User-Centered Insights into Emotional Experiences and AI-Based Emotion Monitoring and Regulation in China: A Cross-Sectional Survey

The global rise in emotional distress demands effective Emotion Monitoring and Regulation (EMR) strategies. While AI offers promising solutions, research often overlooks user-centered perspectives. A cross-sectional survey was conducted in China to investigate emotional experiences, perceptions of AI-based EMR systems, and potential usage scenarios. Out of 624 responses, 458 valid questionnaires were analyzed. Hierarchical regression analysis revealed that Trust, Objective Analysis, and Customization positively predict user engagement, whereas Privacy Concerns negatively predict it. Findings highlight a “Support Gap”: distressed users prefer self-regulation to avoid burdening others. Consequently, users conceptualize AI not as an empathetic “Digital Therapist,” but as an objective “Clinical Assistant.” Furthermore, users define a “Contextual Safe Zone,” welcoming AI in routine settings but rejecting it during high-stakes crises. We translate these insights into actionable design guidelines emphasizing personalization, transparency, and Human-in-the-Loop oversight to ensure AI-EMR technologies are trustworthy, effective, and ethically aligned with user autonomy.