An AI Approach to Support Student Mental Health. Mindfulness
Keywords:
Artificial Intelligence, Mindfulness, Mental Health, Nature, nitor and Acceptance Theory, Student Well-beingAbstract
The rising mental health crisis among students globally calls for innovative solutions that leverage modern technology. This research paper outlines an AI-powered approach to enhance student mental health through a web-based platform for nature-based mindfulness at Astana Medical University. The platform utilizes the principles of the Monitor and Acceptance Theory (MAT) to create virtual experiences of nature, complemented by AI-driven guided meditations tailored to individual user needs. Recent statistics show a troubling increase in mental health issues among university students, with over 40% reporting significant stress and anxiety levels impacting their academic and personal lives. The COVID-19 pandemic has exacerbated these challenges, highlighting the need for accessible mental health resources. This project integrates AI to provide a scalable, personalized mindfulness practice that students can access remotely, aiming to improve their mental well-being by fostering a connection with nature and enhancing self-awareness and acceptance.
The development process involved four key phases: (1) collecting extensive datasets of nature videography; (2) compiling and categorizing guided meditations; (3) training AI models to customize interventions based on user responses; and (4) conducting a pilot study to refine and validate the platform's effectiveness. Preliminary results from the pilot suggest a significant improvement in participants' mental health metrics, demonstrating the potential of AI in mental health interventions. This initiative not only addresses the immediate mental health needs of students but also contributes to broader academic fields, including human-computer interaction, environmental education, and mental health research, by exploring how AI can be harnessed to support well-being through digital mediums.
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.