The AI-Therapist Duo: Exploring the Potential of Human-AI Collaboration in Personalized Art Therapy for PICS Intervention

TL;DR

This paper presents a novel human-AI collaborative art therapy approach for PICS intervention, demonstrating improved personalization and effectiveness through a large-scale user study, and highlighting potential applications in emotional support.

Contribution

It introduces two HITL personalization methods for AI-driven art therapy and evaluates their impact in a large user study, advancing personalized mental health interventions.

Findings

Enhanced therapy personalization and effectiveness

Streamlined therapist workload

Potential benefits for anxiety and depression support

Abstract

Post-intensive care syndrome (PICS) is a multifaceted condition that arises from prolonged stays in an intensive care unit (ICU). While preventing PICS among ICU patients is becoming increasingly important, interventions remain limited. Building on evidence supporting the effectiveness of art exposure in addressing the psychological aspects of PICS, we propose a novel art therapy solution through a collaborative Human-AI approach that enhances personalized therapeutic interventions using state-of-the-art Visual Art Recommendation Systems. We developed two Human-in-the-Loop (HITL) personalization methods and assessed their impact through a large-scale user study (N=150). Our findings demonstrate that this Human-AI collaboration not only enhances the personalization and effectiveness of art therapy but also supports therapists by streamlining their workload. While our study centres on PICS intervention, the results suggest that human-AI collaborative Art therapy could potentially benefit other areas where emotional support is critical, such as cases of anxiety and depression.