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Chart-Pascual JP, Montero-Torres M, Ortega MA, Mar-Barrutia L, Zorrilla Martinez I, Alvarez-Mon M, Gonzalez-Pinto A, Alvarez-Mon MA. Areas of interest and sentiment analysis towards second generation antipsychotics, lithium and mood stabilizing anticonvulsants: Unsupervised analysis using Twitter. J Affect Disord 2024; 351:649-660. [PMID: 38290587 DOI: 10.1016/j.jad.2024.01.234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/01/2024]
Abstract
BACKGROUND Severe mental disorders like Schizophrenia and related psychotic disorders (SRD) or Bipolar Disorder (BD) require pharmacological treatment for relapse prevention and quality of life improvement. Yet, treatment adherence is a challenge, partly due to patients' attitudes and beliefs towards their medication. Social media listening offers insights into patient experiences and preferences, particularly in severe mental disorders. METHODS All tweets posted between 2008 and 2022 mentioning the names of the main drugs used in SRD and BD were analyzed using advanced artificial intelligence techniques such as machine learning, and deep learning, along with natural language processing. RESULTS In this 15-year study analyzing 893,289 tweets, second generation antipsychotics received more mentions in English tweets, whereas mood stabilizers received more tweets in Spanish. English tweets about economic and legal aspects displayed negative emotions, while Spanish tweets seeking advice showed surprise. Moreover, a recurring theme in Spanish tweets was the shortage of medications, evoking feelings of anger among users. LIMITATIONS This study's analysis of Twitter data, while insightful, may not fully capture the nuances of discussions due to the platform's brevity. Additionally, the wide therapeutic use of the studied drugs, complicates the isolation of disorder-specific discourse. Only English and Spanish tweets were examined, limiting the cultural breadth of the findings. CONCLUSION This study emphasizes the importance of social media research in understanding user perceptions of SRD and BD treatments. The results provide valuable insights for clinicians when considering how patients and the general public view and communicate about these treatments in the digital environment.
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Affiliation(s)
- Juan Pablo Chart-Pascual
- Psychiatry Department, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain; Bioaraba Health Research Institute, Vitoria-Gasteiz, Spain; CIBERSAM.
| | - Maria Montero-Torres
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain; Department of Medicine and Medical Specialities, University of Alcala, 28801 Alcala de Henares, Madrid, Spain
| | - Miguel Angel Ortega
- Cancer Registry and Pathology Department, Hospital Universitario Príncipe de Asturias, Alcalá de Henares, Spain; Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain; Department of Medicine and Medical Specialities, University of Alcala, 28801 Alcala de Henares, Madrid, Spain
| | - Lorea Mar-Barrutia
- Psychiatry Department, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; Bioaraba Health Research Institute, Vitoria-Gasteiz, Spain; CIBERSAM
| | - Iñaki Zorrilla Martinez
- Psychiatry Department, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain; Bioaraba Health Research Institute, Vitoria-Gasteiz, Spain; CIBERSAM
| | - Melchor Alvarez-Mon
- Immune System Diseases-Rheumatology and Internal Medicine Service, Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas, University Hospital Príncipe de Asturias, Alcala de Henares, Spain; Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain; Department of Medicine and Medical Specialities, University of Alcala, 28801 Alcala de Henares, Madrid, Spain
| | - Ana Gonzalez-Pinto
- Psychiatry Department, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain; Bioaraba Health Research Institute, Vitoria-Gasteiz, Spain; CIBERSAM
| | - Miguel Angel Alvarez-Mon
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain; Department of Medicine and Medical Specialities, University of Alcala, 28801 Alcala de Henares, Madrid, Spain; Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
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2
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Cimiano P, Collins B, De Vuono MC, Escudier T, Gottowik J, Hartung M, Leddin M, Neupane B, Rodriguez-Esteban R, Schmidt AL, Starke-Knäusel C, Voorhaar M, Wieckowski K. Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators. Front Med (Lausanne) 2024; 11:1274688. [PMID: 38515987 PMCID: PMC10955474 DOI: 10.3389/fmed.2024.1274688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 02/12/2024] [Indexed: 03/23/2024] Open
Abstract
Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.
