Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study

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• dc.contributor.author Leis Machín, Angela 1974-
• dc.contributor.author Ronzano, Francesco
• dc.contributor.author Mayer, Miguel Ángel, 1960-
• dc.contributor.author Furlong, Laura I., 1971-
• dc.contributor.author Sanz, Ferran
• dc.date.accessioned 2021-01-13T07:14:39Z
• dc.date.available 2021-01-13T07:14:39Z
• dc.date.issued 2020
• dc.description.abstract Background: Depressive disorders are the most common mental illnesses, and they constitute the leading cause of disability worldwide. Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed drugs for the treatment of depressive disorders. Some people share information about their experiences with antidepressants on social media platforms such as Twitter. Analysis of the messages posted by Twitter users under SSRI treatment can yield useful information on how these antidepressants affect users' behavior. Objective: This study aims to compare the behavioral and linguistic characteristics of the tweets posted while users were likely to be under SSRI treatment, in comparison to the tweets posted by the same users when they were less likely to be taking this medication. Methods: In the first step, the timelines of Twitter users mentioning SSRI antidepressants in their tweets were selected using a list of 128 generic and brand names of SSRIs. In the second step, two datasets of tweets were created, the in-treatment dataset (made up of the tweets posted throughout the 30 days after mentioning an SSRI) and the unknown-treatment dataset (made up of tweets posted more than 90 days before or more than 90 days after any tweet mentioning an SSRI). For each user, the changes in behavioral and linguistic features between the tweets classified in these two datasets were analyzed. 186 users and their timelines with 668,842 tweets were finally included in the study. Results: The number of tweets generated per day by the users when they were in treatment was higher than it was when they were in the unknown-treatment period (P=.001). When the users were in treatment, the mean percentage of tweets posted during the daytime (from 8 AM to midnight) increased in comparison to the unknown-treatment period (P=.002). The number of characters and words per tweet was higher when the users were in treatment (P=.03 and P=.02, respectively). Regarding linguistic features, the percentage of pronouns that were first-person singular was higher when users were in treatment (P=.008). Conclusions: Behavioral and linguistic changes have been detected when users with depression are taking antidepressant medication. These features can provide interesting insights for monitoring the evolution of this disease, as well as offering additional information related to treatment adherence. This information may be especially useful in patients who are receiving long-term treatments such as people suffering from depression.
• dc.description.sponsorship We received support from the Agency for Management of University and Research Grants in Catalonia (Spain) for the incorporation of new research personnel (FI2016) and from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement number 802750 (FAIRplus) with the support of the European Union’s Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations Companies.
• dc.format.mimetype application/pdf
• dc.identifier.citation Leis A, Ronzano F, Mayer MA, Furlong LI, Sanz F. Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study. J Med Internet Res. 2020; 22(12):e20920. DOI: 10.2196/20920
• dc.identifier.doi http://dx.doi.org/10.2196/20920
• dc.identifier.issn 1439-4456
• dc.identifier.uri http://hdl.handle.net/10230/46152
• dc.language.iso eng
• dc.publisher JMIR Publications
• dc.relation.ispartof J Med Internet Res. 2020; 22(12):e20920
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/802750
• dc.rights © Angela Leis, Francesco Ronzano, Miguel Angel Mayer, Laura I Furlong, Ferran Sanz. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.12.2020. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Antidepressant drugs
• dc.subject.keyword Data mining
• dc.subject.keyword Depression
• dc.subject.keyword Infodemiology
• dc.subject.keyword Mental health
• dc.subject.keyword Serotonin uptake inhibitors
• dc.subject.keyword Social media
• dc.title Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion