Piombo Sarah E, Vega Yon George G, Valente Thomas W
University of Southern California, Los Angeles, CA, USA.
The University of Utah, Salt Lake City, UT, USA.
Health Educ Behav. 2025 Aug;52(4):428-438. doi: 10.1177/10901981251327189. Epub 2025 Mar 27.
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.
创新扩散理论可用于理解如何预防或减缓有害行为的传播，比如青少年社交网络中的电子烟使用行为。本研究基于观察到的社会规范和电子烟使用数据，通过网络模拟来探究不同的网络干预策略如何影响传播动态。模拟以从南加州青少年社交网络与健康行为前瞻性队列研究中的10所学校收集的基线网络数据初始化。传播条件因干预节点的社会规范（支持电子烟、反对电子烟或中立规范）和干预策略的变化而不同，其中根据意见领袖、中介中心性、分割和随机选择这四种干预播种条件，将更强的支持和反对烟草规范分配给15%的网络。对于每个网络，使用R语言中的netdiffuseR包进行模拟，并估计多元广义线性模型以检验传播动态的变化。在更密集的网络和初始电子烟使用者更多的网络中，传播流行率和速率更高。反对电子烟规范在所有干预条件下均显著降低了平均流行率。策略性地选择具有高中介中心性的节点和意见领袖节点可显著降低电子烟使用的平均流行率。本研究结果表明，使网络中15%的规范发生改变可大幅影响电子烟使用流行率。此外，本研究增进了我们对个人和网络因素如何影响传播动态的了解，并表明通过基于网络的干预来针对社会规范是减缓有害行为传播的一条途径。
