id |
caadria2025_219 |
authors |
Liu, Jie, Li, Kexin, Chen, Sihan and Li, Meng |
year |
2025 |
title |
Personalized Virtual Healing Environment Design for Stress Reduction Among Nurses: Combining AI-generated content with user-centered interaction design |
source |
Dagmar Reinhardt, Christiane M. Herr, Anastasia Globa, Jielin Chen, Taro ?Narahara, Nicolas Rogeau (eds.), ARCHITECTURAL INFORMATICS - Proceedings of the 30th CAADRIA Conference, Tokyo, 22-29 March 2025, Volume 4, pp. 541–550 |
summary |
This study addresses the growing need for effective stress management solutions for high-stress healthcare professionals, particularly nurses. The current reliance on traditional stress relief methods faces limitations in clinical settings due to their slow response and impracticality in high-pressure, sterile environments. To fill this gap, the research aims to develop a personalized Virtual Healing Environment (VHE) tailored to individual needs using AI-generated content and user-centered interaction design. The original contribution lies in combining emerging digital technologies with a therapeutic focus to create adaptable, immersive spaces that enhance emotional well-being. Specifically, this research seeks to answer how can emotional states be accurately assessed under the constraints of healthcare settings and how can personalized VHE design be accelerated through digital technologies. A mixed-methods approach was used, involving user interviews, physiological monitoring, and iterative feedback to understand stress triggers and optimize VHE design. The findings showed significant stress reduction and improved emotional states, demonstrating the potential of personalized VHEs to address mental health needs in demanding healthcare environments effectively. This study offers valuable insights into how digital tools can enhance user well-being in therapeutic architectural spaces. |
keywords |
Virtual Healing Environment, Stress Management, Personalization, AI-Generated Content, Interaction Design |
series |
CAADRIA |
full text |
file.pdf (895,074 bytes) |
references |
Content-type: text/plain
|
last changed |
2025/03/21 12:10 |
|