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Affiliation(s)
- Philipp Cimiano
- Semalytix GmbH, Bielefeld, Germany
- CITEC, Bielefeld University, Bielefeld, Germany
| | - Ben Collins
- Boehringer Ingelheim International GmbH, Ingelheim, Germany
| | | | | | - Jürgen Gottowik
- Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | | | - Mathias Leddin
- Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Bikalpa Neupane
- Takeda Pharmaceuticals Co., Ltd., Cambridge, MA, United States
| | | | - Ana Lucia Schmidt
- Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
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Mantri S, Purks JL, Kinel D, Arbatti L, Hosamath A, Allen A, Amara A, Anderson K, Chahine LM, Eberly S, Mathur S, Standaert D, Oakes D, Weintraub D, Shoulson I, Marras C. In Their Own Words: Fears Expressed by People with Parkinson's Disease in an Online Symptom Database. JOURNAL OF PARKINSON'S DISEASE 2024; 14:865-872. [PMID: 38669556 PMCID: PMC11191490 DOI: 10.3233/jpd-230305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/18/2024] [Indexed: 04/28/2024]
Abstract
Parkinson's disease (PD) carries substantial psychosocial burden. Using a database of responses by people with PD reporting up to five "most bothersome problems," we identified 225 fear-based verbatims, which were organized using the framework method into 26 categories. Commonly-reported fears included uncertainty of progression (n = 60, 26.7%), fear of future cognitive impairment (n = 24, 10.7%) and fear of becoming a burden on others (n = 23, 10.2%). Fears in PD are wide-ranging and can constitute the most bothersome aspect of the condition. These data can be used to design interventions to lessen the psychosocial burden of PD.
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Affiliation(s)
- Sneha Mantri
- Department of Neurology, Duke University, Durham, NC, USA
| | - Jennifer L. Purks
- Department of Neurology, University of Rochester, Rochester, NY, USA
| | - Daniel Kinel
- Department of Neurology, Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Lakshmi Arbatti
- Grey Matter Technologies, A Wholly Owned Subsidiary of Modality.ai, San Francisco, CA, USA
| | - Abhishek Hosamath
- Grey Matter Technologies, A Wholly Owned Subsidiary of Modality.ai, San Francisco, CA, USA
| | - Allison Allen
- Department of Neurology, Duke University, Durham, NC, USA
| | - Amy Amara
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Karen Anderson
- Department of Psychiatry and Department of Neurology, Georgetown University, Washington, DC, USA
| | - Lana M. Chahine
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shirley Eberly
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA
| | | | - David Standaert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - David Oakes
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA
| | - Daniel Weintraub
- Departments of Psychiatry and Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ira Shoulson
- Department of Neurology, University of Rochester, Rochester, NY, USA
- Grey Matter Technologies, A Wholly Owned Subsidiary of Modality.ai, San Francisco, CA, USA
| | - Connie Marras
- Edmond J. Safra Program in Parkinson’s Disease, University Health Network, University of Toronto, Toronto, Canada
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4
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Byrom B, Bessant C, Smeraldi F, Abdollahyan M, Bridges Y, Chowdhury M, Tahsin A. Deriving Meaningful Aspects of Health Related to Physical Activity in Chronic Disease: Concept Elicitation Using Machine Learning-Assisted Coding of Online Patient Conversations. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2023; 26:1057-1066. [PMID: 36804528 DOI: 10.1016/j.jval.2023.01.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 12/29/2022] [Accepted: 01/30/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES Clinical outcome assessment (COA) developers must ensure that measures assess aspects of health that are meaningful to the target patient population. Although the methodology for doing this is well understood for certain COAs, such as patient-reported outcome measures, there are fewer examples of this practice in the development of digital endpoints using mobile sensor technology such as physical activity monitors. This study explored the utility of social media data, specifically, posts on online health boards, in understanding meaningful aspects of health related to physical activity in 3 different chronic diseases: fibromyalgia, chronic obstructive pulmonary disease, and chronic heart failure. METHODS We used machine learning and manual coding to summarize the content of posts extracted from 4 online health boards. Where available, patient age and sex were retrieved from post content or user profiles. We utilized analytical approaches to assess the robustness of findings to differences in the characteristics of online samples compared to the true patient population. Finally, we assessed concept saturation by measuring the convergence of autocorrelations. RESULTS We identify a number of aspects of health described as important by patients in our samples, and summarize these into concepts for measurement. For chronic heart failure, these included purposeful walking duration and speed, fatigue, difficulty going upstairs, standing, and aspects of physical exercise. Overall and age-adjusted results did not differ considerably for each disease group. CONCLUSIONS This study illustrates the potential of performing concept elicitation research using social media data, which may provide valuable insight to inform COA development.
