Social network positional selection of peer change agents

描述（由申请人提供）：我们将通过数学模型，利用通过现有的数字通信网络开发的变更代理属性和结构位置参数，评估同行变更代理通信的有效性。同伴改变代理（PCA）为基础的艾滋病毒预防方案利用同伴影响的现象，以及成员在社交网络如何相互沟通。基于PCA的干预措施是最常用的艾滋病毒预防外展干预措施，并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。这一提议的核心假设是，变革推动者往往比信息本身更重要。公共卫生官员宣传的信息往往对其他人，甚至对那些艾滋病毒风险增加的人兴趣有限。事实上，当信息的兴趣有限时，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衡量的结构地位，全部或部分地选择变革推动者，是提高同行影响力的一种方法：它在基于商业组织的干预措施中取得了成功。然而，它还没有在公共卫生领域得到实证检验。通过采用这一方法，本提案超越了传统的同行外联模式。除了利用PCA的结构网络位置，以提高创新的扩散，我们的模型还参数化PCA的重要属性，这是由主要的数据收集从一个大型网络的男性谁与男性发生性关系在印度南部。这些PCA属性包括社会地位特征、领导和沟通行为、与网络成员的关系质量以及物理属性。以前，我们已经开发了一种创新的方法，在这种情况下，允许通过使用手机通信网络在高风险的男性增强网络表征的社会网络表征。我们在印度拥有实地调查数据收集的专业知识，以及大规模社交网络数据收集和分析的经验。我们还拥有通过社交网络传播创新分析的经验，以及利用数学模型确定疾病和/或信息通过男男性行为者网络传播的经验。因此，我们将使用参与者访谈和社交网络生成的结构位置生成的属性在网络中建模安全套通信。将使用三类算法选择候选PCA：（1）基于属性的算法;（2）基于位置的算法;以及（3）组合的基于属性和位置的算法。将使用多个随机模型探索网络中安全套信息的流动，这些模型解决了缺失数据，并使用自我和同行评价数据进行了参数化。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伴变化代理人促进的网络扩散。

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.