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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51785, first published .
Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective

Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective

Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective

Journals

  1. Hussain S, Bresnahan M, Zhuang J. Can artificial intelligence revolutionize healthcare in the Global South? A scoping review of opportunities and challenges. DIGITAL HEALTH 2025;11 View
  2. Ye C, Wang Z, Wu M, Kang R, Yuan F, Chen C. Behavioral drivers of AI nursing acceptance in the Greater Bay Area: a family-caregiver perspective on trust and risk. Frontiers in Public Health 2025;13 View
  3. Silalahi A. Frustration Dissonance and the Paradox of Persistence in ChatGPT Usage: Insights from Indonesia and Taiwan. International Journal of Human–Computer Interaction 2025:1 View
  4. Fang L, Zhu Y, Li J, Fang C, Xu Y, Wang S. User-Centered Insights into Emotional Experiences and AI-Based Emotion Monitoring and Regulation in China: A Cross-Sectional Survey. International Journal of Human–Computer Interaction 2026:1 View
  5. Boykin E, Hatcher W, Hunter L, Meares W, Ginn M. AI, monitoring, and the public workplace. Administrative Theory & Praxis 2026:1 View
  6. Fang L, Zhu Y, Li J, Fang C, Xu Y, Wang S. User Perspectives on AI-Supported Emotion Monitoring and Regulation: A Focus Group Study in Non-Clinical Contexts. International Journal of Human–Computer Interaction 2026:1 View