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Efficient Type 1 Diabetes (T1D) management necessitates comprehensive tracking of various factors that influence blood sugar levels. However, tracking health data for children with T1D poses unique challenges, as it requires the active involvement of both children and their parents. This study aims to uncover the benefits, challenges, and strategies associated with collaborative tracking for children (ages 6-12) with T1D and their parents. Over a three-week data collection probe study with 22 child-parent pairs, we found that collaborative tracking, characterized by the shared responsibility of tracking management and data provision, yielded positive outcomes for both children and their parents. Drawing from these findings, we delineate four distinct tracking approaches: child-independent, child-led, parent-led, and parent-independent. Our study offers insights for designing health technologies that empower both children and parents in learning and encourage the sharing of different perspectives through collaborative tracking. 

Although child participation is required for successful Type 1 Diabetes (T1D) management, it is challenging because the child’s young age and immaturity make it difficult to perform self-care. Thus, parental caregivers are expected to be heavily involved in their child’s everyday illness management. Our study aims to investigate how children and parents collaborate to manage T1D and examine how the children become more independent in their self-management through the support of their parents. Through semi-structured interviews with children with T1D and their parents (N=41), our study showed that children’s knowledge of illness management and motivation for self-care were crucial for their transition towards independence. Based on these two factors, we identified four types of children’s collaboration (i.e., dependent, resistant, eager, and independent) and parents’ strategies for supporting their children’s independence. We suggest design implications for technologies to support collaborative care by improving children’s transition to independent illness management. 

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. 

Clinical documentation is a time-consuming and challenging task, especially in time-critical medical settings. Even with a dedicated scribe person, timely and accurate documentation under time constraints is never easy. In this work, we present a unique type of fast-paced medical team--emergency medical services (EMS)--which has no designated role for documentation while constantly working outside in the field to provide urgent patient care. Through interviews with 13 EMS practitioners, we reveal several interesting and prominent characteristics of EMS documentation practice as well as their associated challenges: EMS practitioners self-organize and collaborate on documentation while in the meantime being both physically and cognitively preoccupied with high-acuity patients, having limited capability to use handheld documentation systems in real-time, and being overwhelmed by strict documentation requirements and regulations. Lastly, we use our findings to discuss both technical and non-technical implications to support timely and collaborative documentation in dynamic medical contexts while accounting for care providers' physical and cognitive constraints in using computing devices. 

Recent arguments claim that behavioral science has focused – to its detriment – on the individual over the system when construing behavioral interventions. In this commentary, we argue that tackling economic inequality using both framings in tandem is invaluable. By studying individuals who have overcome inequality, “positive deviants,” and the system limitations they navigate, we offer potentially greater policy solutions. 

While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations. 

Background Health care and well-being are 2 main interconnected application areas of conversational agents (CAs). There is a significant increase in research, development, and commercial implementations in this area. In parallel to the increasing interest, new challenges in designing and evaluating CAs have emerged. Objective This study aims to identify key design, development, and evaluation challenges of CAs in health care and well-being research. The focus is on the very recent projects with their emerging challenges. Methods A review study was conducted with 17 invited studies, most of which were presented at the ACM (Association for Computing Machinery) CHI 2020 conference workshop on CAs for health and well-being. Eligibility criteria required the studies to involve a CA applied to a health or well-being project (ongoing or recently finished). The participating studies were asked to report on their projects’ design and evaluation challenges. We used thematic analysis to review the studies. Results The findings include a range of topics from primary care to caring for older adults to health coaching. We identified 4 major themes: (1) Domain Information and Integration, (2) User-System Interaction and Partnership, (3) Evaluation, and (4) Conversational Competence. Conclusions CAs proved their worth during the pandemic as health screening tools, and are expected to stay to further support various health care domains, especially personal health care. Growth in investment in CAs also shows the value as a personal assistant. Our study shows that while some challenges are shared with other CA application areas, safety and privacy remain the major challenges in the health care and well-being domains. An increased level of collaboration across different institutions and entities may be a promising direction to address some of the major challenges that otherwise would be too complex to be addressed by the projects with their limited scope and budget.