Generative Artificial Intelligence Intervention and Individual Psychological Counseling on Emotional Distress in Young Adults

This three-arm randomized controlled trial will investigate the efficacy of Emohaa, a generative artificial intelligence (AI)-based chatbot designed to deliver empathetic conversational support to young adults experiencing emotional distress. The study will enroll 222 participants, randomly allocated (1:1:1) into one of the following arms: AI Chatbot Group: Participants will interact weekly with Emohaa via a WeChat-integrated interface for 30-minute sessions over a 6-week period. The chatbot uses fine-tuned large language models to simulate emotionally supportive conversations and provide personalized, non-directive psychological support. Traditional Counseling Group: Participants will receive six weekly sessions (face-to-face or remote) with trained counselors using structured, supportive counseling protocols derived from cognitive-behavioral therapy (CBT). Waitlist Control Group: Participants will not receive any intervention during the study period but will be offered access to Emohaa after study completion. Assessment Schedule and Outcome Measures Data will be collected via Wenjuanxing online survey links at six time points: T1: Baseline (before intervention) T2: After session 2 T3: After session 4 T4: Post-intervention (after session 6) T5: 2-week follow-up T6: 1-month follow-up All outcome measures are validated self-report instruments with established psychometric properties in Chinese populations. Primary Outcomes (T1-T6) PHQ-9: Patient Health Questionnaire for depressive symptoms GAD-7: Generalized Anxiety Disorder Scale ISI: Insomnia Severity Index (7 items) Academic Burnout Scale (6 items) Secondary Outcomes (T1-T6) ERQ: Emotion Regulation Questionnaire (10 items) Loneliness Scale (3 items) IUS-12: Intolerance of Uncertainty Scale PSS-10: Perceived Stress Scale GESS: General Self-Efficacy Scale (10 items) Additional Measures (T2-T6) CSQ-8: Client Satisfaction Questionnaire DWAI: Digital Working Alliance Inventory Data Quality and Collection Procedures All data will be collected electronically using Wenjuanxing (问卷星), which provides timestamped, secure survey distribution and response logging. Participants will receive automatic reminders prior to each time point. The data collection team will perform regular checks to detect and manage missing or inconsistent entries. To ensure the reliability and validity of the data collection process: All measurement instruments are widely used, psychometrically validated scales in Chinese. Survey completion will be monitored in real time. Study staff will be trained in participant guidance and data integrity monitoring procedures. Duplicate entries will be flagged using participant ID and contact verification protocols. Random audits and outlier checks will be conducted at each time point to ensure data quality.