Sridharan Vishnupriya, Cohen Trevor, Cobb Nathan, Myneni Sahiti
The University of Texas School of Biomedical Informatics at Houston, Texas, USA.
Georgetown University Medical Center, Washington DC, USA.
Stud Health Technol Inform. 2017;237:123-129.
Online communities have been an integral part of tobacco cessation programs. They are rich in content, and offer insights into factors affecting an individual's behavior change efforts. We used word representation techniques to infer implicit meaning embedded in messages exchanged in a health-related online community. Our analysis of peer interactions revealed that individuals factor in safety, glamour, expense, and media projection when choosing a form of nicotine intake. When choosing pharmacotherapy techniques, individuals focus on brands, dosage, and side effects associated with each form (e.g. gums, patches). Our analysis sheds light on factors embedded in peer interactions, which might lead to opinion formation based on peer influence and knowledge dissemination in these social platforms. Such understanding enables design of high-engagement behavior change technologies, through personalization of content delivery by factoring in individual-level beliefs, behavioral state, and community-level influences.
在线社区一直是戒烟项目不可或缺的一部分。它们内容丰富，能深入了解影响个人行为改变努力的因素。我们使用词表示技术来推断在一个与健康相关的在线社区中交换的信息中所蕴含的隐含意义。我们对同伴互动的分析表明，个体在选择尼古丁摄入形式时会考虑安全性、魅力、费用和媒体宣传。在选择药物治疗技术时，个体关注与每种形式（如口香糖、贴片）相关的品牌、剂量和副作用。我们的分析揭示了同伴互动中所蕴含的因素，这些因素可能会导致在这些社交平台上基于同伴影响和知识传播形成观点。这种理解能够通过考虑个体层面的信念、行为状态和社区层面的影响来实现内容传递的个性化，从而设计出高参与度的行为改变技术。
