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。无论是传播 传染病，如艾滋病毒，以及传播的信念和做法， 健康行为，如饮食风险行为，可以理解为网络生成健康 在社交网络上运行（有时非常复杂和动态）的过程。这 社会网络和健康研究的急剧增长证明了这一点。 30年尽管对健康的重要性有明确的需求和认识，但网络方法仍是 在健康和健康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 密集的介绍，有利于广度超过深度，并直接投资于研究员的研究- 准备好的项目，以帮助刺激创新的健康研究。这种方法是成功的， 参与者满意度高，对培训的需求每年都超过空缺。 虽然基础课程序列是在高需求，我们的研究员和校友有 不断表示有兴趣进行更深入、更先进的方法培训。因此，对于 更新我们建议通过提供两种类型的研讨会来扩大这种密集的介绍 在交替年：我们将继续在奇数年（计划年5，7，9）密集介绍，但 在偶数年提供一个先进的方法序列（6，8，10）。高级培训将侧重于 关于基本方法的估计和实现细微差别，包括 同伴效应（包括实验），复杂的数据收集，高级网络归纳 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 相关项目或参加过我们早期研讨会的人员。通过提供先进 培训，我们可以推动社会的社交网络和卫生学者过去的新手工作 让他们能够培训和指导他人。新课程还将 通过新代码、视频讲座和教学材料扩展我们的在线资源。这 该计划将为参与者提供将研究从 从早期的想法到实用的、理性的和生成性的社交网络和健康研究 在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.