Many evaluation studies assess the direct effect of an intervention on individuals, but there is an increasing interest in clarifying how interventions can impact larger social settings. One process that can lead to these setting-level effects is diffusion, in which intervention effects spread from participants to non-participants. Diffusion may be particularly important when intervention participation rates are low, as they often are in universal family based prevention programs. We drew on socialization and diffusion theories to articulate how features of peer networks may promote the diffusion of intervention effects. Then, we tested the measurement properties of ten social network analytic (SNA) measures of diffusion potential. Data were from 42 networks (n = 5,784 students) involved in the PROSPER intervention trial. All families of sixth-grade students were invited to participate in a family based substance use prevention program, and 17 % of the families attended at least one session. We identified two dimensions of network structure—social integration and location of intervention participants in their peer network—that might promote diffusion. Analyses demonstrated that these SNA measures varied across networks and were distinct from traditional analytic measures that do not require social network analysis (i.e., participation rate, how representative participants are of the broader population). Importantly, several SNA measures and the global network index predicted diffusion over and above the effect of participation rate and representativeness. We conclude by recommending which SNA measures may be the most promising for studying how networks promote the diffusion of intervention effects and lead to setting-level effects.
Prevention Science – Springer Journals
Published: Feb 1, 2014
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