Focused Training in Social Networks and Health

摘要 健康和健康行为在很大程度上取决于社交网络。两种病毒的传播 传染性疾病，如艾滋病毒，以及形成 健康行为，如饮食风险行为，可以理解为网络产生的健康 流程，在(有时非常复杂和动态的)社交网络上运行。这 过去一段时间，社交网络和健康研究的显著增长证明了这一点 30年了。尽管有明确的需求和对健康重要性的认识，但网络方法是 卫生和卫生政策的标准社会科学方法序列中很少涉及 学者。社交网络与健康(SN&H)学者R25的第一阶段专注于 注重广度而不是深度的密集介绍，并直接投资于研究员的研究- 现成的项目，以帮助刺激创新的健康研究。这一方法取得了成功， 学员的满意度和对培训的需求每年都超过开业。 尽管基础课程顺序需求很高，但我们的研究员和校友 不断表示有兴趣进行更深入、更先进的方法培训。因此，对于这一点 续订我们建议通过提供两种类型的研讨会来扩展这一密集介绍 交替年份：我们将在奇数年(节目第5年、第7年、第9年)继续密集介绍 提供偶数年(6、8、10)的高级方法序列。高级培训将重点放在 关于基本方法的估计和实现的细微差别，包括 同辈效应(含实验)、复杂数据收集、高级网络感应 技术(社区和角色)、模拟和计算建模以及动态 统计建模。目标受众将是已经开始网络分析的人 参加过我们早先的研讨会的人，或参加过相关项目的人。通过提供高级 通过培训，我们可以推动社交网络社区和健康学者通过新手工作 并使他们能够培训和指导其他人。新的一套课程还将 通过新代码、视频讲座和教学材料扩展我们的在线资源。这 计划将为参与者提供所需的技能和资源，使研究从 将早期想法转化为实用、合理和多产的社交网络和健康研究 处于当代网络科学的前沿。

Abstract Health and health behavior depend crucially on social networks. Both the spread of communicable diseases, such as HIV, and the diffusion of beliefs and practices that shape health behavior, such as dietary risk behavior, can be understood as network-generated health processes, operating over (sometimes very complex and dynamic) social networks. This recognition is evidenced by the dramatic growth in social network and health studies in the last 30 years. Despite the clear demand and recognition of health importance, network methods are rarely covered in the standard social-science methods sequences for health and health-policy scholars. The first phase of the Social Networks & Health (SN&H) scholars R25 focused on an intensive introduction that favored breadth over depth and investing directly in fellows’ research- ready projects to help spur innovative health research. This approach has been successful, with high participant satisfaction and demand for the training outpacing openings every year. Although the basics course sequence is in high demand, our Fellows and alumni have continuously expressed interest in more in-depth, advanced methods training. As such, for this renewal we propose to expand on this intensive introduction by offering two types of workshops in alternating years: we’ll continue the intensive intro in odd years (program years 5, 7, 9) but offer an advanced methods sequence in even years (6, 8, 10). The advanced training will focus on the estimation and implementation nuances of base methods, covering causal inference in peer effects (including experiments), complex data collection, advanced network inductive techniques (communities and roles), simulation and computational modeling, and dynamic statistical modeling. The target audience will be people who have started network analysis related projects or who have participated in our earlier workshops. By providing advanced training, we can propel the community of social networks and health scholars past novice work and empower them to be able to train and mentor others. The new set of courses will also expand our online resources with new code, video lectures, and instructional materials. This program will provide participants with the skills and resources needed to move research from inchoate ideas to practical, well-reasoned and generative social networks and health research at the cutting edge of contemporary network science.