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Comparing Social Network Influence on Alcohol Use Using Affiliation Data

使用隶属关系数据比较社交网络对饮酒的影响

基本信息

批准号：
8643170
负责人：
Kayo Fujimoto
金额：
$ 11.9万
依托单位：
UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-15 至 2015-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8643170
关键词：
Accounting Address Adolescent Affect Alcohol consumption Alcohol or Other Drugs use Alcohols Attention Behavior Behavior Control Behavioral Characteristics Collection Complex Computer software Data Data Analyses Dependence Dependency Development Diffusion Distant Etiology Event Evolution Friends Friendships Goals Graph Health Individual Joints Knowledge Life Longitudinal Studies Maps Measures Mentors Methodology Methods Mission Modeling Neighborhoods Network-based Organism Outcome Measure Pathway Analysis Peer Group Phase Play Positioning Attribute Prevention program Procedures Process Property Public Health Relative (related person)Research Risk Risk Factors Role Schools Social Environment Social Network Specialist Staging Statistical Models Structure Sum Techniques Testing United States National Institutes of Health Weight abstracting adolescent alcohol adolescent substance use alcohol misuse alcohol prevention base burden of illness career conditioning disability drinking behavior insight longitudinal analysis peer peer influence social substance using adolescents theories tool underage drinking

项目摘要

6. Project Summary/Abstract The goal of the proposed research is to extend one-mode network data analysis of friendship relations (actor-by-actor network) to two-mode (actor-by-event affiliation/bipartite) network data to model the influence of co-participation in school-based organized activities on adolescent alcohol use. The first aim is to determine the utility of a new conceptualization of affiliation-based network influence by directly modeling (using multiple Network Autocorrelation Models) the effect of two-mode/affiliation exposure on drinking behavior controlling for other competing peer influences primarily those based on close friends or peers occupying similar network position. The second aim is to determine the relative contributions of multiple forms of network effects on alcohol use, and how these network effects operate together as risk factors. The research during the R00 phase will focus on structural properties and the dynamics of two-mode network structural analysis of affiliation networks in relation to alcohol. Related to this, the third aim is to estimate the new specification of two-mode Exponential Random Graph Model (ERGM) with geometric weighting technique to test the effects of co-affiliation on adolescent alcohol use, and it will be extended to longitudinal analysis by stochastically modeling the co-evolution of one-mode and two-mode networks to examine the cross-dependencies in the evolution of friendship and affiliation networks in relation to alcohol use within an actor-based modeling framework. The fourth aim is to explore social mechanisms that drive joint dynamics of affiliation network structures conditioned on one-mode friends' networks in relation to alcohol use. Addressing these questions would help establish the PI's long-term career goal of establishing herself as a specialist in two-mode network, which is separate and distinct from the primary mentor's (Thomas Valente) main approach of analyzing one-mode networks in the study of peer influence on substance use centered on adolescent alcohol use. Research for both K99 and R00 phase use data from both the National Longitudinal Study of Adolescent Health (Add Health) and from USC-collected data. Not only does the proposed study have the potential to provide insight into how school-based alcohol prevention program based on social influence model should be implemented, the proposed approach of using two-mode network data does not require the collection of network data (sociometrics). Therefore this methodology has the potential to be applied to a wide variety of studies and used in various fields of public health that traditionally have not been able to use network methods.

6. 项目总结/摘要本研究的目标是扩展友谊关系的单模式网络数据分析（演员-演员网络）到双模式（演员-事件隶属关系/二分）网络数据来建模共同参与学校组织的活动对青少年饮酒的影响。第一个目标是通过直接建模来确定基于隶属关系的网络影响力的新概念的效用（使用多个网络自相关模型）两种模式/隶属关系暴露对饮酒的影响对其他竞争同伴的行为控制主要影响基于亲密朋友或同伴的行为占据相似的网络地位。第二个目标是确定多个因素的相对贡献对酒精使用的网络效应的形式，以及这些网络效应如何作为风险因素一起发挥作用。这 R00阶段的研究将重点关注双模网络的结构特性和动力学与酒精相关的隶属网络的结构分析。与此相关，第三个目标是估计具有几何加权的双模式指数随机图模型（ERGM）的新规范技术来测试共同归属对青少年饮酒的影响，并将扩展到纵向通过对一模和二模网络的协同演化进行随机建模来进行分析，以检查友谊和归属网络的演变与饮酒相关的交叉依赖性基于参与者的建模框架。第四个目标是探索驱动联合动力的社会机制以与饮酒相关的单一模式朋友网络为条件的隶属网络结构。解决这些问题将有助于 PI 确立长期职业目标，将自己打造成一名双模式网络专家，与主要导师（Thomas Valente）不同且独立以同伴对物质使用影响的研究为中心分析单模网络的主要方法关于青少年饮酒。 K99 和 R00 相的研究均使用来自国家实验室的数据青少年健康纵向研究（Add Health）和南加州大学收集的数据。不仅拟议的研究有可能深入了解学校的酒精预防计划应实施基于社会影响力模型的建议方法，使用两种模式网络数据不需要收集网络数据（社会计量学）。因此该方法论具有具有应用于广泛研究和公共卫生各个领域的潜力传统上一直无法使用网络方法。