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. 2021 Aug:282:114136.
doi: 10.1016/j.socscimed.2021.114136. Epub 2021 Jun 16.

Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach

Cassie McMillan  1 , David R Schaefer  2
Affiliations

Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach

Cassie McMillan et al. Soc Sci Med. 2021 Aug.

Abstract

Public health researchers and social scientists highlight the promise of network-based strategies to inform and enhance interventions that curb risky adolescent health behaviors. However, we currently lack an understanding of how different variants of network-based interventions shape the distribution of targeted behaviors. The current project considers the effectiveness of five targeting strategies that are designed to have differential impacts on the health of program participants versus non-participants. Using simulations that are empirically-grounded in 28 observed school-based networks from the PROSPER study, we evaluate how these approaches shape long-term alcohol use for intervention participants and non-participants, separately, and consider whether contextual factors moderate their success. Findings suggest that enrolling well-connected adolescents results in the lowest drinking levels for non-participants, while strategies that target groups of friends excel at protecting participants from harmful influences. These trends become increasingly pronounced in contexts characterized by higher levels of peer influence.

Keywords: Adolescents; Alcohol use; Empirically-grounded simulations; Health interventions; Social networks.

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Figures

Figure 1.
Figure 1.
Illustration of strategies targeting individuals versus groups Notes: Asterisks indicate that a node was invited to participate in the intervention by the practitioner. Dark gray nodes represent students who participated in the intervention (including friends invited by targets). Light gray nodes represent students with at least one direct connection to an intervention participant.
Figure 2.
Figure 2.
Differences between average drinking for participants and non-participants following random versus network-based interventions
Figure 3.
Figure 3.
Expected change in average drinking level for participants by intervention type and network-level peer influence
Figure 4.
Figure 4.
Expected change in average drinking level for non-participants by intervention type and network-level influence
See this image and copyright information in PMC

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