Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference最新文献

There is growing interest in HCI to study ways to support access to accurate, accessible, relevant online health information for different populations. Yet, there remains a need to understand the barriers that are posed by the way our platforms are designed as well as how we might overcome these barriers for people with dementia. To address this, we conducted sixteen interviews and observation sessions with people with mild to moderate dementia. Our analysis uncovered four barriers to online health information and corresponding mitigation strategies that participants employed. We discuss how HCI researchers may apply these findings towards new technical approaches and standards concerning information accessibility and credibility for neurodiverse populations. Finally, we broaden the scope of HCI research to include investigations of the accessibility and credibility of online information for people with age-related cognitive impairment independent of proxies.

Conversational interaction, for example through chatbots, is well-suited to enable automated health coaching tools to support self-management and prevention of chronic diseases. However, chatbots in health are predominantly scripted or rule-based, which can result in a stagnant and repetitive user experience in contrast with more dynamic, data-driven chatbots in other domains. Consequently, little is known about the tradeoffs of pursuing data-driven approaches for health chatbots. We examined multiple artificial intelligence (AI) approaches to enable micro-coaching dialogs in nutrition - brief coaching conversations related to specific meals, to support achievement of nutrition goals - and compared, reinforcement learning (RL), rule-based, and scripted approaches for dialog management. While the data-driven RL chatbot succeeded in shorter, more efficient dialogs, surprisingly the simplest, scripted chatbot was rated as higher quality, despite not fulfilling its task as consistently. These results highlight tensions between scripted and more complex, data-driven approaches for chatbots in health.

Young adults have high rates of mental health conditions, yet they are the age group least likely to seek traditional treatment. They do, however, seek information about their mental health online, including by filling out online mental health screeners. To better understand online self-screening, and its role in help-seeking, we conducted focus groups with 50 young adults who voluntarily completed a mental health screener hosted on an advocacy website. We explored (1) catalysts for taking the screener, (2) anticipated outcomes, (3) reactions to the results, and (4) desired next steps. For many participants, the screener results validated their lived experiences of symptoms, but they were nevertheless unsure how to use the information to improve their mental health moving forward. Our findings suggest that online screeners can serve as a transition point in young people's mental health journeys. We discuss design implications for online screeners, post-screener feedback, and digital interventions broadly.

Black older adults from lower socioeconomic environments are often neglected in health technology interventions. Voice assistants have a potential to make healthcare more accessible to older adults, yet, little is known about their experiences with this type of health information seeking, especially Black older adults. Through a three-phase exploratory study, we explored health information seeking with 30 Black older adults in lower-income environments to understand how they ask health-related questions, and their perceptions of the Google Home being used for that purpose. Through our analysis, we identified the health information needs and common search topics, and discussed the communication breakdowns and types of repair performed. We contribute an understanding of cultural code-switching that has to be done by these older adults when interacting with voice assistants, and the importance of such phenomenon when designing for historically excluded groups.

Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data requires motivation and literacy. Machine learning (ML) methods can identify patterns, but a key challenge is making actionable suggestions based on personal health data. We introduce GlucoGoalie, which combines ML with an expert system to translate ML output into personalized nutrition goal suggestions for individuals with T2D. In a controlled experiment, participants with T2D found that goal suggestions were understandable and actionable. A 4-week in-the-wild deployment study showed that receiving goal suggestions augmented participants' self-discovery, choosing goals highlighted the multifaceted nature of personal preferences, and the experience of following goals demonstrated the importance of feedback and context. However, we identified tensions between abstract goals and concrete eating experiences and found static text too ambiguous for complex concepts. We discuss implications for ML-based interventions and the need for systems that offer more interactivity, feedback, and negotiation.

Self-management research in HCI has addressed a variety of conditions. Yet, this literature has largely focused on neurotypical populations and chronic conditions that can be managed, leaving open questions of what self-management might look like for populations with progressive cognitive impairment. Grounded in interviews with seventeen technology savvy people with mild to moderate dementia, our analysis reveals their use of technological and social resources as part of the work of self-management. We detail how participants design self-management systems to enable desired futures, function well in their social world, and maintain control. Our discussion broadens the notion of self-management to include future-oriented, sociotechnical, self-determinate design. We advocate for expanding the way technologists, designers, and HCI scholars view people with mild to moderate dementia to recognize them as inventive creators and capable actors in self-management.

Personal health informatics continues to grow in both research and practice, revealing many challenges of designing applications that address people's needs in their health, everyday lives, and collaborations with clinicians. Research suggests strategies to address such challenges, but has struggled to translate these strategies into design practice. This study examines translation of insights from personal health informatics research into resources to support designers. Informed by a review of relevant literature, we present our development of a prototype set of design cards intended to support designers in re-thinking potential assumptions about personal health informatics. We examined our design cards in semi-structured interviews, first with 12 student designers and then with 12 health-focused professional designers and researchers. Our results and discussion reveal tensions and barriers designers encounter, the potential for translational resources to inform the design of health-related technologies, and a need to support designers in addressing challenges of knowledge, advocacy, and evidence in designing for health.

Many 10-14 year olds are at the early stages of using social media, habits they develop on popular platforms can have lasting effects on their socio-emotional wellbeing. We led a remote innovation workshop with 23 middle schoolers on digital wellbeing, identity exploration, and computational concepts related to social computing. This workshop was a unique opportunity to reflect on emergent habits, discuss them with peers, and imagine oneself as an ICT innovator. Resulting themes related to participants' social wellbeing online included a) sense of belonging to communities of interest, friends, and family, b) self-care and social support strategies involving managing risks, control, and empathy, and c) experimentation while building self-confidence and bravely exploring audience reactions. Participants iteratively designed and tested a sandbox social network website, resulting in Social Sketch. Reflecting on our study, we describe the process for conceptualizing Social Sketch, and challenges in social media innovation with teenagers.

Makerspaces are being introduced in a wide variety of settings, including community settings such as schools and libraries. Older adults are one group for whom making agendas are being pursued, with envisioned outcomes such as supporting agency and well-being. However, research on making and DIY with older adults typically study individuals who are already engaged in making practices or bring individuals in to a technology environment that has already been created. In this paper, we study the older adult-driven formation of a makerspace in an independent living community. Through an ethnographically-informed approach, we studied the ways that individuals considered appropriate allocation of resources towards a makerspace, scoped activities, evaluated goals, and made trade-ofs. Our analysis is centered around describing the way that this makerspace formed as well as three ways that individuals made sense of the makerspace as the planning unfolded: the openness of a space that promises to cater to interests of the population; the promise of a makerspace to involve more residents in technology, but the need to obscure the technology to make it appealing; and a valuation of the return on investment for limited fnancial and space resources. Our discussion contributes to supporting and studying early adoption of technology by older adults, complicates visions of "making for all," and presents considerations regarding the often under-specifed community of a makerspace.