Al-assisted symbolic healing for digital natives: A Jungian perspective based on the S-O-R and Fogg behavior models

This study examines the design of emotional healing interventions for Generation Z individuals experiencing anxiety and investigates the mechanisms of AI-assisted collaborative drawing in addressing their needs for personalized and interactive emotional regulation. Drawing on Jungian theory of artistic compensation to evaluate AI-based art therapy, and integrating the S-O-R (Stimulus-Organism-Response) model and the FBM (Fogg Behavior Model), we analyzed how the intelligent mechanisms of AI collaborative painting contribute to emotional healing. We established three art therapy groups-generative AI painting, interactive AI painting, and traditional painting-for comparison. The therapeutic effects were evaluated using the Generalized Anxiety Disorder Scale (GAD-7) and the Difficulties in Emotion Regulation Scale (DERS). The findings confirm the superior performance of AI collaborative drawing in enhancing immediacy and feedback, providing personalized support, and improving users' emotional stability. Furthermore, the study explores how AI platforms can develop personalized emotional healing functions that effectively guide emotional expression and processing. The potential of AI collaborative drawing in emotional healing has often been overlooked. This study aims to demonstrate how research design and theoretical modeling can open new avenues for analyzing its applications, thereby offering innovative strategies for supporting the mental health of Generation Z as well as new tools and perspectives for psychotherapy and art therapy practice.