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Psychiatr Q. 2018 Sep;89(3):569-580. doi: 10.1007/s11126-017-9559-y.

Online Communication about Depression and Anxiety among Twitter Users with Schizophrenia: Preliminary Findings to Inform a Digital Phenotype Using Social Media.

Author information

1
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA. yuh958@mail.harvard.edu.
2
Computational Epidemiology Group, Boston Children's Hospital, Boston, MA, USA. yuh958@mail.harvard.edu.
3
Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA.
4
Computational Epidemiology Group, Boston Children's Hospital, Boston, MA, USA.
5
Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
6
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Abstract

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.

KEYWORDS:

Anxiety; Depression; Digital phenotype; Mental health; Schizophrenia; Social media; Technology

PMID:
29327218
PMCID:
PMC6043409
[Available on 2019-09-01]
DOI:
10.1007/s11126-017-9559-y

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