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

Formative Evaluation of Digital Health Interventions (2876) Depression and Mood Disorders; Suicide Prevention (1541) Artificial Intelligence (1789) Machine Learning (1781) Anxiety and Stress Disorders (1212) Chatbots and Conversational Agents (648)

Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27654, first published .
Thematic Analysis on User Reviews for Depression and Anxiety Chatbot Apps: Machine Learning Approach

Thematic Analysis on User Reviews for Depression and Anxiety Chatbot Apps: Machine Learning Approach

Thematic Analysis on User Reviews for Depression and Anxiety Chatbot Apps: Machine Learning Approach

Authors of this article:

Arfan Ahmed1, 2 Author Orcid Image ;   Sarah Aziz1, 2 Author Orcid Image ;   Mohamed Khalifa3 Author Orcid Image ;   Uzair Shah1 Author Orcid Image ;   Asma Hassan1 Author Orcid Image ;   Alaa Abd-Alrazaq1, 2 Author Orcid Image ;   Mowafa Househ1 Author Orcid Image
Article Authors Cited by (22) Tweetations (3) Metrics

Journals

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  12. Chen C, Lam K, Yip K, So H, Lum T, Wong I, Yam J, Chui C, Ip P. Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial. JMIR Human Factors 2025;12:e65785 View
  13. Okuboyejo S, Han S, Jha S, Eneja C, Orji R. Insights from User Reviews to Improve Suicide Prevention Apps: A Machine Learning and Thematic Analysis-Based Approach. International Journal of Human–Computer Interaction 2025:1 View
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Books/Policy Documents

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Conference Proceedings

  1. Booth F, Potts C, Bond R, Mulvenna M, Ennis E, Mctear M. Proceedings of the 33rd European Conference on Cognitive Ergonomics. Review mining to discover user experience issues in mental health and wellbeing chatbots View
  2. Kostadinov R, Vicheva D, Paunov L, Georgieva M, Topalov V, Georgiev S. 2023 International Conference on Applied Mathematics & Computer Science (ICAMCS). Artificial Intelligence Implementation for Development of Socially Significant Disease Prediction and Risk Mitigation Monitoring – Patients Perspective View
  3. Young J, Jawara L, Nguyen D, Daly B, Huh-Yoo J, Razi A. Proceedings of the CHI Conference on Human Factors in Computing Systems. The Role of AI in Peer Support for Young People: A Study of Preferences for Human- and AI-Generated Responses View
  4. Namvarpour M, Razi A. Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing. Uncovering Contradictions in Human-AI Interactions: Lessons Learned from User Reviews of Replika View

Dissertations

  1. . Comprehensive Evaluation of VA-Developed PTSD Apps: A Systematic Review, MARS Scale Assessment, and User Review Analysis through Thematic and Path Analysis. View