Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies

Amid Ayobi, Katarzyna Stawarz, Dmitri Katz, Paul Marshall, Taku Yamagata, Raul Santos-Rodriguez, Peter A Flach, Aisling Ann O'Kane

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

Co-design is a widely applied design process with well-documented values, including mutual learning and collective creativity. However, the real-world challenges of conducting multidisciplinary co-design research to inform the design of self-care technologies are not well established. We provide a qualitative account of a multidisciplinary project that aimed to co-design machine learning applications for Type 1 Diabetes (T1D) self-management. Through interviews, we identify not only perceived social, technological and strategic benefits of co-design but also organisational, translational and pragmatic design challenges: participants with T1D experienced difficulties in co-designing systems that met their individual self-care needs as part of group activities; HCI and AI researchers described challenges resulting from applying co-design outcomes to data-driven ML work; and industry collaborators highlighted academic data sharing regulations as cross- organisational challenges that can impede co-design efforts. Based on this understanding, we discuss opportunities for supporting multidisciplinary collaborations and aligning individual health needs with collaborative co-design activities.
Original languageEnglish
Title of host publicationProceedings of the ACM on Human-Computer Interaction
PublisherAssociation for Computing Machinery (ACM)
Pages1-26
Number of pages24
Volume5
EditionCSCW2
DOIs
Publication statusPublished - 18 Oct 2021
EventACM Conference on Computer Supported Cooperative Work 2021 - Virtual
Duration: 23 Oct 202127 Oct 2021
https://cscw.acm.org/2021/

Publication series

NameProceedings of the ACM on Human-Computer Interaction

Conference

ConferenceACM Conference on Computer Supported Cooperative Work 2021
Abbreviated titleCSCW 2021
Period23/10/2127/10/21
Internet address

Bibliographical note

Funding Information:
For context we provide here an overview of the 18-month long co-design project. Its aim was to co-design ML-based decision support concepts and co-create suitable machine learning approaches. The co-design project was funded by a scheme with a focus on fostering collaborations between businesses and academic organisations. The project involved HCI researchers, AI researchers and industry collaborators. The industry collaborators worked at a T1D start-up. A shared objective was to co-design ML-based decision support concepts and cocreate suitable machine learning approaches. Fifteen participants with T1D (aged 24-69; 3-34 years since T1D diagnosis; 11 were male) were recruited. Participants received an Apple Watch, a 12-months Dexcom Continuous Glucose Monitor (CGM) subscription, and access to an app provided by the start-up for their participation.

Publisher Copyright:
© 2021 ACM.

Keywords

  • co-design
  • participatory design
  • diabetes
  • t1d
  • personal health
  • self-care
  • self-management
  • HCI-AI
  • explainable artificial intelligence
  • machine learning

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