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Assessment of Antipsychotic Medications on Social Media: Machine Learning Study
Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8637121/ https://www.ncbi.nlm.nih.gov/pubmed/34867531 http://dx.doi.org/10.3389/fpsyt.2021.737684 |
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author | Alvarez-Mon, Miguel A. Donat-Vargas, Carolina Santoma-Vilaclara, Javier de Anta, Laura Goena, Javier Sanchez-Bayona, Rodrigo Mora, Fernando Ortega, Miguel A. Lahera, Guillermo Rodriguez-Jimenez, Roberto Quintero, Javier Álvarez-Mon, Melchor |
author_facet | Alvarez-Mon, Miguel A. Donat-Vargas, Carolina Santoma-Vilaclara, Javier de Anta, Laura Goena, Javier Sanchez-Bayona, Rodrigo Mora, Fernando Ortega, Miguel A. Lahera, Guillermo Rodriguez-Jimenez, Roberto Quintero, Javier Álvarez-Mon, Melchor |
author_sort | Alvarez-Mon, Miguel A. |
collection | PubMed |
description | Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment in this regard. Methods: We collected tweets containing mentions of antipsychotic medications posted between January 1st 2019 and October 31st 2020. The content of each tweet and the characteristics of the users were analyzed as well as the number of retweets and likes generated. Results: Twitter users, especially those identified as patients, showed an interest in antipsychotic medications, mainly focusing on the topics of sexual dysfunction and sedation. Interestingly, paliperidone, despite being among one of the newest antipsychotics, accounted for a low number of tweets and did not generate much interest. Conversely, retweet and like ratios were higher in those tweets asking for or offering help, in those posted by institutions and in those mentioning cognitive complaints. Moreover, health professionals did not have a strong presence in tweet postings, nor did medical institutions. Finally, trivialization was frequently observed. Conclusion: This analysis of tweets about antipsychotic medications provides insights into experiences and opinions related to this treatment. Twitter user perspectives therefore constitute a valuable input that may help to improve clinicians' knowledge of antipsychotic medications and their communication with patients regarding this treatment. |
format | Online Article Text |
id | pubmed-8637121 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86371212021-12-03 Assessment of Antipsychotic Medications on Social Media: Machine Learning Study Alvarez-Mon, Miguel A. Donat-Vargas, Carolina Santoma-Vilaclara, Javier de Anta, Laura Goena, Javier Sanchez-Bayona, Rodrigo Mora, Fernando Ortega, Miguel A. Lahera, Guillermo Rodriguez-Jimenez, Roberto Quintero, Javier Álvarez-Mon, Melchor Front Psychiatry Psychiatry Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment in this regard. Methods: We collected tweets containing mentions of antipsychotic medications posted between January 1st 2019 and October 31st 2020. The content of each tweet and the characteristics of the users were analyzed as well as the number of retweets and likes generated. Results: Twitter users, especially those identified as patients, showed an interest in antipsychotic medications, mainly focusing on the topics of sexual dysfunction and sedation. Interestingly, paliperidone, despite being among one of the newest antipsychotics, accounted for a low number of tweets and did not generate much interest. Conversely, retweet and like ratios were higher in those tweets asking for or offering help, in those posted by institutions and in those mentioning cognitive complaints. Moreover, health professionals did not have a strong presence in tweet postings, nor did medical institutions. Finally, trivialization was frequently observed. Conclusion: This analysis of tweets about antipsychotic medications provides insights into experiences and opinions related to this treatment. Twitter user perspectives therefore constitute a valuable input that may help to improve clinicians' knowledge of antipsychotic medications and their communication with patients regarding this treatment. Frontiers Media S.A. 2021-11-18 /pmc/articles/PMC8637121/ /pubmed/34867531 http://dx.doi.org/10.3389/fpsyt.2021.737684 Text en Copyright © 2021 Alvarez-Mon, Donat-Vargas, Santoma-Vilaclara, Anta, Goena, Sanchez-Bayona, Mora, Ortega, Lahera, Rodriguez-Jimenez, Quintero and Álvarez-Mon. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Alvarez-Mon, Miguel A. Donat-Vargas, Carolina Santoma-Vilaclara, Javier de Anta, Laura Goena, Javier Sanchez-Bayona, Rodrigo Mora, Fernando Ortega, Miguel A. Lahera, Guillermo Rodriguez-Jimenez, Roberto Quintero, Javier Álvarez-Mon, Melchor Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title | Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title_full | Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title_fullStr | Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title_full_unstemmed | Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title_short | Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
title_sort | assessment of antipsychotic medications on social media: machine learning study |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8637121/ https://www.ncbi.nlm.nih.gov/pubmed/34867531 http://dx.doi.org/10.3389/fpsyt.2021.737684 |
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