Projects per year
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 language | English |
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Title of host publication | Proceedings of the ACM on Human-Computer Interaction |
Publisher | Association for Computing Machinery (ACM) |
Pages | 1-26 |
Number of pages | 24 |
Volume | 5 |
Edition | CSCW2 |
DOIs | |
Publication status | Published - 18 Oct 2021 |
Event | ACM Conference on Computer Supported Cooperative Work 2021 - Virtual Duration: 23 Oct 2021 → 27 Oct 2021 https://cscw.acm.org/2021/ |
Publication series
Name | Proceedings of the ACM on Human-Computer Interaction |
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Conference
Conference | ACM Conference on Computer Supported Cooperative Work 2021 |
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Abbreviated title | CSCW 2021 |
Period | 23/10/21 → 27/10/21 |
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
Fingerprint
Dive into the research topics of 'Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies'. Together they form a unique fingerprint.Projects
- 2 Finished
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COTADS: 8030 EPSRC via Southampton TAS_PP_00034 - COdesigning Trustworthy Autonomous Diabetes Systems
O'Kane, A. A., Marshall, P. & Ayobi, A.
1/05/21 → 30/06/22
Project: Research
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ML4D: InnovateUK ML4D: Machine Learning for Enhanced Diabetes Self-Care
O'Kane, A. A., Marshall, P., Santos-Rodriguez, R. & Flach, P. A.
1/11/18 → 30/04/20
Project: Research
Prizes
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CSCW 2021 Honorary Mention
Ayobi, A. (Recipient), Stawarz, K. (Recipient), Katz, D. (Recipient), Marshall, Paul (Recipient), Yamagata, Taku (Recipient), Santos-Rodriguez, Raul (Recipient), Flach, Peter A (Recipient) & O'Kane, Aisling A (Recipient), 14 Oct 2021
Prize: Prizes, Medals, Awards and Grants
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