Rulison Kelly L, Gest Scott D, Osgood D Wayne
Department of Public Health Education, University of North Carolina at Greensboro, Greensboro, NC, 27410, USA,
Prev Sci. 2015 Jan;16(1):133-44. doi: 10.1007/s11121-014-0465-3.
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.
许多评估研究评估了干预措施对个体的直接影响,但人们越来越关注如何阐明干预措施如何影响更大的社会环境。一个可能导致这些环境层面影响的过程是扩散,即干预效果从参与者传播到非参与者。当干预参与率较低时,扩散可能尤为重要,就像在普遍的家庭预防项目中经常出现的情况那样。我们借鉴社会化和扩散理论来阐明同伴网络的特征可能如何促进干预效果的扩散。然后,我们测试了十种社会网络分析(SNA)扩散潜力测量方法的测量属性。数据来自参与PROSPER干预试验的42个网络(n = 5784名学生)。所有六年级学生的家庭都被邀请参加一个基于家庭的物质使用预防项目,17%的家庭至少参加了一次课程。我们确定了网络结构的两个维度——社会融合以及干预参与者在其同伴网络中的位置——这可能促进扩散。分析表明,这些SNA测量方法在不同网络中存在差异,并且与不需要社会网络分析的传统分析测量方法(即参与率、参与者对更广泛人群的代表性)不同。重要的是,几种SNA测量方法和全球网络指数在预测扩散方面超过了参与率和代表性的影响。我们最后推荐了哪些SNA测量方法在研究网络如何促进干预效果的扩散并导致环境层面影响方面可能最有前景。