Pennsylvania State University, University Park, PA, USA.
Prev Sci. 2011 Dec;12(4):349-60. doi: 10.1007/s11121-011-0229-2.
A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools' organizational, cultural or instructional systems that influence children's relationships), or implicitly (e.g., by altering behavioral norms designed to influence children's social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science--both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts.
大多数基于学校的预防计划旨在改变环境层面的社会动态，无论是通过明确地（例如，改变影响儿童关系的学校组织、文化或教学系统），还是通过含蓄地（例如，通过改变旨在影响儿童社会关系和互动的行为规范）。然而，在这些计划的结果分析中，丰富而复杂的同伴网络动态通常被简化为个体特征的聚合，或者使用不考虑网络数据相互依赖性的方法进行评估。在本文中，我们介绍了社会网络分析领域的概念和分析方法，并说明了它们对预防科学的巨大价值——既是完善计划理论的工具来源，也是更复杂和有针对性的干预效果检验方法。另一个目标是为社会网络分析对公共卫生工作的更广泛影响的讨论提供信息。
