Individuals with multiple chronic health conditions (MCC) often face an overwhelming set of self-management work, resulting in a need to set care priorities. Yet, much self-management work is invisible to healthcare providers. This study aimed to understand how to support the development and sharing of connections between personal values and self-management tasks through the facilitated use of an interactive visualization system: Conversation Canvas. We conducted a field study with 13 participants with MCC, 3 caregivers, and 7 primary care providers in Washington State. Analysis of interviews with MCC participants showed that developing visualizations of connections between personal values, self-management tasks, and health conditions helped individuals make sense of connections relevant to their health and wellbeing, recognize a road map of central issues and their impacts, feel respected and understood, share priorities with providers, and support value-aligned changes. These findings demonstrated potential for the guided process and visualization to support priorities-aligned care.
Children with Type 1 Diabetes (T1D) face many challenges with keeping their blood glucose levels within a healthy range because they cannot manage their illness by themselves. To prevent children’s blood glucose from becoming too high or too low, parents apply different strategies to avoid risky situations. To understand how parents of children with T1D manage these risks, we conducted semi-structured interviews with children with T1D (ages 6-12) and their parents (N=41). We identified four types of strategies used by parents (i.e., educated guessing game, contingency planning, experimentation, and reaching out for help) that can be categorized according to two dimensions: 1) the cause of risk (known or unknown) and 2) the occurrence of risk (predictable or unpredictable). Based on our findings, we provide design implications for collaborative health technologies that support parents in better planning for contingencies and identifying unknown causes of risks together with their children.
Online fitness video tutorials are an increasingly popular way to stay fit at home without a personal trainer. However, to keep the screen playing the video in view, users typically disrupt their balance and break the motion flow --- two main pillars for the correct execution of yoga poses. While past research partially addressed this problem, these approaches supported only a limited view of the instructor and simple movements. To enable the fluid execution of complex full-body yoga exercises, we propose FlowAR, an augmented reality system for home workouts that shows training video tutorials as always-present virtual static and dynamic overlays around the user. We tested different overlay layouts in a study with 16 participants, using motion capture equipment for baseline performance. Then, we iterated the prototype and tested it in a furnished lab simulating home settings with 12 users. Our results highlight the advantages of different visualizations and the system's general applicability.
Hand edema, defined as swelling of the hands caused by excess fluid accumulation, is a pervasive condition affecting a person’s range of motion and functional ability. However, treatment strategies remain limited to time-consuming manual massage by trained therapists, deterring a widely accessible approach. We present KnitDema, a robotic textile device that allows sequential compression from distal to proximal finger phalanges for mobilizing edema. We machine-knit the device and integrate small-scale actuators to
envelop granular body locations such as fingers, catering to the shape of the hand. In addition, the device affords customizable compression levels through the enclosed fiber-like actuators. We characterize compression parameters and simulate the shunting
of edema through a mock fluid system. Finally, we conduct a case study to evaluate the feasibility of the device, in which five hand edema patients assess KnitDema. Our study provides insights into the opportunities for robotic textiles to support personalized rehabilitation.
Older adults are increasingly acting as caregivers, given population aging and pervasive caregiver shortages. Meanwhile, gig-economy-based carework platforms have also become popular. As older adults are one of the fastest-growing groups of informal caregivers and technology users in the past decade, we conducted an online survey among older adults residing in the US (N = 193) about how they use these platforms to manage their caregiving tasks. We identified factors related to their frequency of using caregiving help and their intention to continue using caregiving help via carework platforms. We also reported how and why older adults use these platforms, their main concerns and needs related to these platforms, and their most significant positive and negative experiences. Our findings contribute to a foundational understanding of how older caregivers use carework platforms and how such platforms could be better designed to suit the needs and wants of older caregivers.
Engaging with multiple streams of personal health data to inform self-care of chronic health conditions remains a challenge. Existing informatics tools provide limited support for patients to make data actionable. To design better tools, we conducted two studies with Type 1 diabetes patients and their clinicians. In the first study, we observed data review sessions between patients and clinicians to articulate the tasks involved in assessing different types of data from diabetes devices to make care decisions. Drawing upon these tasks, we designed novel data interfaces called episode-driven data narratives and performed a task-driven evaluation. We found that as compared to the commercially available diabetes data reports, episode-driven data narratives improved engagement and decision-making with data. We discuss implications for designing data interfaces to support interaction with multidimensional health data to inform self-care.