A social media study on the effects of psychiatric medication use

Koustuv Saha, Benjamin Sugar, John Torous, Bruno Abrahao, Emre Kıcıman, Munmun De Choudhury

    Research output: Contribution to conferencePaperpeer-review

    Abstract

    Understanding the effects of psychiatric medications during mental health treatment constitutes an active area of inquiry. While clinical trials help evaluate the effects of these medications, many trials suffer from a lack of generalizability to broader populations. We leverage social media data to examine psychopathological effects subject to self-reported usage of psychiatric medication. Using a list of common approved and regulated psychiatric drugs and a Twitter dataset of 300M posts from 30K individuals, we develop machine learning models to first assess effects relating to mood, cognition, depression, anxiety, psychosis, and suicidal ideation. Then, based on a stratified propensity score based causal analysis, we observe that use of specific drugs are associated with characteristic changes in an individual’s psychopathology. We situate these observations in the psychiatry literature, with a deeper analysis of pre-treatment cues that predict treatment outcomes. Our work bears potential to inspire novel clinical investigations and to build tools for digital therapeutics.

    Original languageEnglish (US)
    Pages440-451
    Number of pages12
    StatePublished - 2019
    Event13th International Conference on Web and Social Media, ICWSM 2019 - Munich, Germany
    Duration: Jun 11 2019Jun 14 2019

    Conference

    Conference13th International Conference on Web and Social Media, ICWSM 2019
    CountryGermany
    CityMunich
    Period6/11/196/14/19

    ASJC Scopus subject areas

    • Computer Networks and Communications

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