and challenges of NYU PRC academic-community collaboration.

Keywords: Collaboration, Evaluation

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: : I designed and implemented the study. With a background in public health, social work and political sicence, my research interests focus on social determinants of health and community-based health interventions and program evaluation. Area of expertise: quantitative and qualitative research methods; conversant with various software programs in advanced statistical and qualitative data analysis.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.