Related Experiment Video
Updated: Jun 7, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Integrating large language models in mental health practice: a qualitative descriptive study based on expert
Yingzhuo Ma1, Yi Zeng1, Tong Liu1
1Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Experts explored integrating large language models (LLMs) into mental health care. Findings highlight potential practice reforms and risks, emphasizing the need for training, guidelines, and transparency for effective LLM implementation.
Area of Science:
- Artificial Intelligence in Healthcare
- Mental Health Technology Integration
- Clinical Practice Innovation
Background:
- Growing interest in large language models (LLMs) like ChatGPT for mental health applications.
- Limited reporting on expert perspectives regarding LLM integration in mental health practice.
- Need to understand conceptualizations and perceived benefits/challenges of LLMs in mental health.
Purpose of the Study:
- To explore mental health and AI expert conceptualizations of LLMs.
- To investigate expert perceptions on integrating LLMs into mental health practice.
- To identify potential benefits, risks, and prerequisites for LLM adoption in mental health.
Main Methods:
- Online semi-structured interviews conducted with 21 experts (psychiatrists, nurses, AI researchers) in China (Feb-Apr 2024).
- Snowballing and purposive sampling used for expert recruitment.
- Conventional content analysis applied to interview data on LLM integration perspectives.
Main Results:
- Four themes emerged: practice/application reform (access, participation, efficiency), technological-mental health gap (misinformation, lack of nuance, user risk).
- Prerequisites for integration identified: training, guidelines, patient engagement, and transparency.
- Expert expectations include reasonable workload allocation and LLM upgrades.
Conclusions:
- Findings offer critical guidance for effective implementation, management, and optimization of LLMs in mental health.
- Successful integration can enhance the quality and accessibility of mental health services.
- Addressing identified risks and prerequisites is crucial for responsible LLM adoption.
More Related Videos
08:53Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Related Concept Videos
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Modeling in Therapy
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
Language and Cognition
Treatment Strategies for Psychological Disorders
Psychological therapies focus on modifying emotions, thoughts, and behaviors through talking, interpreting, listening, rewarding, challenging, and modeling. Clinical psychologists, counselors, and social workers commonly practice psychotherapy. Clinical...
Theoretical Approaches to Psychological Disorder
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
Psychodynamic Therapy