# When and How to Integrate Multimodal Large Language Models in College Psychotherapy: Perspectives from Multi-stakeholders

arXiv: https://arxiv.org/abs/2502.00229 · HTML: https://mlsanity.com/paper/2502.00229/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Multimodal emotion understanding, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 13 of its 110 references that are in the map.
- First posted on arXiv 1 Feb 2025.

## Placed in

- Multimodal LLMs / vision-language models / [Multimodal emotion understanding](https://mlsanity.com/mllm/multimodal-emotion-understanding/)

## Builds on (most cited first, 13 of 13)

- [Emergent Abilities of Large Language Models](https://mlsanity.com/paper/2206.07682/) (2022)
- [Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks](https://mlsanity.com/paper/2302.08399/) (2023)
- [From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future](https://mlsanity.com/paper/2408.02479/) (2024)
- [Turning large language models into cognitive models](https://mlsanity.com/paper/2306.03917/) (2023)
- [A Computational Framework for Behavioral Assessment of LLM Therapists](https://mlsanity.com/paper/2401.00820/) (2024)
- [Large Language Models in Mental Health Care: a Scoping Review](https://mlsanity.com/paper/2401.02984/) (2024)
- [Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions](https://mlsanity.com/paper/1811.08592/) (2018)
- [LLM-based Conversational AI Therapist for Daily Functioning Screening and Psychotherapeutic Intervention via Everyday Smart Devices](https://mlsanity.com/paper/2403.10779/) (2024)
- [PATIENT-Psi: Using Large Language Models to Simulate Patients for Training Mental Health Professionals](https://mlsanity.com/paper/2405.19660/) (2024)
- [Understanding the Therapeutic Relationship between Counselors and Clients in Online Text-based Counseling using LLMs](https://mlsanity.com/paper/2402.11958/) (2024)
- [Recognizing Emotion Regulation Strategies from Human Behavior with Large Language Models](https://mlsanity.com/paper/2408.04420/) (2024)
- [Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models](https://mlsanity.com/paper/2405.05060/) (2024)
- [The Influence of Task and Group Disparities over Users' Attitudes Toward Using Large Language Models for Psychotherapy](https://mlsanity.com/paper/2409.05703/) (2024)

## Abstract (arXiv)

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.