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

YILMA, Bereket Abera; Kim, Chan Mi; Ludden, Geke; van Rompay, Thomas; LEIVA, Luis A.

doi:10.1080/10447318.2025.2487859

Article (Scientific journals)

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

YILMA, Bereket Abera; Kim, Chan Mi; Ludden, Geke et al.

2025 • In International Journal of Human-Computer Interaction, 41 (23), p. 14709 - 14722

Peer Reviewed verified by ORBi

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https://hdl.handle.net/10993/68006

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10.1080/10447318.2025.2487859

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Keywords :

artwork; health; intensive care unit; machine learning; personalization; Recommendation; rehabilitation; user experience; Artwork; Condition; Intensive care; Machine-learning; Personalizations; Psychological Aspects; State of the art; Therapeutic intervention; Users' experiences; Human Factors and Ergonomics; Human-Computer Interaction; Computer Science Applications

Abstract :

[en] 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.

Disciplines :

Computer science

Author, co-author :

YILMA, Bereket Abera ^✱; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

Kim, Chan Mi ^✱; Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

Ludden, Geke ; Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

van Rompay, Thomas ; Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

LEIVA, Luis A. ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

^✱ These authors have contributed equally to this work.

External co-authors :

yes

Language :

English

Title :

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

Publication date :

2025

Journal title :

International Journal of Human-Computer Interaction

ISSN :

1044-7318

eISSN :

1532-7590

Publisher :

Taylor and Francis Ltd.

Volume :

Issue :

Pages :

14709 - 14722

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.tandfonline.com/doi/pdf/10.1080/10447318.2025.2487859

Funders :

European Union through the ERA-NET Cofund funding
European Innovation Council Pathfinder program

Funding text :

Research supported by the Horizon 2020 FET program of the European Union through the ERA-NET Cofund funding [grant CHIST-ERA-20-BCI-001] and the European Innovation Council Pathfinder program [SYMBIOTIK project, grant 101071147] and from the Top Technology Twente Connecting Industry program (TKI Topsector HTSM), which is partially funded by Philips Research. We thank Prof. Dr. Gerald Cupchik (University of Toronto) for his input on the study design (content of art therapy) and his advice throughout the analysis phase.

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