Characterizing Social Networks and Communication Channels in a Web-Based Peer Support Intervention.
Characterizing Social Networks and Communication Channels in a Web-Based Peer Support Intervention.
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基于网络的同伴支持干预中社交网络和沟通渠道的特征。
DOI：
10.1089/cyber.2015.0359
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Hanneman,Robert
中科院分区：
文献类型：
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作者：
Owen,JasonE;Curran,Michaela;Bantum,ErinO'Carroll;Hanneman,Robert
网络和移动(MHealth)干预措施有望改善健康结果，但参与度和消耗量可能会减少效果大小。由于社交网络可以提高参与度，这是一种关键的行动机制，因此了解社交网络的结构和潜在影响可能是改善mHealth效果的关键。本研究(A)评估大型社交网络干预中四种不同沟通渠道(讨论板、聊天、电子邮件和博客)的社交网络特征，(B)预测在线社区的成员资格，以及(C)评估社区成员资格是否影响参与度。参与者是299名癌症幸存者，他们使用为期12周的Health-space.net干预措施，患有严重的痛苦。针对每种类型的网络通信(即，讨论板、博客、网络邮件和聊天)分别标识社交网络属性(例如，密度和集群)。每个渠道都表现出高度的聚集性，在一个沟通渠道中成为社区成员与在其他每个渠道中处于同一社区相关(φ= 0.56-0.89，PS <； 0.05)。社区成员的预测因沟通渠道不同而不同，这表明每个渠道都能接触到不同类型的用户。最后，讨论板、聊天或博客社区的成员身份与参与应对技能练习的时间(DS = 1.08-1.84，PS <； 0.001)和干预的总时间(DS = 1.13-1.8，PS <； 0.001)密切相关。提供多种沟通渠道的移动健康干预措施使参与者能够扩大他们与之沟通的个人数量，创造机会以不同的渠道与不同的个人进行交流，并可能提高整体参与度。
Web and mobile (mHealth) interventions have promise for improving health outcomes, but engagement and attrition may be reducing effect sizes. Because social networks can improve engagement, which is a key mechanism of action, understanding the structure and potential impact of social networks could be key to improving mHealth effects. This study (a) evaluates social network characteristics of four distinct communication channels (discussion board, chat, e-mail, and blog) in a large social networking intervention, (b) predicts membership in online communities, and (c) evaluates whether community membership impacts engagement. Participants were 299 cancer survivors with significant distress using the 12-week health-space.net intervention. Social networking attributes (e.g., density and clustering) were identified separately for each type of network communication (i.e., discussion board, blog, web mail, and chat). Each channel demonstrated high levels of clustering, and being a community member in one communication channel was associated with being in the same community in each of the other channels (φ= 0.56–0.89,ps < 0.05). Predictors of community membership differed across communication channels, suggesting that each channel reached distinct types of users. Finally, membership in a discussion board, chat, or blog community was strongly associated with time spent engaging with coping skills exercises (Ds = 1.08–1.84,ps < 0.001) and total time of intervention (Ds = 1.13–1.80,ps < 0.001). mHealth interventions that offer multiple channels for communication allow participants to expand the number of individuals with whom they are communicating, create opportunities for communicating with different individuals in distinct channels, and likely enhance overall engagement.