AI-assisted stress management: Efficacy compared to traditional methods
Publication Type
Conference Proceeding Article
Publication Date
8-2025
Abstract
As the demand for accessible mental health interventions grows, AI-driven therapy offers a promising solution, particularly for stress management. This study investigates the potential of AI-driven therapy to improve emotional clarity and reduce the stigma associated with seeking mental health support. Drawing on Cognitive Behavioral Therapy (CBT), which links thoughts, emotions, and behaviors, the research investigates how AI therapists may impact emotional and behavioral outcomes. Using a three-group experimental design, the study compares the effects of AI therapists, journaling, and human therapists on stress management. The study aims to provide insights into AI’s role in stress reduction, emotional processing, and lowering barriers to therapy. By evaluating both traditional and AI-supported mental health interventions, this research contributes to the understanding of AI’s potential in the future of mental health care delivery.
Discipline
Artificial Intelligence and Robotics | Cognitive Psychology | Graphics and Human Computer Interfaces
Research Areas
Data Science and Engineering
Publication
Americas Conference on Information Systems (AMCIS 2025): Proceedings, August 14-16, Montreal
Publisher
Association for Information Systems
City or Country
Atlanta
Citation
WANG, Runyu; SIAU, Keng; and Zhang, Zili.
AI-assisted stress management: Efficacy compared to traditional methods. (2025). Americas Conference on Information Systems (AMCIS 2025): Proceedings, August 14-16, Montreal.
Available at: https://ink.library.smu.edu.sg/sis_research/10989
Additional URL
https://aisel.aisnet.org/amcis2025/health_it/sig_health/2/