Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data.
Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data.
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DOI：
10.2196/jmir.6426
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发表时间：
2017-10-31
影响因子：
7.4
通讯作者：
Das AK
中科院分区：
文献类型：
--
作者：
Kim SJ;Marsch LA;Hancock JT;Das AK
与药物使用有关的促进和预防药物使用的交流在社交媒体上广泛流行。社交媒体大数据涉及自然发生的通信现象，这些现象可以通过社交媒体平台观察到，可以用于计算或可扩展的解决方案，以生成数据驱动的推理。尽管利用社交媒体大数据监测和治疗药物使用问题的潜力很大，但社交媒体上与药物使用相关的交流的特征、机制和结果在很大程度上是未知的。了解这些方面可以帮助研究人员有效地利用社交媒体、大数据和平台，为有药物使用问题的人进行观察和健康沟通推广。这项批判性审查的目的是确定如何利用社交媒体大数据来了解有问题的处方药使用的沟通和行为模式。我们阐述了在使用社交媒体大数据进行药物滥用和成瘾研究时的理论应用、伦理挑战和方法论考虑。在严格审查过程的基础上，我们提出了一种类型学，并提出了关键举措，以解决使用社交媒体研究处方药滥用和成瘾方面的知识差距。首先，我们对社交媒体上与毒品相关的传播的文献进行了叙述性的总结。我们还考察了以下研究过程中的伦理考量：(1)社交媒体大数据挖掘，(2)分组或跟踪调查，以及(3)传播社交媒体数据驱动的研究结果。为了建立一个基于批评性综述的类型学，我们搜索了PubMed数据库和医学互联网研究杂志/JMIR出版物中的整个电子收藏主题“信息人口学和信息监控”。符合我们的纳入标准的研究(例如，使用关于处方药的非医疗用途的社交媒体数据，数据信息学驱动的发现)被审查以进行知识合成。用户特征、交流特征、这种交流的机制和预测因素，以及使用社交媒体进行有问题的药物使用相关交流的心理和行为结果是我们的类型学的维度。除了伦理实践和考虑因素外，我们还回顾了每项研究中使用的方法学和计算方法，以发展我们的类型学。我们开发了一种类型学，通过社交媒体大数据的镜头，更好地理解非医疗、有问题的处方药使用。对符合我们纳入标准的高度相关的研究进行了审查，以进行知识合成。在社交媒体上分享与问题物质使用相关的交流的用户的特征是按一般群体术语报告的，例如青少年、Twitter用户和Instagram用户。所有综述的研究都审查了社交媒体上与毒品使用有关的有问题的沟通的沟通特点，如语言特性和社交网络。在回顾的研究中，这种社交媒体沟通的机制和预测因素没有被直接检查或经验性地确定。参与和接触有关问题药物使用的社交媒体交流的心理或行为后果(例如，模仿危险健康行为的行为意图增加)是另一个研究不足的领域。我们在社交媒体传播和处方药滥用和上瘾的范围内提供理论应用、伦理考虑和经验证据。我们的批判性审查表明，社交媒体大数据可以成为了解、监测和干预药物滥用和成瘾问题的巨大资源。
Substance use–related communication for drug use promotion and its prevention is widely prevalent on social media. Social media big data involve naturally occurring communication phenomena that are observable through social media platforms, which can be used in computational or scalable solutions to generate data-driven inferences. Despite the promising potential to utilize social media big data to monitor and treat substance use problems, the characteristics, mechanisms, and outcomes of substance use–related communications on social media are largely unknown. Understanding these aspects can help researchers effectively leverage social media big data and platforms for observation and health communication outreach for people with substance use problems. The objective of this critical review was to determine how social media big data can be used to understand communication and behavioral patterns of problematic use of prescription drugs. We elaborate on theoretical applications, ethical challenges and methodological considerations when using social media big data for research on drug abuse and addiction. Based on a critical review process, we propose a typology with key initiatives to address the knowledge gap in the use of social media for research on prescription drug abuse and addiction. First, we provided a narrative summary of the literature on drug use–related communication on social media. We also examined ethical considerations in the research processes of (1) social media big data mining, (2) subgroup or follow-up investigation, and (3) dissemination of social media data-driven findings. To develop a critical review-based typology, we searched the PubMed database and the entire e-collection theme of “infodemiology and infoveillance” in the Journal of Medical Internet Research / JMIR Publications. Studies that met our inclusion criteria (eg, use of social media data concerning non-medical use of prescription drugs, data informatics-driven findings) were reviewed for knowledge synthesis. User characteristics, communication characteristics, mechanisms and predictors of such communications, and the psychological and behavioral outcomes of social media use for problematic drug use–related communications are the dimensions of our typology. In addition to ethical practices and considerations, we also reviewed the methodological and computational approaches used in each study to develop our typology. We developed a typology to better understand non-medical, problematic use of prescription drugs through the lens of social media big data. Highly relevant studies that met our inclusion criteria were reviewed for knowledge synthesis. The characteristics of users who shared problematic substance use–related communications on social media were reported by general group terms, such as adolescents, Twitter users, and Instagram users. All reviewed studies examined the communication characteristics, such as linguistic properties, and social networks of problematic drug use–related communications on social media. The mechanisms and predictors of such social media communications were not directly examined or empirically identified in the reviewed studies. The psychological or behavioral consequence (eg, increased behavioral intention for mimicking risky health behaviors) of engaging with and being exposed to social media communications regarding problematic drug use was another area of research that has been understudied. We offer theoretical applications, ethical considerations, and empirical evidence within the scope of social media communication and prescription drug abuse and addiction. Our critical review suggests that social media big data can be a tremendous resource to understand, monitor and intervene on drug abuse and addiction problems.
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