Social network analysis of public health programs to measure partnership Martin W. Schoen * , Sarah Moreland-Russell, Kim Prewitt, Bobbi J. Carothers Center for Public Health Systems Science, George Warren Brown School of Social Work, Washington University in Saint Louis, USA article info Article history: Received 7 July 2013 Received in revised form 30 August 2014 Accepted 29 October 2014 Available online 30 October 2014 Keywords: Social network analysis Obesity prevention Tobacco cessation Public health Collaboration Partnership Community research abstract In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce to- bacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the net- works, we conducted comparative analyses with and without adjustment for network size. SIM pro- grams had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. © 2014 Elsevier Ltd. All rights reserved. 1. Introduction Collaborative efforts among organizations with multiple pro- gramming and skill sets can result in higher levels of community impact (Kania and Kramer, 2011). An increasing number of public health initiatives use community-based approaches involving cross-sector partnerships (Roussos and Fawcett, 2000). Integrated efforts to address public health issues by involving multiple stakeholders are expected to result in better health outcomes than programs not using a network approach (Kwait et al., 2001). The rationale behind this is that no single organization has full control over all of the determinants of population health (Woulfe et al., 2010). By pooling resources, talents, and strategies, multiple sec- tors can more effectively carry out the responsibilities that affect the health of the targeted population (Martin et al., 2009). While community-based health initiatives or collective action approaches are quite popular, there is a lack of substantive research on their effectiveness and impact (Roussos and Fawcett, 2000). A key reason for the shortage of evidence is that evaluating the structure and collaboration of coalitions or community partner- ships is challenging (de Silva-Sanigorski et al., 2010a). These diffi- culties must be considered when evaluating collaborative efforts and further highlight the need for continued research on partner- ship formation using designs that measure activities, organizations, and social network development (Provan et al., 2003). Network analysis can measure partnership characteristics and can be used to predict collaboration and effectiveness in organizations (Honeycutt and Strong, 2011). Network metrics such as degree, density, and centralization can be used describe relationships among people and organizations and can reveal differences in communication and collaboration among coalitions (Scholz et al., 2008) and determine community capacity (Singer and Kegler, 2004). Social network methods are frequently performed on single networks at one time (Leischow et al., 2010) or over a period of time (Luque et al., 2011) to examine network characteristics. There are few examples of using whole networks as the unit of analysis * Corresponding author. Center for Public Health Systems Science, 700 Rosedale Avenue, Campus Box 1009, St. Louis, MO 63112-1408, USA. E-mail address: schoenmw@slu.edu (M.W. Schoen). Contents lists available at ScienceDirect Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed http://dx.doi.org/10.1016/j.socscimed.2014.10.057 0277-9536/© 2014 Elsevier Ltd. All rights reserved. Social Science & Medicine 123 (2014) 90e95