As mental health issues rise among college students, there is an increasing interest and demand in leveraging Multimodal Language Models (MLLM) to enhance mental support services, yet integrating them into psychotherapy remains theoretical or non-user-centered. This study investigated the opportunities and challenges of using MLLMs within the campus psychotherapy alliance in China. Through three studies involving both therapists and student clients, we argue that the ideal role for MLLMs at this stage is as an auxiliary tool to human therapists. Users widely expect features such as triage matching and real-time emotion recognition. At the same time, for independent therapy by MLLM, concerns about capabilities and privacy ethics remain prominent, despite high demands for personalized avatars and non-verbal communication. Our findings further indicate that users' sense of social identity and perceived relative status of MLLMs significantly influence their acceptance. This study provides insights for future intelligent campus mental healthcare.
@article{arxiv.2502.00229,
title = {When and How to Integrate Multimodal Large Language Models in College Psychotherapy: Perspectives from Multi-stakeholders},
author = {Jiyao Wang and Youyu Sheng and Qihang He and Zian Zhang and Haolong Hu and Yumei Jing and Dengbo He},
journal= {arXiv preprint arXiv:2502.00229},
year = {2026}
}