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

Reviews on Innovations in Cancer (31) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Pharmacovigilance (134)

Published on in Vol 4, No 1 (2018): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/7952, first published .
Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology

Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology

Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology

Authors of this article:

Rachel R.J. Kalf1 Author Orcid Image ;   Amr Makady1, 2 Author Orcid Image ;   Renske M.T. ten Ham1, 2 Author Orcid Image ;   Kim Meijboom1, 3 Author Orcid Image ;   Wim G. Goettsch1, 2 Author Orcid Image ;   On Behalf Of IMI-GetReal Workpackage 14
Article Authors Cited by (13) Tweetations (11) Metrics

Journals

  1. McDonald L, Behl V, Sundar V, Mehmud F, Malcolm B, Ramagopalan S. Validity of social media for assessing treatment patterns in oncology patients: a case study in melanoma. JAMIA Open 2019;2(4):416 View
  2. Makady A, Kalf R, Ryll B, Spurrier G, de Boer A, Hillege H, Klungel O, Goettsch W. Social media as a tool for assessing patient perspectives on quality of life in metastatic melanoma: a feasibility study. Health and Quality of Life Outcomes 2018;16(1) View
  3. Pulini A, Caetano G, Clautiaux H, Vergeron L, Pitts P, Katz G. Impact of Real-World Data on Market Authorization, Reimbursement Decision & Price Negotiation. Therapeutic Innovation & Regulatory Science 2021;55(1):228 View
  4. Ricard B, Marsch L, Crosier B, Hassanpour S. Exploring the Utility of Community-Generated Social Media Content for Detecting Depression: An Analytical Study on Instagram. Journal of Medical Internet Research 2018;20(12):e11817 View
  5. Moes F, Houwaart E, Delnoij D, Horstman K. Questions regarding ‘epistemic injustice’ in knowledge-intensive policymaking: Two examples from Dutch health insurance policy. Social Science & Medicine 2020;245:112674 View
  6. 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
  7. Kleinhout-Vliek T, De Bont A, Boer A. Under careful construction: combining findings, arguments, and values into robust health care coverage decisions. BMC Health Services Research 2022;22(1) View
  8. Faust G, Booth A, Merinopoulou E, Halhol S, Tosar H, Nawaz A, Szlachetka M, Chiu G. The Experiences of Patients With Adjuvant and Metastatic Melanoma Using Disease-Specific Social Media Communities in the Advent of Novel Therapies (Excite Project): Social Media Listening Study. JMIR Cancer 2022;8(2):e34073 View
  9. Chew S, Koh M, Loo C, Thumboo J, Shantakumar S, Matchar D. Making Clinical Practice Guidelines Pragmatic: How Big Data and Real World Evidence Can Close the Gap. Annals of the Academy of Medicine, Singapore 2018;47(12):523 View
  10. Kalf R, Delnoij D, Ryll B, Bouvy M, Goettsch W. Information Patients With Melanoma Spontaneously Report About Health-Related Quality of Life on Web-Based Forums: Case Study. Journal of Medical Internet Research 2021;23(12):e27497 View
  11. Golder S, Stevens R, O'Connor K, James R, Gonzalez-Hernandez G. Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review. Journal of Medical Internet Research 2022;24(4):e35788 View
  12. Boșoteanu L, Așchie M, Boșoteanu M. Online Doc: Is Social Media Education a Tool for Melanoma Prevention? A Survey-Based Analysis Among Romanian Digitally Active Users. Cureus 2023 View
  13. Gao Y, Xu A, Hu P. Mining Patient-Generated Content for Medication Relations and Transition Network to Predict the Rankings and Volumes of Different Medications. Information Systems Frontiers 2024 View