ORIGINAL RESEARCH article
Front. Psychol.
Sec. Health Psychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1619818
This article is part of the Research TopicImplementing Mental Health Prevention and Promotion Programs: A Sustainable Approach - Volume IIView all 22 articles
Artificial Intelligence-Assisted Psychological Intervention Mechanisms for University Students in the Context of New Media Technologies: An Analysis Based on Data from the National Institute of Mental Health
Provisionally accepted
- 1School of Art & Design, Guangzhou College of Commerce, Guangzhou, China
- 2Faculty of Humanities and Arts, Macau University of Science and Technology, Macau, China
- 3School of Arts, Universiti Sains Malaysia, Penang, Malaysia
- 4School of Art and Design, Guangzhou University, Guangzhou, China
- 5School of Public Administration, Guangzhou University, Guangzhou, China
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With the pervasive influence of new media, mental health issues among college students have become increasingly prominent, marked by high rates of emotional disorders, delayed interventions, uneven resource allocation, and insufficient attention to individual differences. This study assesses the mental health status of college students and explores the potential of artificial intelligence (AI) technologies in supporting psychological interventions. Using publicly available data from the National Institute of Mental Health (NIMH), descriptive statistical methods are applied to analyze key variables such as depression, anxiety, social support, quality of life, and technology usage. A personalized AI intervention framework is developed, integrating psychological assessments, social support levels, and technology usage patterns. Through data-driven strategy-matching algorithms, the framework provides tailored mental health support for students in different psychological states. Results show that the average depression score among the student population is 7.5 (SD = 4.2), and the average anxiety score is 6.8 (SD = 3.9), indicating the widespread prevalence of emotional issues. Additionally, a significant correlation is found between technology usage frequency and negative psychological indicators. The study’s novelty lies in applying AI models to psychological intervention strategies, leveraging intelligent perception, real-time feedback, and dynamic adjustment mechanisms to enhance personalization and operational efficiency. These findings offer a new theoretical foundation and practical pathway for building mental health support systems in higher education.
Keywords: university student mental health, artificial intelligence, intervention strategies, Personalized intervention, New media
Received: 28 Apr 2025; Accepted: 11 Aug 2025.
Copyright: © 2025 Hao, Chen, Zhao, Zhang and Zheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ning Zhao, School of Art & Design, Guangzhou College of Commerce, Guangzhou, China
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