Proceedings:
Vol. 13 (2019): Thirteenth International AAAI Conference on Web and Social Media
Volume
Issue:
Vol. 13 (2019): Thirteenth International AAAI Conference on Web and Social Media
Track:
Full Papers
Downloads:
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.
DOI:
10.1609/icwsm.v13i01.3242
ICWSM
Vol. 13 (2019): Thirteenth International AAAI Conference on Web and Social Media