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Affiliation(s)
- Bill Byrom
- Independent Researcher, Nottingham, England, UK
| | - Conrad Bessant
- Queen Mary University of London, London, England, UK; Mebomine Ltd, Pioneer House, Vision Park, Histon, Cambridge, England, UK.
| | - Fabrizio Smeraldi
- Queen Mary University of London, London, England, UK; Mebomine Ltd, Pioneer House, Vision Park, Histon, Cambridge, England, UK
| | - Maryam Abdollahyan
- Queen Mary University of London, London, England, UK; Mebomine Ltd, Pioneer House, Vision Park, Histon, Cambridge, England, UK
| | | | | | - Asiyya Tahsin
- Queen Mary University of London, London, England, UK
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5
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de Anta L, Alvarez-Mon MA, Ortega MA, Salazar C, Donat-Vargas C, Santoma-Vilaclara J, Martin-Martinez M, Lahera G, Gutierrez-Rojas L, Rodriguez-Jimenez R, Quintero J, Alvarez-Mon M. Areas of Interest and Social Consideration of Antidepressants on English Tweets: A Natural Language Processing Classification Study. J Pers Med 2022; 12:jpm12020155. [PMID: 35207644 PMCID: PMC8879287 DOI: 10.3390/jpm12020155] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/11/2022] [Accepted: 01/18/2022] [Indexed: 01/11/2023] Open
Abstract
Background: Antidepressants are the foundation of the treatment of major depressive disorders. Despite the scientific evidence, there is still a sustained debate and concern about the efficacy of antidepressants, with widely differing opinions among the population about their positive and negative effects, which may condition people’s attitudes towards such treatments. Our aim is to investigate Twitter posts about antidepressants in order to have a better understanding of the social consideration of antidepressants. Methods: We gathered public tweets mentioning antidepressants written in English, published throughout a 22-month period, between 1 January 2019 and 31 October 2020. We analysed the content of each tweet, determining in the first place whether they included medical aspects or not. Those with medical content were classified into four categories: general aspects, such as quality of life or mood, sleep-related conditions, appetite/weight issues and aspects around somatic alterations. In non-medical tweets, we distinguished three categories: commercial nature (including all economic activity, drug promotion, education or outreach), help request/offer, and drug trivialization. In addition, users were arranged into three categories according to their nature: patients and relatives, caregivers, and interactions between Twitter users. Finally, we identified the most mentioned antidepressants, including the number of retweets and likes, which allowed us to measure the impact among Twitter users. Results: The activity in Twitter concerning antidepressants is mainly focused on the effects these drugs may have on certain health-related areas, specifically sleep (20.87%) and appetite/weight (8.95%). Patients and relatives are the type of user that most frequently posts tweets with medical content (65.2%, specifically 80% when referencing sleep and 78.6% in the case of appetite/weight), whereas they are responsible for only 2.9% of tweets with non-medical content. Among tweets classified as non-medical in this study, the most common subject was drug trivialization (66.86%). Caregivers barely have any presence in conversations in Twitter about antidepressants (3.5%). However, their tweets rose more interest among other users, with a ratio 11.93 times higher than those posted by patients and their friends and family. Mirtazapine is the most mentioned antidepressant in Twitter (45.43%), with a significant difference with the rest, agomelatine (11.11%). Conclusions: This study shows that Twitter users that take antidepressants, or their friends and family, use social media to share medical information about antidepressants. However, other users that do not talk about antidepressants from a personal or close experience, frequently do so in a stigmatizing manner, by trivializing them. Our study also brings to light the scarce presence of caregivers in Twitter.
