This paper is in the following e-collection/theme issue:

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Participatory Medicine & E-Patients (773) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 18, No 3 (2016): March

Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research

Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research

Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research

Authors of this article:

Valéry Risson1 Author Orcid Image ;   Deepanshu Saini2 Author Orcid Image ;   Ian Bonzani3 Author Orcid Image ;   Alice Huisman1 Author Orcid Image ;   Melvin Olson1 Author Orcid Image
Article Authors Cited by (29) Tweetations (22) Metrics

Journals

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  15. Lavorgna L, Lanzillo R, Brescia Morra V, Abbadessa G, Tedeschi G, Bonavita S. Social Media and Multiple Sclerosis in the Posttruth Age. Interactive Journal of Medical Research 2017;6(2):e18 View
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  18. Kamiński M, Łoniewski I, Misera A, Marlicz W. Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. International Journal of Environmental Research and Public Health 2019;16(23):4591 View
  19. Belleudi V, Trotta F, Vecchi S, Amato L, Addis A, Davoli M. Studies on drug switchability showed heterogeneity in methodological approaches: a scoping review. Journal of Clinical Epidemiology 2018;101:5 View
  20. TOSYALI H, SÜTÇÜ C, TOSYALI F. Patient Loyalty in the HospitalPatient Relationship: The Mediating Role of Social Media. Erciyes İletişim Dergisi 2019;6(1):783 View
  21. Wise J, Möller A, Christie D, Kalra D, Brodsky E, Georgieva E, Jones G, Smith I, Greiffenberg L, McCarthy M, Arend M, Luttringer O, Kloss S, Arlington S. The positive impacts of Real-World Data on the challenges facing the evolution of biopharma. Drug Discovery Today 2018;23(4):788 View
  22. Qian Y, Zhang Y, He X, Xu S, Yang X, Mo C, Lu X, Qiu M, Xiao Q. Findings in Chinese Patients With Parkinson's Disease: A Content Analysis From the SML Study. Frontiers in Psychiatry 2021;12 View
  23. Walsh J, Cave J, Griffiths F. Spontaneously Generated Online Patient Experience of Modafinil: A Qualitative and NLP Analysis. Frontiers in Digital Health 2021;3 View
  24. Schmidt A, Rodriguez-Esteban R, Gottowik J, Leddin M. Applications of quantitative social media listening to patient-centric drug development. Drug Discovery Today 2022;27(5):1523 View
  25. Chauhan J, Aasaithambi S, Márquez-Rodas I, Formisano L, Papa S, Meyer N, Forschner A, Faust G, Lau M, Sagkriotis A. Understanding the Lived Experiences of Patients With Melanoma: Real-World Evidence Generated Through a European Social Media Listening Analysis. JMIR Cancer 2022;8(2):e35930 View
  26. Effenberger M, Kronbichler A, Bettac E, Grabherr F, Grander C, Adolph T, Mayer G, Zoller H, Perco P, Tilg H. Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis. Journal of Medical Internet Research 2021;23(8):e21656 View
  27. Leist T, Cole M, Verma S, Keenan A, Le H. A retrospective claims analysis of fatigue in patients with multiple sclerosis on disease-modifying therapy. Multiple Sclerosis and Related Disorders 2023;78:104917 View
  28. Sloesen B, O'Brien P, Verma H, Asaithambi S, Parashar N, Mothe R, Shaikh J, Syntosi A. Patient Experiences and Insights on Chronic Ocular Pain: Social Media Listening Study. JMIR Formative Research 2024;8:e47245 View
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