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...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:1f48419337014cd1920ccbd6454816f92021-11-18T07:29:05ZAssessment of Antipsychotic Medications on Social Media: Machine Learning Study1664-064010.3389/fpsyt.2021.737684https://doaj.org/article/1f48419337014cd1920ccbd6454816f92021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fpsyt.2021.737684/fullhttps://doaj.org/toc/1664-0640Background: 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.Miguel A. Alvarez-MonMiguel A. Alvarez-MonMiguel A. Alvarez-MonCarolina Donat-VargasCarolina Donat-VargasJavier Santoma-VilaclaraLaura de AntaJavier GoenaJavier GoenaRodrigo Sanchez-BayonaFernando MoraFernando MoraMiguel A. OrtegaMiguel A. OrtegaGuillermo LaheraGuillermo LaheraGuillermo LaheraGuillermo LaheraRoberto Rodriguez-JimenezRoberto Rodriguez-JimenezRoberto Rodriguez-JimenezJavier QuinteroJavier QuinteroMelchor Álvarez-MonMelchor Álvarez-MonMelchor Álvarez-MonFrontiers Media S.A.articlepsychosispsychiatryneuropsychopharmacologyantipsychoticsmachine learningartificial intelligencePsychiatryRC435-571ENFrontiers in Psychiatry, Vol 12 (2021) |
| institution |
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| collection |
DOAJ |
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EN |
| topic |
psychosis psychiatry neuropsychopharmacology antipsychotics machine learning artificial intelligence Psychiatry RC435-571 |
| spellingShingle |
psychosis psychiatry neuropsychopharmacology antipsychotics machine learning artificial intelligence Psychiatry RC435-571 Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Carolina Donat-Vargas Carolina Donat-Vargas Javier Santoma-Vilaclara Laura de Anta Javier Goena Javier Goena Rodrigo Sanchez-Bayona Fernando Mora Fernando Mora Miguel A. Ortega Miguel A. Ortega Guillermo Lahera Guillermo Lahera Guillermo Lahera Guillermo Lahera Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Javier Quintero Javier Quintero Melchor Álvarez-Mon Melchor Álvarez-Mon Melchor Álvarez-Mon Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
| 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 |
article |
| author |
Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Carolina Donat-Vargas Carolina Donat-Vargas Javier Santoma-Vilaclara Laura de Anta Javier Goena Javier Goena Rodrigo Sanchez-Bayona Fernando Mora Fernando Mora Miguel A. Ortega Miguel A. Ortega Guillermo Lahera Guillermo Lahera Guillermo Lahera Guillermo Lahera Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Javier Quintero Javier Quintero Melchor Álvarez-Mon Melchor Álvarez-Mon Melchor Álvarez-Mon |
| author_facet |
Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Miguel A. Alvarez-Mon Carolina Donat-Vargas Carolina Donat-Vargas Javier Santoma-Vilaclara Laura de Anta Javier Goena Javier Goena Rodrigo Sanchez-Bayona Fernando Mora Fernando Mora Miguel A. Ortega Miguel A. Ortega Guillermo Lahera Guillermo Lahera Guillermo Lahera Guillermo Lahera Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Roberto Rodriguez-Jimenez Javier Quintero Javier Quintero Melchor Álvarez-Mon Melchor Álvarez-Mon Melchor Álvarez-Mon |
| author_sort |
Miguel A. Alvarez-Mon |
| title |
Assessment of Antipsychotic Medications on Social Media: Machine Learning Study |
| title_short |
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_sort |
assessment of antipsychotic medications on social media: machine learning study |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/1f48419337014cd1920ccbd6454816f9 |
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