The impact of social norms on diffusion dynamics: A simulation of e-cigarette use behavior

Health Education & Behavior ยท 2025

Diffusion of innovations theory can be used to understand how to prevent or slow the spread of harmful behaviors, such as e-cigarette use in adolescent social networks.

Published2025Cited by1

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  1. Piombo, S.
  2. Vega Yon, G. G.University of UtahiD
  3. Valente, T. W.

Abstract

Diffusion of innovations theory can be used to understand how to prevent or slow the spread of harmful behaviors, such as e-cigarette use in adolescent social networks. This study explores how different network intervention strategies could impact diffusion dynamics through network simulations based on observed social norms and e-cigarette use data. Simulations were initialized with baseline network data collected from 10 schools in a prospective cohort study of adolescent social networks and health behaviors in Southern California. Diffusion conditions varied by changes in social norms for intervention nodes (pro-e-cigarette, anti-e-cigarette, or neutral norms) and intervention strategy, where greater pro- and anti-tobacco norms were assigned to 15% of the network based on four intervention seeding conditions: opinion leadership, betweenness centrality, segmentation, and random selection. For each network, simulations were run using the netdiffuseR package in R and multivariate generalized linear models were estimated to examine changes in diffusion dynamics. Diffusion prevalence and rate were greater in denser networks and networks with more initial e-cigarette users. Anti-e-cigarette norms significantly decreased average prevalence across all intervention conditions. Strategically selecting high betweenness centrality nodes and opinion leader nodes significantly decreased the average prevalence of e-cigarette use. The results of this study show that achieving a change in norms for 15% of a network can substantially impact e-cigarette use prevalence. Furthermore, this study enhances our knowledge of how personal and network factors affect diffusion dynamics and demonstrates that targeting social norms through network-based interventions is one avenue for slowing the spread of harmful behaviors.

Cite

@article{piombo2025,
  title = {The impact of social norms on diffusion dynamics: A simulation of e-cigarette use behavior},
  author = {{Piombo}, {Sarah} and {Vega Yon}, {George G.} and {Valente}, {Thomas W.}},
  year = {2025},
  month = {3},
  journal = {Health Education & Behavior},
  volume = {52},
  number = {4},
  pages = {428โ€“438},
  doi = {10.1177/10901981251327189},
  url = {https://doi.org/10.1177/10901981251327189},
}