Social network positional selection of peer change agents

描述(申请人提供)：我们将通过利用现有数字通信网络开发的更改代理属性和结构位置参数的数学模型来评估同行更改代理的沟通有效性。基于同龄人改变代理(PCA)的艾滋病毒预防计划利用了同龄人影响的现象以及社交网络中成员之间的沟通方式。以PCA为基础的干预措施是最常用的外展艾滋病毒预防干预措施，已在国内和国际上得到广泛实施。然而，现有的基于PCA的干预措施在国际环境中产生了令人失望的结果。这一提议的中心假设是，变革推动者往往比消息本身更重要。通常情况下，公共卫生官员宣传的信息可能对其他人兴趣有限，甚至对那些艾滋病毒风险增加的人也是如此。事实上，当人们对信息的兴趣有限时，那些艾滋病毒风险增加的人往往会更多地关注谁是变革的推动者。根据正式社会网络特征所衡量的结构地位，选择全部或部分变革推动者，是增加同行影响力的一种方法：它在基于企业组织的干预中取得了成功。然而，它还没有在公共卫生领域进行过实证测试。通过采用这一方法，这项提议超越了传统的同行外联模式。除了利用PCA的结构网络地位来促进创新的扩散之外，我们的模型还对PCA的重要属性进行了参数化，这些属性是通过从南印度男性性行为者的大型网络中收集的主要数据确定的。这些PCA属性包括社会地位特征、领导力和沟通行为、与网络成员的联系品质以及身体属性。此前，我们已经开发了一种在这种情况下进行社交网络表征的创新方法，允许通过在高危男性中使用手机通信网络来增强网络表征。我们在印度拥有现场调查数据收集专业知识，并拥有大规模社交网络数据收集和分析的经验。我们还拥有通过社会网络传播创新分析的经验，并利用数学模型确定通过男男性行为者(MSM)网络传播疾病和/或信息。因此，我们将使用参与者访谈生成的属性和社交网络生成的结构位置对网络中的避孕套传播进行建模。候选PCA将使用三类算法进行选择：(1)基于属性；(2)基于位置；(3)基于属性和基于位置的组合算法。安全套信息在网络中的流动将使用解决缺失数据的多个随机模型进行探索，并使用自我和同行评估数据进行参数化。在未来的工作中，我们将测试新的生物行为预防干预措施如何通过战略选择的同行变革促进剂促进的网络传播。

DESCRIPTION (provided by applicant): We will assess peer change agent communication effectiveness through mathematical models that utilize change agent attribute and structural position parameters developed through existing digital communication networks. Peer change agent (PCA)-based HIV prevention programs capitalize on the phenomenon of peer influence and how members in social networks communicate with one another. PCA-based interventions are the most frequently used outreach HIV prevention interventions and have been widely implemented both domestically and internationally. Existing PCA-based interventions, however, have yielded disappointing results in international settings. The central postulate of this proposa is that the change agent can often be more important than the message itself. Oftentimes, the messages promoted by public health officials may be of limited interest to others, even to those at increased HIV risk. In fact, when messages are of limited interest, those at increased HIV risk will tend to focus more on who the change agent is. The selection of change agents based in whole or in part upon their structural position as measured by formal social network characterization is one approach to increase potency of peer influence: it has been successful in business organization-based interventions. It has not, however, been empirically tested in the public health realm. By adopting this methodology, this proposal moves beyond traditional peer outreach models. In addition to utilizing the structural network position of PCAs to enhance the diffusion of innovation, our model also parameterizes important attributes of PCAs, which are determined by primary data collection from a large network of men who have sex with men in South India. These PCA attributes include social status features, leadership and communication behavior, tie qualities with members of their network, and physical attributes. Previously we have developed an innovative approach to social network characterization in this setting that allows for augmented network characterization through the use of cell phone communication networks in high- risk men. We have field survey data collection expertise in India and experience with large scale social network data collection and analyses. We also have experience in diffusion of innovation analyses through social networks and utilizing mathematical models for determining diffusion of disease and/or information through networks of men who have sex with men (MSM). Thus we will model condom communication within the network using attributes generated from participant interviews and social network-generated structural positions. Candidate PCAs will be selected using three classes of algorithms: (1) attribute-based; (2) position- based; and (3) combined attribute- and position-based. Flow of condom information in the network will be explored using multiple stochastic models that address missing data and are parameterized using self- and peer-evaluation data. In future work, we will test how novel bio-behavioral prevention interventions, diffuse through a network facilitated by strategically selected peer change agents.