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Various contact tracing approaches have been applied to help contain the spread of COVID-19, with technology-based tracing and human tracing among the most widely adopted. However, governments and communities worldwide vary in their adoption of digital contact tracing, with many instead choosing the human approach. We investigate how people perceive the respective benefits and risks of human and digital contact tracing through a mixed-methods survey with 291 respondents from the United States. Participants perceived digital contact tracing as more beneficial for protecting privacy, providing convenience, and ensuring data accuracy, and felt that human contact tracing could help provide security, emotional reassurance, advice, and accessibility. We explore the role of self-tracking technologies in public health crisis situations, highlighting how designs must adapt to promote societal benefit rather than just self-understanding. We discuss how future digital contact tracing can better balance the benefits of human tracers and technology amidst the complex contact tracing process and context.
The rise of ridesharing platforms has transformed traditional transportation, making it more accessible for getting to work and accessing grocery stores and healthcare providers, which are essential to physical and mental well-being. However, such technologies are not available everywhere. Additionally, there is a scarcity of HCI work that investigates how vulnerable populations such as rural-dwelling people with HIV face and overcome transportation barriers. To extend past research, we conducted 31 surveys and 18 interviews with people living with HIV (22 surveys, 14 interviews) and their case coordinators (9 surveys, 4 interviews) in rural areas. Contrary to past research, we found that the use of alternative vehicles, extensive support networks, and nonprofit health organizations facilitated transportation. However, distance, the lack of trust and infrastructure, stigma, and other cultural underpinnings made popular forms of urban transportation unappealing. We contextualize our findings with prior research and contribute implications for future research and design.
Polycystic Ovary Syndrome (PCOS) is a condition that causes hormonal imbalance and infertility in women and people with female reproductive organs. PCOS causes different symptoms for different people, with no singular or universal cure. Being a stigmatized and enigmatic condition, it is challenging to discover, diagnose, and manage PCOS. This work aims to inform the design of inclusive health technologies through an understanding of people's lived experiences and challenges with PCOS. We conducted semi-structured interviews with 10 women diagnosed with PCOS and analyzed a PCOS-specific subreddit forum. We report people's support-seeking, sense-making, and self-experimentation practices, and find uncertainty and stigma to be key in shaping their unique experiences of the condition. We further identify potential avenues for designing technology to support their diverse needs, such as personalized and contextual tracking, accelerated self-discovery, and co-management, contributing to a growing body of HCI literature on stigmatized topics in women's health and well-being.
Physical activity (PA) is crucial for reducing the risk of obesity, an epidemic that disproportionately burdens families of low-socioeconomic status (SES). While fitness tracking tools can increase PA awareness, more work is needed to examine (1) how such tools can help people benefit from their social environment, and (2) how reflections can help enhance PA attitudes. We investigated how fitness tracking tools for families can support social modeling and self-modeling (through reflection), two critical processes in Social Cognitive Theory. We developed StoryMap, a novel fitness tracking app for families aimed at supporting both modes of modeling. Then, we conducted a five-week qualitative study evaluating StoryMap with 16 low-SES families. Our findings contribute an understanding of how social and self-modeling can be implemented in fitness tracking tools and how both modes of modeling can enhance key PA attitudes: self-efficacy and outcome expectations. Finally, we propose design recommendations for social personal informatics tools.
Fertility tracking and technology are characterized by logging varied health-related data potentially associated with female fertility cycles. Such data are often seen as private and restricted to the individual level. We conducted an interview study with 21 people (16 in the U.S.) facing challenges to conceive and 5 U.S. healthcare providers specialized in infertility to analyze (in)fertility experiences with data. Our findings suggest that although fertility data are considered personal and private, they are embedded in larger ecological systems of use, influencing and being influenced by different stakeholders, institutional contexts, and sociocultural factors. Leveraging the Ecological Systems Theory, we analyze the relationships and factors shaping individuals’ fertility trajectories, discussing how the different layers influence the work individuals have to engage and the burden imposed on them through various social, institutional, and cultural boundaries. We propose an ecological perspective on fertility data practices and discuss opportunities to counter-influence broader environmental systems through data tracking.
