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Designing for Diabetes Decision Support Systems with Fluid Contextual Reasoning

Katz, Dmitri S.; Price, Blaine A.; Holland, Simon and Dalton, Nicholas Sheep (2018). Designing for Diabetes Decision Support Systems with Fluid Contextual Reasoning. In: CHI '18 Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, New York, NY, USA, article no. 625.

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Type 1 diabetes is a potentially life-threatening chronic condition that requires frequent interactions with diverse data to inform treatment decisions. While mobile technolo- gies such as blood glucose meters have long been an essen- tial part of this process, designing interfaces that explicitly support decision-making remains challenging. Dual-process models are a common approach to understanding such cog- nitive tasks. However, evidence from the first of two stud- ies we present suggests that in demanding and complex situations, some individuals approach disease management in distinctive ways that do not seem to fit well within existing models. This finding motivated, and helped frame our second study, a survey (n=192) to investigate these behaviors in more detail. On the basis of the resulting analysis, we posit Fluid Contextual Reasoning to explain how some people with diabetes respond to particular situations, and discuss how an extended framework might help inform the design of user interfaces for diabetes management.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 The Authors
ISBN: 1-4503-5620-6, 978-1-4503-5620-6
Project Funding Details:
Funded Project NameProject IDFunding Body
STRETCH: Socio-Technical Resilience for Enhancing Targeted Community HealthcareEP/P01013X/1EPSRC (Engineering and Physical Sciences Research Council)
Monetize Me? Privacy and the Quantified Self in the Digital EconomyEP/L021285/1EPSRC (Engineering and Physical Sciences Research Council)
Adaptive Security And Privacy (XC-11-004-BN)291652EC (European Commission): FP (inc.Horizon2020 & ERC schemes)
Google Scholarship for Students with DisabilitiesNot SetGoogle
Keywords: health; chronic conditions; mHealth; apps; pervasive computing; ubiquitous computing; wearable interaction; quantified self; personal informatics; Internet of Things; digital health
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 53363
Depositing User: Dmitri Katz
Date Deposited: 07 Mar 2018 13:29
Last Modified: 02 Apr 2020 11:11
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