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Cited by 48Mental Health via WritingSchizophrenia research and treatmentImpact of Technology on Adolescents

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

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Hswen, Yulin, Naslund, John A., Brownstein, John S., Hawkins, Jared B.·2018·Psychiatric Quarterly
DOI 10.1007/s11126-017-9559-yPMC PMC6043409
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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.

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  • Twitter users with a self-disclosed diagnosis of schizophrenia more frequently discuss symptoms of depression and anxiety.

    “Several studies have also demonstrated that when compared to a control group, Twitter users with a self-disclosed diagnosis of schizophrenia show unique online communication patterns (Michael L Birnbaum, Ernala, Rizvi, De Choudhury, & Kane, 2017), including more frequent discussion of tobacco use (Hswen et al., 2017), symptoms of depression and anxiety (Hswen, Naslund, Brownstein, & Hawkins, 2018b”

    From Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice (2020) · cites this paper as Hswen, Naslund, Brownstein, & Hawkins, 2018b

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Authors
Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B.
Affiliations
  • Boston Children's Hospital (US)
  • Harvard University (US)
Corresponding author
Hswen, Yulin
ORCID
Venue
Psychiatric Quarterly
Publisher
Springer Science and Business Media LLC
Published
2018-01-12
Volume
89
Issue
3
Pages
569-580
ISSN
  • 0033-2720 (ISSN-L)
  • 1573-6709
DOI
10.1007/s11126-017-9559-y
PMC
PMC6043409
OpenAlex
W2784245106
Cited by
48
References
12
Citations by year
2026: 1 · 2025: 3 · 2024: 7 · 2023: 7 · 2022: 9 · 2021: 6 · 2020: 8 · 2019: 4 · 2018: 3
FWCI
7.11
Type
journal article
Language
en
Open access
Licence
Locations
  • Psychiatric Quarterly (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • Canadian Institutes of Health Research
  • U.S. National Library of Medicine (R01LM010812, T15LM007092)
  • Bill and Melinda Gates Foundation (OPP1093011)
Topics
  • Social Sciences › Psychology › Social Psychology › Mental Health via Writing
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
Keywords
schizophrenia, depression, anxiety, Twitter, social media, digital phenotypes, online communication, presenting symptoms, early illness detection, schizophrenia spectrum disorders
MeSH terms
Anxiety, Communication, Depression, Female, Humans, Male, Random Allocation, Schizophrenia, Schizophrenic Psychology, Time Factors, Statistics, Nonparametric, Social Media

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