Advance Care Planning (ACP) allows individuals to specify their preferred end-of-life life-sustaining treatments before they become incapacitated by injury or terminal illness (e.g., coma, cancer, dementia). While online ACP offers high accessibility, it lacks key benefits of clinical consultations, including personalized value exploration, immediate clarification of decision consequences. To bridge this gap, we conducted two formative studies: 1) shadowed and interviewed 3 ACP teams consisting of physicians, nurses, and social workers (18 patients total), and 2) interviewed 14 users of ACP websites. Building on these insights, we designed PreCare in collaboration with 6 ACP professionals. PreCare is a website with 3 AI-driven assistants designed to guide users through exploring personal values, gaining ACP knowledge, and supporting informed decision-making. A usability study (n=12) showed that PreCare achieved a System Usability Scale (SUS) rating of excellent. A comparative evaluation (n=12) showed that PreCare's AI assistants significantly improved exploration of personal values, knowledge, and decisional confidence, and was preferred by 92% of participants.
View on arXiv@article{hsu2025_2505.09115,
title={ PreCare: Designing AI Assistants for Advance Care Planning (ACP) to Enhance Personal Value Exploration, Patient Knowledge, and Decisional Confidence },
author={ Yu Lun Hsu and Yun-Rung Chou and Chiao-Ju Chang and Yu-Cheng Chang and Zer-Wei Lee and Rokas Gipiškis and Rachel Li and Chih-Yuan Shih and Jen-Kuei Peng and Hsien-Liang Huang and Jaw-Shiun Tsai and Mike Y. Chen },
journal={arXiv preprint arXiv:2505.09115},
year={ 2025 }
}