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

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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.
Original languageEnglish
Article number559
Number of pages16
JournalProceedings of the ACM on Human-Computer Interaction
DOIs
Publication statusPublished - 19 Apr 2023

Bibliographical note

Funding Information:
Huge thanks go to the participants for their time and engagement, the Juvenile Diabetes Research Foundation (JDRF) for their help in participant recruitment and Will and Harry for their valuable insights. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Digital Health and Care Centre for Doctoral Training (CDT) at the University of Bristol (UKRI Grant No. EP/S023704/1), Innovate UK Digital Catalyst Award - Digital Health ML4Diabetes, and the UKRI Trustworthy Autonomous Systems Hub (Grant code: RITM0372366) COTADS.

Publisher Copyright:
© 2023 ACM.

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