Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.
Computational Epidemiology Group, Boston Children's Hospital, Boston, MA, USA.
Psychiatr Q. 2018 Sep;89(3):569-580. doi: 10.1007/s11126-017-9559-y.
Digital technologies hold promise for supporting the detection and management of schizophrenia. This exploratory study aimed to generate an initial understanding of whether patterns of communication about depression and anxiety on popular social media among individuals with schizophrenia are consistent with offline representations of the illness. From January to July 2016, posts on Twitter were collected from a sample of Twitter users who self-identify as having a schizophrenia spectrum disorder (n = 203) and a randomly selected sample of control users (n = 173). Frequency and timing of communication about depression and anxiety were compared between groups. In total, the groups posted n = 1,544,122 tweets and users had similar characteristics. Twitter users with schizophrenia showed significantly greater odds of tweeting about depression compared with control users (OR = 2.69; 95% CI 1.76-4.10), and significantly greater odds of tweeting about anxiety compared with control users (OR = 1.81; 95% CI 1.20-2.73). This study offers preliminary insights that Twitter users with schizophrenia may express elevated symptoms of depression and anxiety in their online posts, which is consistent with clinical characteristics of schizophrenia observed in offline settings. Social media platforms could further our understanding of schizophrenia by informing a digital phenotype and may afford new opportunities to support early illness detection.
数字技术有望支持精神分裂症的检测和管理。这项探索性研究旨在初步了解精神分裂症患者在社交媒体上发布的关于抑郁和焦虑的信息模式是否与线下对该疾病的描述一致。2016 年 1 月至 7 月,从自我诊断为精神分裂症谱系障碍的 Twitter 用户样本(n=203)和随机选择的对照用户样本(n=173)中收集了 Twitter 上的帖子。比较了两组人群关于抑郁和焦虑的沟通频率和时间。总共有两组共发布了 n=1544122 条推文,用户具有相似的特征。与对照组相比,精神分裂症患者在 Twitter 上发布抑郁相关内容的几率明显更高(OR=2.69;95%CI 1.76-4.10),发布焦虑相关内容的几率也明显更高(OR=1.81;95%CI 1.20-2.73)。这项研究提供了初步的见解,即精神分裂症患者在他们的在线帖子中可能表达了更高水平的抑郁和焦虑症状,这与线下观察到的精神分裂症的临床特征一致。社交媒体平台可以通过提供数字表型进一步加深我们对精神分裂症的了解,并为支持早期疾病检测提供新的机会。