Document Type
Article
Publication Date
3-2-2020
Publication Title
Substance Use & Misuse
Volume
55
Issue
5
Abstract
Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects “diffusing” into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti’s Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP set have network position and non-network differences (such as demographic, attitudinal, or behavioral differences) compared to the remaining members of the target group (non-SPs). Methods: A first-year class at a private residential university (N = 1342) completed network and non-network measures. Analyses were restricted only to heavy drinkers, leading to a final analytic sample of 529. Results: SPs and non-SPs differed on multiple network variables, but did not differ on most demographic, attitudinal, and behavior variables. Conclusions: As designed, the SP program identified participants who were distinguished by their network position. The fact that they did not also differ on other characteristics shows the SPs are not significantly different than heavy drinkers who were not selected.
First Page
715
Last Page
720
Recommended Citation
Ott, Miles Q.; Balestrieri, Sara G.; DiGuiseppi, Graham; Clark, Melissa A.; Bernstein, Michael; Helseth, Sarah; and Barnett, Nancy P., "Identification and Description of Potentially Influential Social Network Members using the Strategic Player Approach" (2020). Statistical and Data Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/sds_facpubs/24
Digital Object Identifier (DOI)
10.1080/10826084.2019.1701032
Rights
Licensed to Smith College and distributed CC-BY under the Smith College Faculty Open Access Policy.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Included in
Data Science Commons, Other Computer Sciences Commons, Statistics and Probability Commons
Comments
Peer reviewed accepted manuscript.