Sean A. Munson

Digital technologies now mediate much of health and care work, but their benefits are unevenly distributed, and research documenting this reaches practice slowly. One reason is that HCI and health evaluate work differently, so papers at their intersection are judged by whichever criteria a reviewer brings from their home community. In this introduction to the ACM HEALTH Continuous Special Section on Human-Centered Computing in Healthcare, we state the criteria we used and where they came from: which people a paper accounts for, whether the health context changes what the paper contributes to computing, whether its methods and any theory suit its question, and what its findings change for design, adoption, or governance. We introduce the 18 papers in this first installment.

The HCI community has advanced the capabilities and availability of technology to support people’s understanding of their health and to connect with others for health support. Weaponization of sensitive health data, however, necessitates greater emphasis on how this information might be used to create harm and how people navigate the associated risks. We examine how people in the United States altered their period-tracking and other technology use after the 2022 overturn of Roe v. Wade. Through interviews with 22 participants from nine states, we found that most did not significantly change their period tracking despite privacy concerns—a pattern we explain through participants’ complex risk calculus, in which abstract legal threats competed with concrete benefits, switching costs, and the paradoxical role of tracking as both risk and protection against unwanted pregnancy. Uncertainty about legal implications and inaccessible privacy policies further complicated decision-making. While tracking practices remained largely unchanged, the overturn affected how participants made decisions regarding data privacy across technologies and spurred broader life changes. Many learned about the implications of the overrule from news articles and social media, highlighting the importance of journalism and timely, accurate, and comprehensive science communication.

Always-on home IoT technologies, such as smart speakers, sensors, and cameras, are increasingly marketed toward older adults aging in place and their support networks for use in care contexts. At the same time, their integration into care relationships surfaces tensions around autonomy, consent, and relational power that existing systems are not well-equipped to address. Through individual and paired interviews with 22 participants (adults aged 65+ and their support network members), we examine how smart home adoption, use, and management become sites of ongoing negotiations. We find that older adults differentiate what they are willing to share based on the recipient, data modality, and degree of retained control, across both platform and family data sharing. They accept awareness mechanisms while desiring authority over automated actions. We show that older adults' preferences are frequently bypassed through structural power asymmetries rooted in device acquisition and management pathways, often rationalized by family members' protective intent. Older adults prefer to actively negotiate boundaries and resist forms of surveillance that undermine their autonomy. From these findings, we emphasize the need for smart home systems that support ongoing, multi-sided negotiations and derive three design criteria for creating care environments that preserve older adults' agency and dignity.

Technology has and will continue to have a significant impact on queer people’s health and well-being; however, it is not guaranteed that these implementations lead to meaningful advancements. Through a scoping review of 69 queer health technology papers in the ACM Digital Library, we review who queer health and well-being research has centered, what health topics have been targeted, and how technology has been used to address them. Our results identify trends in health foci and intervention implementation strategies, revealing opportunities for upstream efforts that work across individual, community, and structural levels. We therefore argue for greater attention towards structural constructions of queer health and well-being, specific and intentional groupings when developing interventions, and four commitments for designing and carrying out technology-enabled health interventions: commitments to holistic constructions of problem spaces, leverage points, and unintended harms; to reflexive practices for challenging assumptions; to accountability to community needs and flourishing; and to expansion towards situated and relational understandings of health. This work culminates in a framework and research agenda for queer health technology that provides guidance for future interventions.

This formative research explored health science researchers’ perspectives on the development of an artificial intelligence–based virtual study assistant and identified 8 potential features and their priorities.

UNSTRUCTURED This formative research explored health science researchers’ perspectives on the development of an artificial intelligence–based virtual study assistant and identified 8 potential features and their priorities.

Personal informatics processes require navigating distinct challenges across stages of tracking, but the range of data, goals, expertise, and context that individuals bring to self-tracking often presents barriers that undermine those processes. We investigate the potential of Generative AI (GAI) to support people across stages of pursuing self-tracking for health. We conducted interview and observation sessions with 19 participants from the United States who self-track for health, examining how they interact with GAI around their personal health data. Participants formulated and refined queries, reflected on recommendations, and abandoned queries that did not meet their needs and health goals. They further identified opportunities for GAI support across stages of self-tracking, including in deciding what data to track and how, in defining and modifying tracking plans, and in interpreting data-driven insights. We discuss GAI opportunities in accounting for a range of health goals, in providing support for self-tracking processes across planning, reflection, and action, and in consideration of limitations of embedding GAI in health self-tracking tools.