BIG::AI BIG::Health
Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies
2021. Proceedings of the ACM on Human-Computer Interaction.
Amid Ayobi, Katarzyna Stawarz, Dmitri Katz, Paul Marshall, Taku Yamagata, Raul Santos-Rodriguez, Peter Flach & Aisling O'Kane.
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.
Full paper
https://dl.acm.org/doi/abs/10.1145/3479601?sid=SCITRUS
Citation
Ayobi, A., Stawarz, K., Katz, D., Marshall, P., Yamagata, T., Santos-Rodriguez, R., … O'Kane, A. A.
(2021 , oct).
Co-designing personal health? multidisciplinary benefits and challenges in informing diabetes self-care technologies.
Proc. ACM Hum.-Comput. Interact., 5(CSCW2).
URL: https://doi.org/10.1145/3479601, doi:10.1145/3479601
BibTeX
@article{10.1145/3479601,
author = {Ayobi, Amid and Stawarz, Katarzyna and Katz, Dmitri and Marshall, Paul and Yamagata, Taku and Santos-Rodriguez, Raul and Flach, Peter and O'Kane, Aisling Ann},
title = {Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies},
year = {2021},
issue_date = {October 2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {5},
number = {CSCW2},
url = {https://doi.org/10.1145/3479601},
doi = {10.1145/3479601},
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.},
journal = {Proc. ACM Hum.-Comput. Interact.},
month = {oct},
articleno = {457},
numpages = {26},
keywords = {HCI-AI, T1D, co-design, diabetes, explainable artificial intelligence, human-centred machine learning, participatory design, personal health, self-care, self-management}
}