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

Depression and Mood Disorders; Suicide Prevention (1363) Peer-to-Peer Support and Online Communities (636) New Methods (944) Natural Language Processing (692) Physician and Health Services Rating by Consumers (128)

Published on in Vol 5, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10726, first published .
Identifying the Underlying Factors Associated With Patients’ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews

Identifying the Underlying Factors Associated With Patients’ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews

Identifying the Underlying Factors Associated With Patients’ Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews

Authors of this article:

Maryam Zolnoori1, 2, 3 Author Orcid Image ;   Kin Wah Fung1 Author Orcid Image ;   Paul Fontelo1 Author Orcid Image ;   Hadi Kharrazi4 Author Orcid Image ;   Anthony Faiola5 Author Orcid Image ;   Yi Shuan Shirley Wu6 Author Orcid Image ;   Virginia Stoffel7 Author Orcid Image ;   Timothy Patrick8 Author Orcid Image
Article Authors Cited by (7) Tweetations (6) Metrics

Journals

  1. Zolnoori M, Balls-Berry J, Brockman T, Patten C, Huang M, Yao L. A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol for a Content Analysis. JMIR Research Protocols 2019;8(8):13914 View
  2. Zolnoori M, Fung K, Patrick T, Fontelo P, Kharrazi H, Faiola A, Wu Y, Eldredge C, Luo J, Conway M, Zhu J, Park S, Xu K, Moayyed H, Goudarzvand S. A systematic approach for developing a corpus of patient reported adverse drug events: A case study for SSRI and SNRI medications. Journal of Biomedical Informatics 2019;90:103091 View
  3. White E, Read J, Julo S. The role of Facebook groups in the management and raising of awareness of antidepressant withdrawal: is social media filling the void left by health services?. Therapeutic Advances in Psychopharmacology 2021;11 View
  4. Hatef E, Singh Deol G, Rouhizadeh M, Li A, Eibensteiner K, Monsen C, Bratslaver R, Senese M, Kharrazi H. Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record: Findings of a Retrospective Cohort Study. Frontiers in Public Health 2021;9 View
  5. Zolnour A, Eldredge C, Faiola A, Yaghoobzadeh Y, Khani M, Foy D, Topaz M, Kharrazi H, Fung K, Fontelo P, Davoudi A, Tabaie A, Breitinger S, Oesterle T, Rouhizadeh M, Zonnor Z, Moen H, Patrick T, Zolnoori M. A risk identification model for detection of patients at risk of antidepressant discontinuation. Frontiers in Artificial Intelligence 2023;6 View
  6. Arillotta D, Floresta G, Guirguis A, Corkery J, Catalani V, Martinotti G, Sensi S, Schifano F. GLP-1 Receptor Agonists and Related Mental Health Issues; Insights from a Range of Social Media Platforms Using a Mixed-Methods Approach. Brain Sciences 2023;13(11):1503 View
  7. Zhu J, Zhang X, Jin R, Jiang H, Kenne D. Probing Public Perceptions of Antidepressants on Social Media: A Mixed Methods Approach (Preprint). JMIR Formative Research 2024 View