Use of large language models (LLMs) for personalized and accessible mental health support

Mental health challenges among students have become increasingly prevalent and concerning in recent years. While traditional approaches to addressing these issues often involve counselling services and therapeutic interventions, there is a growing recognition of the potential benefits of incorporati...

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Main Author: Lee, Junwei
Other Authors: Shen Zhiqi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175174
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1751742024-04-26T15:41:29Z Use of large language models (LLMs) for personalized and accessible mental health support Lee, Junwei Shen Zhiqi School of Computer Science and Engineering Computational Intelligence Lab ZQShen@ntu.edu.sg Computer and Information Science Mental health challenges among students have become increasingly prevalent and concerning in recent years. While traditional approaches to addressing these issues often involve counselling services and therapeutic interventions, there is a growing recognition of the potential benefits of incorporating 3D AI assistants to support students' mental well-being. In the realm of student mental health, where the emphasis is often on stress, anxiety, depression, and academic pressures, the integration of 3D AI assistants and virtual reality technologies offers a novel approach. These AI-driven avatars can serve as personalized virtual companions to students, providing them with emotional support, guidance, and coping strategies. However, the specific software tools and their usability, utility, and acceptance by both students and mental health professionals remain relatively unexplored. To address this gap and harness the potential of 3D AI assistants in the context of student mental health, this paper presents two significant contributions: 1. A comprehensive description of a 3D AI assistant system tailored to the needs of students, offering insights into the technical aspects of avatar creation and customization, thereby laying the groundwork for future research and implementation. 2. An extensive evaluation of the 3D AI assistant system from the perspectives of both developers and students. This evaluation encompasses not only the usability of the technology but also its acceptance and effectiveness as a valuable tool in promoting student well-being. Additionally, this study highlights key findings, shares valuable lessons learned, and acknowledges the primary limitations encountered, paving the way for the potential integration of 3D AI assistants as a transformative resource in enhancing the mental health of students. Bachelor's degree 2024-04-23T00:38:29Z 2024-04-23T00:38:29Z 2024 Final Year Project (FYP) Lee, J. (2024). Use of large language models (LLMs) for personalized and accessible mental health support. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175174 https://hdl.handle.net/10356/175174 en SCSE23-0460 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
spellingShingle Computer and Information Science
Lee, Junwei
Use of large language models (LLMs) for personalized and accessible mental health support
description Mental health challenges among students have become increasingly prevalent and concerning in recent years. While traditional approaches to addressing these issues often involve counselling services and therapeutic interventions, there is a growing recognition of the potential benefits of incorporating 3D AI assistants to support students' mental well-being. In the realm of student mental health, where the emphasis is often on stress, anxiety, depression, and academic pressures, the integration of 3D AI assistants and virtual reality technologies offers a novel approach. These AI-driven avatars can serve as personalized virtual companions to students, providing them with emotional support, guidance, and coping strategies. However, the specific software tools and their usability, utility, and acceptance by both students and mental health professionals remain relatively unexplored. To address this gap and harness the potential of 3D AI assistants in the context of student mental health, this paper presents two significant contributions: 1. A comprehensive description of a 3D AI assistant system tailored to the needs of students, offering insights into the technical aspects of avatar creation and customization, thereby laying the groundwork for future research and implementation. 2. An extensive evaluation of the 3D AI assistant system from the perspectives of both developers and students. This evaluation encompasses not only the usability of the technology but also its acceptance and effectiveness as a valuable tool in promoting student well-being. Additionally, this study highlights key findings, shares valuable lessons learned, and acknowledges the primary limitations encountered, paving the way for the potential integration of 3D AI assistants as a transformative resource in enhancing the mental health of students.
author2 Shen Zhiqi
author_facet Shen Zhiqi
Lee, Junwei
format Final Year Project
author Lee, Junwei
author_sort Lee, Junwei
title Use of large language models (LLMs) for personalized and accessible mental health support
title_short Use of large language models (LLMs) for personalized and accessible mental health support
title_full Use of large language models (LLMs) for personalized and accessible mental health support
title_fullStr Use of large language models (LLMs) for personalized and accessible mental health support
title_full_unstemmed Use of large language models (LLMs) for personalized and accessible mental health support
title_sort use of large language models (llms) for personalized and accessible mental health support
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175174
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