論文アブストラクト： Breathalyzers, the standard quantitative method for assessing inebriation, are primarily owned by law enforcement and used only after a potentially inebriated individual is caught driving. However, not everyone has access to such specialized hardware. We present drunk user interfaces: smartphone user interfaces that measure how alcohol affects a person's motor coordination and cognition using performance metrics and sensor data. We examine five drunk user interfaces and combine them to form the "DUI app". DUI uses machine learning models trained on human performance metrics and sensor data to estimate a person's blood alcohol level (BAL). We evaluated DUI on 14 individuals in a week-long longitudinal study wherein each participant used DUI at various BALs. We found that with a global model that accounts for user-specific learning, DUI can estimate a person's BAL with an absolute mean error of 0.005% ± 0.007% and a Pearson's correlation coefficient of 0.96 with breathalyzer measurements.
論文アブストラクト： Self-care technologies have been influenced by medical values and models. One of the values that was acritically incorporated was that self-care was medicalised, and, as a result, technologies were designed to afford use with clinicians and fit structured medical processes. This paper seeks to broaden the understanding of self-care in HCI, to acknowledge the mundane ways in which self-care is achieved. Drawing on in-depth interviews with patients and carers, and online ethnography of an online community, we describe how the self-care of Parkinson's is mundane. The fieldwork contrasts with more medicalised perspectives on self-care, thus we discuss the properties of a self-care concept that would acknowledge its mundane nature. Our hope is to sensitise designers to identify the mundane ways in which self-care is performed and, consequently, design technologies that better fit the complexities of everyday life with a chronic condition.
論文アブストラクト： Type 1 diabetes is a potentially life-threatening chronic condition that requires frequent interactions with diverse data to inform treatment decisions. While mobile technologies such as blood glucose meters have long been an essential part of this process, designing interfaces that explicitly support decision-making remains challenging. Dual-process models are a common approach to understanding such cognitive tasks. However, evidence from the first of two studies 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.
毎分ごとにグルコースの量を監視することができるサービスFlash Glucose Meter (FGM)と糖尿病を防ぐために、グルコースの量やそれの偏差値などを可視化できるサービスを使って実験を行なった。
論文アブストラクト： This paper analyses sexual health workers' 'talk' around their introduction of a digital platform to enhance a regionally managed condom distribution scheme for young people. In examining the discursive resources workers used in framing the sexual health service, their service users and digital technology, we argue that problematic ideologies around young people and sexuality were exercised and reproduced. Workers positioned themselves as the gatekeepers of young people's sexual health, who were in turn constructed as 'mischievous' and 'misguided', with technology having a corruptive role over what was considered to be 'healthy' and 'normal' sexual relationships. We suggest our findings indicate severe challenges in developing community-commissioned platforms alongside service providers, and questions how plausible user participation can be in attempting to conduct collaborative, participatory and engaged work in this context.