Community Social Network Pattern Analysis: Development of a Novel Methodology Using a Complex, Multi-Level Health Intervention

Community social networks (CSN) include both individuals and groups, and those with strong partnerships and relationships are well positioned to implement community-based interventions. However, information on the nature of CSN relationships, which is required for multi-level community-based interventions, is not present in the literature. Using data from the multi-level Children's Healthy Living (CHL) trial to reduce child obesity in nine Pacific communities, this study aimed to develop a methodology based on Social Network Analysis (SNA) to understand how CSN evolved over the course of a two-year trial, as well as the characteristics of CSN most successful in impacting indicators of childhood obesity. The two-year trial was conducted over four six-month intervals. Within each interval, implemented activities, as recorded in CHL monthly reports, were coded by activity implementer(s), e.g. government agency, school, or community-based group, as well as for collective efficacy impact of the activity, e.g. to leverage resources from outside the CSN or to facilitate civic engagement. Coded data were used to create CSN maps for the four time intervals, and SNA techniques examined the CSN characteristics. CSN density increased over time, as measured by the number of ties within the network. Schools, community-based groups and large organisations were identified as the primary implementers of the CHL intervention and formed a community implementer backbone. Social leveraging, i.e. linking local groups to people with authority over outside resources, was shown to be a central component in intervention success. It took time to develop strong CSN, and stronger (denser) CSN were more successful in building social cohesion and enacting community change. Findings illustrate a methodology that can be useful for tracking the development and impact of CSN.