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Affiliation(s)
- Laura de Anta
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, 28031 Madrid, Spain; (L.d.A.); (M.M.-M.); (J.Q.)
| | - Miguel Angel Alvarez-Mon
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, 28031 Madrid, Spain; (L.d.A.); (M.M.-M.); (J.Q.)
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain; (G.L.); (M.A.-M.)
- Correspondence: (M.A.A.-M.); (M.A.O.)
| | - Miguel A. Ortega
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain; (G.L.); (M.A.-M.)
- Ramón y Cajal Health Research Institute (IRYCIS), 28034 Madrid, Spain
- Correspondence: (M.A.A.-M.); (M.A.O.)
| | - Cristina Salazar
- Departamento Teoría de la Señal y Comunicaciones y Sistemas Telemáticos y Computación, Escuela Técnica Superior de Ingeniería de Telecomunicación, Universidad Rey Juan Carlos, 28942 Fuenlabrada, Spain;
| | - Carolina Donat-Vargas
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine (IMM), Karolinska Institute, 171 77 Stockholm, Sweden;
| | | | - Maria Martin-Martinez
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, 28031 Madrid, Spain; (L.d.A.); (M.M.-M.); (J.Q.)
| | - Guillermo Lahera
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain; (G.L.); (M.A.-M.)
- Ramón y Cajal Health Research Institute (IRYCIS), 28034 Madrid, Spain
- CIBERSAM (Biomedical Research Networking Centre in Mental Health), 22807 Madrid, Spain;
- Psychiatry Service, Príncipe de Asturias University Hospital, 28805 Alcalá de Henares, Spain
| | | | - Roberto Rodriguez-Jimenez
- CIBERSAM (Biomedical Research Networking Centre in Mental Health), 22807 Madrid, Spain;
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas 12), Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain
| | - Javier Quintero
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, 28031 Madrid, Spain; (L.d.A.); (M.M.-M.); (J.Q.)
| | - Melchor Alvarez-Mon
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain; (G.L.); (M.A.-M.)
- Ramón y Cajal Health Research Institute (IRYCIS), 28034 Madrid, Spain
- Immune System Diseases-Rheumatology and Oncology Service, University Hospital Príncipe de Asturias, CIBEREHD, 28805 Alcalá de Henares, Spain
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Takeuchi H, Mori Y, Tsutsumi Y. Pathophysiology, prognosis and treatment of tardive dyskinesia. Ther Adv Psychopharmacol 2022; 12:20451253221117313. [PMID: 36312846 PMCID: PMC9597038 DOI: 10.1177/20451253221117313] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/15/2022] [Indexed: 11/06/2022] Open
Abstract
UNLABELLED Tardive dyskinesia (TD), a movement disorder associated with antipsychotics, most frequently affects the lower face and jaw muscles, but can also affect walking, breathing and use of the hands and limbs. Knowledge of TD among physicians may be limited, and the pathophysiology of TD is poorly understood. We conducted this review to summarise the current knowledge surrounding the pathophysiology of TD and present recommendations for prevention and treatment based on a literature search and roundtable discussion attended by psychiatrists in Japan. It has been suggested that dopamine hypersensitivity, damaged gamma-aminobutyric acidergic neurons and/or increased production of reactive oxygen species may contribute to development of TD. Symptoms can profoundly affect everyday life; patients who develop TD have poorer prognoses, worse health-related quality of life, greater social withdrawal and higher mortality than patients without TD. Traditional treatment options include dietary supplements, although evidence for their effectiveness is low. Among pharmaceutical interventions, there is moderate evidence that switching to the second-generation antipsychotic clozapine, which has a lower affinity for dopamine D2 receptors than other antipsychotics, may improve symptoms. Vesicular monoamine transporter 2 (VMAT-2) inhibitors, which oppose the increased dopaminergic activity associated with