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Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data
BACKGROUND: Antidepressants are known to show heterogeneous effects across individuals and conditions, posing challenges to understanding their efficacy in mental health treatment. Social media platforms enable individuals to share their day-to-day concerns with others and thereby can function as un...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8077932/ https://www.ncbi.nlm.nih.gov/pubmed/33739296 http://dx.doi.org/10.2196/26589 |
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author | Saha, Koustuv Torous, John Kiciman, Emre De Choudhury, Munmun |
author_facet | Saha, Koustuv Torous, John Kiciman, Emre De Choudhury, Munmun |
author_sort | Saha, Koustuv |
collection | PubMed |
description | BACKGROUND: Antidepressants are known to show heterogeneous effects across individuals and conditions, posing challenges to understanding their efficacy in mental health treatment. Social media platforms enable individuals to share their day-to-day concerns with others and thereby can function as unobtrusive, large-scale, and naturalistic data sources to study the longitudinal behavior of individuals taking antidepressants. OBJECTIVE: We aim to understand the side effects of antidepressants from naturalistic expressions of individuals on social media. METHODS: On a large-scale Twitter data set of individuals who self-reported using antidepressants, a quasi-experimental study using unsupervised language analysis was conducted to extract keywords that distinguish individuals who improved and who did not improve following the use of antidepressants. The net data set consists of over 8 million Twitter posts made by over 300,000 users in a 4-year period between January 1, 2014, and February 15, 2018. RESULTS: Five major side effects of antidepressants were studied: sleep, weight, eating, pain, and sexual issues. Social media language revealed keywords related to these side effects. In particular, antidepressants were found to show a spectrum of effects from decrease to increase in each of these side effects. CONCLUSIONS: This work enhances the understanding of the side effects of antidepressants by identifying distinct linguistic markers in the longitudinal social media data of individuals showing the most and least improvement following the self-reported intake of antidepressants. One implication of this work concerns the potential of social media data as an effective means to support digital pharmacovigilance and digital therapeutics. These results can inform clinicians in tailoring their discussion and assessment of side effects and inform patients about what to potentially expect and what may or may not be within the realm of normal aftereffects of antidepressants. |
format | Online Article Text |
id | pubmed-8077932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-80779322021-05-06 Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data Saha, Koustuv Torous, John Kiciman, Emre De Choudhury, Munmun JMIR Ment Health Short Paper BACKGROUND: Antidepressants are known to show heterogeneous effects across individuals and conditions, posing challenges to understanding their efficacy in mental health treatment. Social media platforms enable individuals to share their day-to-day concerns with others and thereby can function as unobtrusive, large-scale, and naturalistic data sources to study the longitudinal behavior of individuals taking antidepressants. OBJECTIVE: We aim to understand the side effects of antidepressants from naturalistic expressions of individuals on social media. METHODS: On a large-scale Twitter data set of individuals who self-reported using antidepressants, a quasi-experimental study using unsupervised language analysis was conducted to extract keywords that distinguish individuals who improved and who did not improve following the use of antidepressants. The net data set consists of over 8 million Twitter posts made by over 300,000 users in a 4-year period between January 1, 2014, and February 15, 2018. RESULTS: Five major side effects of antidepressants were studied: sleep, weight, eating, pain, and sexual issues. Social media language revealed keywords related to these side effects. In particular, antidepressants were found to show a spectrum of effects from decrease to increase in each of these side effects. CONCLUSIONS: This work enhances the understanding of the side effects of antidepressants by identifying distinct linguistic markers in the longitudinal social media data of individuals showing the most and least improvement following the self-reported intake of antidepressants. One implication of this work concerns the potential of social media data as an effective means to support digital pharmacovigilance and digital therapeutics. These results can inform clinicians in tailoring their discussion and assessment of side effects and inform patients about what to potentially expect and what may or may not be within the realm of normal aftereffects of antidepressants. JMIR Publications 2021-03-19 /pmc/articles/PMC8077932/ /pubmed/33739296 http://dx.doi.org/10.2196/26589 Text en ©Koustuv Saha, John Torous, Emre Kiciman, Munmun De Choudhury. Originally published in JMIR Mental Health (http://mental.jmir.org), 19.03.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Short Paper Saha, Koustuv Torous, John Kiciman, Emre De Choudhury, Munmun Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title | Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title_full | Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title_fullStr | Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title_full_unstemmed | Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title_short | Understanding Side Effects of Antidepressants: Large-scale Longitudinal Study on Social Media Data |
title_sort | understanding side effects of antidepressants: large-scale longitudinal study on social media data |
topic | Short Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8077932/ https://www.ncbi.nlm.nih.gov/pubmed/33739296 http://dx.doi.org/10.2196/26589 |
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