Chronic Care in a Life Transition: Challenges and Opportunities for Artificial Intelligence to Support Young Adults With Type 1 Diabetes Moving to University

2023. Sam James, Miranda Armstrong, Zahraa Abdallah & Aisling O'Kane
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.

Abstract

Self-managing a chronic condition involves adapting management strategies to life’s continual change. Among these changes, moments of significant life transition can render routine self-management practices obsolete without significant modification to the new context. In this study, we examine one significant life transition for young adults living with Type 1 Diabetes, the move from home to university, to understand how near future AI-enhanced technologies might provide opportunities and challenges for supporting care. From interviews with 24 students in the UK who had moved away from their childhood homes, we used sensemaking literature to frame the process of initial disruption to the rebuilding of self-care practices around a new lifestyle and support networks. By studying a significant life transition, we uncover implications for the design of T1D technology, particularly closed-loop systems, through AI enhancements and human-centred design approaches, then extrapolate for other significant life transitions and chronic conditions.

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Citation

James, S., Armstrong, M., Abdallah, Z., & O'Kane, A. A. (2023). Chronic care in a life transition: challenges and opportunities for artificial intelligence to support young adults with type 1 diabetes moving to university. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery. URL: https://doi.org/10.1145/3544548.3580901, doi:10.1145/3544548.3580901

BibTeX

@inproceedings{10.1145/3544548.3580901,
author = {James, Sam and Armstrong, Miranda and Abdallah, Zahraa and O'Kane, Aisling Ann},
title = {Chronic Care in a Life Transition: Challenges and Opportunities for Artificial Intelligence to Support Young Adults With Type 1 Diabetes Moving to University},
year = {2023},
isbn = {9781450394215},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3544548.3580901},
doi = {10.1145/3544548.3580901},
abstract = {Self-managing a chronic condition involves adapting management strategies to life’s continual change. Among these changes, moments of significant life transition can render routine self-management practices obsolete without significant modification to the new context. In this study, we examine one significant life transition for young adults living with Type 1 Diabetes, the move from home to university, to understand how near future AI-enhanced technologies might provide opportunities and challenges for supporting care. From interviews with 24 students in the UK who had moved away from their childhood homes, we used sensemaking literature to frame the process of initial disruption to the rebuilding of self-care practices around a new lifestyle and support networks. By studying a significant life transition, we uncover implications for the design of T1D technology, particularly closed-loop systems, through AI enhancements and human-centred design approaches, then extrapolate for other significant life transitions and chronic conditions.},
booktitle = {Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems},
articleno = {559},
numpages = {16},
keywords = {Artificial Intelligence, Health, Life Transitions, Qualitative Study, Type 1 Diabetes, University},
location = {Hamburg, Germany},
series = {CHI '23}
}