Cataloguing Treatments Discussed and Used in Online Autism Communities.
Cataloguing Treatments Discussed and Used in Online Autism Communities.
复制标题
对在线自闭症社区讨论和使用的治疗方法进行编目。
DOI：
10.1145/3038912.3052661
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Elhadad,Noémie
中科院分区：
文献类型：
--
作者：
Zhang,Shaodian;Kang,Tian;Qiu,Lin;Zhang,Weinan;Yu,Yong;Elhadad,Noémie
大量患者在在线健康社区（OHC）中讨论治疗。健康研究人员感兴趣的一个研究问题是，在OHC中讨论的治疗方法最终是否会被社区成员在他们的真实的生活中使用。在本文中，我们依靠机器学习方法来自动识别来自在线自闭症社区的治疗提及的归因。我们的工作背景是在线自闭症社区，在那里，父母交换对自闭症谱系障碍儿童的护理支持。我们的方法能够区分与患者，护理人员和其他人相关的治疗讨论，以及确定是否实际采取治疗。我们调查的治疗，不仅讨论，但也使用的患者根据两种类型的内容分析，横截面和纵向。通过我们的内容分析确定的治疗方法有助于创建一个真实世界治疗方法的目录。这项研究结果为未来的研究奠定了基础，以比较现实世界的药物使用与既定的临床指南。
A large number of patients discuss treatments in online health communities (OHCs). One research question of interest to health researchers is whether treatments being discussed in OHCs are eventually used by community members in their real lives. In this paper, we rely on machine learning methods to automatically identify attributions of mentions of treatments from an online autism community. The context of our work is online autism communities, where parents exchange support for the care of their children with autism spectrum disorder. Our methods are able to distinguish discussions of treatments that are associated with patients, caregivers, and others, as well as identify whether a treatment is actually taken. We investigate treatments that are not just discussed but also used by patients according to two types of content analysis, cross-sectional and longitudinal. The treatments identified through our content analysis help create a catalogue of real-world treatments. This study results lay the foundation for future research to compare real-world drug usage with established clinical guidelines.