NetHealth: Modeling the Co-Evolution of Social Networks and Health Behaviors

项目总结/摘要 该项目的目的是收集两个方面两年多的连续纵向数据 人们的社交网络和健康行为，以（1）测试有关社会联系机制的理论， 网络和人类行为，以及（2）评估社会影响过程导致变化的程度 与健康相关的行为。评估社会影响力在社交网络中发挥作用的程度至关重要 制定未来的干预措施，利用社交网络的力量，减少 不健康的行为，并增加健康行为的流行。然而，根据经验， 重要的社会影响是非常困难的。除了社交，还有其他机制。 传染，通过它可以观察到的集群（即相似的人之间的联系）发生：自我选择 （与相似的其他人形成联系），共同暴露于并发的外源性因素，选择性回避，以及 对于没有表现出特征匹配的领带，衰减率更高。 从经验上判断这些竞争过程需要高有效性，细粒度， 关于人们社交网络及其健康相关行为方面随时间变化的纵向数据。 该项目将通过创新使用两个移动的，远程，永远在线的不显眼的 传感器系统：智能手机和其他智能设备，用于捕获通信交互信息 和社会关系，以及健康监测臂章，以捕捉有关身体活动（PA）和睡眠习惯的信息 （SH）。500名即将入学的大学生将被要求在他们的智能手机上安装监控应用程序。 设备，并将收到一个健康监测臂章抵达校园后，佩戴臂章在任何时候。 关于谁与谁通信的数据从手机和其他智能设备中获得，以及PA上的数据 和SH将使我们能够绘制出社交网络和PA的共同进化， 因为学生被随机分配到同性霍尔斯和宿舍内， 他们，因为有一些社会关系之前到达，这是一个理想的人口，其中观察 社交网络的出现。 有了这些数据，我们将回答有关网络和行为的基本问题。你是谁 知道（一个人在社交网络中的位置）决定你做什么（例如， 人是（？还是说你所做的决定了你认识谁？当两个PA不同的人 和/或她建立了社交关系他们可能变得相似吗？如果是这样，是因为不那么活跃（更穷） 睡眠者）变得更活跃（更健康的睡眠者）或反之亦然？另外，如果有健康 行为差异，领带可能会很快死亡，永远没有机会加强足够， 影响过程可以开始发挥作用？

PROJECT SUMMARY/ABSTRACT The purpose of this project is to collect continuous longitudinal data over a two year period on both people's social networks and health behaviors in order to (1) test theories about the mechanisms linking social networks and human behavior, and (2) assess the extent to which social influence processes lead to changes in health-related behaviors. Assessing the extent to which social influence operates in social networks is critical for devising future interventions that could harness the power of social networks to reduce incidences of unhealthy behaviors and increase the prevalence of healthier ones. However empirically determining how important social influence is has turned out to be very difficult. There are other mechanisms besides social contagion through which the observed clustering (i.e. ties among similar people) can occur: self-selection (forming ties with similar others), joint exposure to concurrent exogenous factors, selective avoidance, and high decay rates for ties that do not exhibit trait matching. Empirically adjudicating between these competing processes requires high-validity, fine-grained, longitudinal data on changes over time in people's social networks and their health-related behavioral sides. This project will collect such data through the innovative use of two mobile, remote, always-on unobtrusive sensor systems: smartphones and other smart devices to capture information on communicative interactions and social ties, and health monitor armbands to capture information on physical activity (PA) and sleep habits (SH). Five hundred incoming college students will be asked to install monitoring applications on their smart devices and will receive a health monitor armband upon arrival on campus to wear the armband at all times. Data about who communicates with who obtained from the phones and other smart devices, and data on PA and SH obtained from the armbands will allow us to map out the co-evolution of a social network and PA and SH behaviors within it. Because students are randomly allocated to same-sex residence halls and rooms within them, and because there are few social ties prior to arrival, this is an idea population in which to observe the emergence of a social network. With these data we will answer fundamental questions about networks and behavior. Does who you know (a person's position in a social network) determine what you do (for instance, how physical active a person is)? Or does what you do determine who you know? What happens when two people with different PA and/or SH form a social tie? Are they likely to become similar, and if so, is it because the less active (poorer sleeper) becomes more active (a healthier sleepier) or vice a versa? Alternatively, when there are health behavior differences, is the tie likely to die quickly and never get a chance to strengthen enough so that influence processes can begin to come into play?