prolonged antipsychotic use by interfering with dopamine uptake and storage, have the strongest evidence for efficacy. VMAT-2 inhibitors are approved in the United States for the treatment of TD, and the first VMAT-2 inhibitor was approved in Japan for this indication in March 2022. Most guidelines recommend treating TD by first reducing the dose of antipsychotics or switching to clozapine or other second-generation antipsychotics, which have a lower association with TD than first-generation antipsychotics. We recommend focusing on prevention and monitoring for TD when prescribing antipsychotics, given that TD is often irreversible. Physicians should treat with antipsychotics only when necessary and at the lowest effective dose, and frequently monitor for TD symptoms. PLAIN LANGUAGE SUMMARY Plain Language Summary (In Japanese). VISUAL SUMMARY Visual Summary (In Japanese).
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Affiliation(s)
- Hiroyoshi Takeuchi
- Department of Neuropsychiatry, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Yasuhiro Mori
- Department of Psychiatry, Aichi Medical University, Aichi, Japan
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Alvarez-Mon MA, Donat-Vargas C, Santoma-Vilaclara J, de Anta L, Goena J, Sanchez-Bayona R, Mora F, Ortega MA, Lahera G, Rodriguez-Jimenez R, Quintero J, Álvarez-Mon M. Assessment of Antipsychotic Medications on Social Media: Machine Learning Study. Front Psychiatry 2021; 12:737684. [PMID: 34867531 PMCID: PMC8637121 DOI: 10.3389/fpsyt.2021.737684] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 10/19/2021] [Indexed: 12/21/2022] Open
Abstract
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.
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Affiliation(s)
- Miguel A Alvarez-Mon
- Department of Medicine and Medical Specialities, University of Alcala, Alcala de Henares, Spain.,Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain.,Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Carolina Donat-Vargas
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.,IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | | | - Laura de Anta
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Javier Goena
- Department of Psychiatry and Clinical Psychology, University of Navarra Clinic, Pamplona, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Rodrigo Sanchez-Bayona
- Hospital Universitario 12 de Octubre, Unidad de Cáncer de Mama y Ginecológico, Madrid, Spain
| | - Fernando Mora
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain.,Department of Legal and Psychiatry, Complutense University, Madrid, Spain
| | - Miguel A Ortega
- Department of Medicine and Medical Specialities, University of Alcala, Alcala de Henares, Spain.,Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Guillermo Lahera
- Department of Medicine and Medical Specialities, University of Alcala, Alcala de Henares, Spain.,Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain.,Department of Psychiatry, University Hospital Principe de Asturias, Alcalá de Henares, Spain.,CIBERSAM (Biomedical Research Networking Centre in Mental Health), Madrid, Spain
| | - Roberto Rodriguez-Jimenez
- CIBERSAM (Biomedical Research Networking Centre in Mental Health), Madrid, Spain.,Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas 12), Madrid, Spain.,Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Javier Quintero
- Department of Psychiatry and Mental Health, Hospital Universitario Infanta Leonor, Madrid, Spain.,Department of Legal and Psychiatry, Complutense University, Madrid, Spain
| | - Melchor Álvarez-Mon
- Department of Medicine and Medical Specialities, University of Alcala, Alcala de Henares, Spain.,Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain.,Service of Internal Medicine and Immune System Diseases-Rheumatology, University Hospital Príncipe de Asturias (CIBEREHD), Alcalá de Henares, Spain
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