Social networks and health: a systematic review of sociocentric network studies in low- and middle-income countries.
Social networks and health: a systematic review of sociocentric network studies in low- and middle-income countries.
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DOI：
10.1016/j.socscimed.2014.08.019
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发表时间：
2015-01
期刊：
影响因子：
--
通讯作者：
Christakis NA
中科院分区：
文献类型：
--
作者：
Perkins JM;Subramanian SV;Christakis NA
在低收入和中等收入国家，自然形成的社交网络可能对健康结果特别重要，因为广泛的社会关系网往往是各种资源的主要来源。了解社会网络结构和网络中有影响力的个人如何通过对非目标参与者产生级联效应等方式放大干预措施在中低收入国家的效果，为提高此类环境中公共卫生干预措施的效率和效力提供了机会。我们对PubMed、Econlit、Sociological Abstracts和PsycINFO进行了系统回顾，以确定17篇社会中心网络论文（来自10项研究）的样本，这些论文专门研究了中低收入国家的健康问题。我们还单独选择了19篇社会中心网络论文（来自其他10项研究），这些论文涉及与中低收入国家福祉相关的发展主题。首先，为了提供一个方法资源，我们讨论了所选论文中采用的社会中心网络研究设计，然后提供了一个105个名称生成器问题的目录，用于测量本综述中引用的所有LMIC网络论文（包括自我和社会中心网络论文）中的社会联系。其次，我们发现，网络组成，个人网络中心性和网络结构与重要的健康行为和健康和发展成果在不同的背景下，在多个层次的分析和不同的网络类型。最后，我们强调卫生研究人员和从业人员在低收入国家的机会，1）设计有效的研究和干预措施在低收入国家，占某些个人和整体网络结构的社会中心网络位置，2）测量结果或干预外部性的传播，和3）提高援助的有效性和效率的基础上对社会结构的知识。总之，人类的健康和福祉是通过复杂的动态社会关系网联系在一起的。在资源有限、人们依赖直接和间接关系获得支持的情况下，利用这种信息可能特别重要。
In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex webs of dynamic social relationships. Harnessing such information may be especially important in contexts where resources are limited and people depend on their direct and indirect connections for support.
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