This research introduces a novel human-centric anxiety detection system that combines advanced language models with personalized guidance mechanisms.

• Identifies anxiety levels across multiple real-life scenarios (work, education, relationships)
• Provides interpretable explanations rather than simple categorization
• Delivers customized guidance based on individual anxiety patterns
• Demonstrates how AI can bridge detection and intervention in mental health

This research advances mental healthcare by enabling more accessible, personalized anxiety support tools that can help identify early warning signs of severe psychological distress and potentially prevent escalation to crisis situations.

Exploring the Panorama of Anxiety Levels: A Multi-Scenario Study Based on Human-Centric Anxiety Level Detection and Personalized Guidance