Transgender people face difficulties accessing healthcare from providers, and thus often turn to online sources to seek health information. However, online platforms may not properly support trans health information seeking, and health information found online may be limited in accuracy. To examine how online platforms can best support trans health information seeking, we conducted online focus groups with trans people (n = 26) about their experiences with online health information and their needs and desires for online health information seeking platforms. We found that trans people face both facilitators and barriers to finding accurate, actionable information online. Facilitators include online community discovery, group privacy features, and the dual synchronous and asynchronous nature of online content. Barriers include platform censorship, misinformation, hate speech, and lack of tools to flag inaccurate content. We provide recommendations for how platforms can support trans health information seeking by ensuring that medical information is accurate, accessible, easy to locate, and relevant to a diverse set of trans identities and experiences.
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.
Recently, consumer-facing health technologies such as Artificial Intelligence (AI)-based symptom checkers (AISCs) have sprung up in everyday healthcare practice. AISCs solicit symptom information from users and provide medical suggestions and possible diagnoses, a responsibility that people usually entrust with real-person authorities such as physicians and expert patients. Thus, the advent of AISCs begs a question of whether and how they transform the notion of medical authority in people’s everyday healthcare practice. To answer this question, we conducted an interview study with thirty AISC users. We found that users assess the medical authority of AISCs using various factors including AISCs’ automated decisions and interaction design patterns, associations with established medical authorities like hospitals, and comparisons with other health technologies. We reveal how AISCs are used in healthcare delivery, discuss how AI transforms conventional understandings of medical authority, and derive implications for designing AI-enabled health technology.
People with food hypersensitivities experience adverse reactions when eating certain foods and thus need to adapt their diet. When dining out, the challenge is greater as people entrust the care of their allergy, intolerance, or celiac disease, in the hands of staff who might not have enough knowledge to appropriately care for them. This interview study explored how people with food hypersensitivities avoid reactions while eating out, to inspire future digital technology design. Our findings show the social and emotional impact of food hypersensitivities and how people practically cope by investigating restaurants' safety precautions, correcting orders, or even educating restaurants' staff. We discuss our findings against the experiences of other people living with chronic conditions and offer design opportunities for digital technologies to enhance dining out experiences of people with food hypersensitivities.
Public controversies around the unethical use of personal data are increasing, spotlighting data ethics as an increasingly important field of study. MyData is a related emerging vision that emphasizes individuals' control of their personal data. In this paper, we investigate people's perceptions of various data management scenarios by measuring the perceived ethicality and level of felt concern concerning the scenarios. We deployed a set of 96 unique scenarios to an online crowdsourcing platform for assessment and invited a representative sample of the participants to a second-stage questionnaire about the MyData vision and its potential in the field of healthcare. Our results provide a timely investigation into how topical data-related practices affect the perceived ethicality and the felt concern. The questionnaire analysis reveals great potential in the MyData vision. Through the combined quantitative and qualitative results, we contribute to the field of data ethics.
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.
Breastfeeding brings benefits for newborns and parents, but can be a challenging process. In this paper, we leverage a mixed-methods approach that builds on the Integrated Behavioural Model (IBM) to explore parents' perspectives toward breastfeeding along with their lived experiences, and examine the role of technology in this setting. Results of twelve semi-structured interviews and 175 online survey responses suggest generally positive attitudes toward breastfeeding and good theoretical knowledge. This is combined with a complex lived experience of breastfeeding where main challenges are situated in practical, emotional, and environmental/societal aspects, which are currently not sufficiently recognised by technology that seeks to support breastfeeding. Building upon our findings, we present points for reflection for the design of technology to support breastfeeding, focusing on the importance of drawing from the lived experience of parents, and ensuring that technology not only casts breastfeeding as an individual but also as a collective effort.