Abstract
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.
(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.
- Content Type Journal Article
- Pages 1-12
- DOI 10.1007/s11121-011-0229-2
- Authors
- Scott D. Gest, Pennsylvania State University, University Park, PA, USA
- D. Wayne Osgood, Pennsylvania State University, University Park, PA, USA
- Mark E. Feinberg, Pennsylvania State University, University Park, PA, USA
- Karen L. Bierman, Pennsylvania State University, University Park, PA, USA
- James Moody, Duke University, Durham, NC, USA
- Journal Prevention Science
- Online ISSN 1573-6695
- Print ISSN 1389-4986