This paper presents a qualitative study with 17 participants that uses video elicitations to investigate how conversational AI agents driven by large language models might support “shared care,” or coordination of home-based care among family caregivers (FCs) and home care workers (HCWs) who care for the same care recipient (CR). Participants saw conversational AI as a promising tool that might help streamline communication, coordinate shift handovers, bridge language gaps, and support onboarding of new or substitute caregivers. That said, caregivers assumed AI agents would inevitably make mistakes and should thus be designed to signal uncertainty and make it easy to report errors. More broadly, participants discussed how AI agents designed for sensitive home care contexts will need to explicitly preserve the human essence of care, minimize extra data work that might distract from caregiving, and always complement—not replace—human judgment.

This paper explores opportunities and challenges for data-driven advocacy to support home care workers, an often overlooked group of low-wage, frontline health workers.First, we investigate what data to collect and how to collect it in ways that preserve privacy and avoid burdening workers.Second, we examine how workers and advocates could use collected data to strengthen individual and collective advocacy efforts.Our qualitative study with 11 workers and 15 advocates highlights tensions between workers' desires for individual and immediate benefits and advocates' preferences to prioritize more collective and long-term benefits.We also uncover discrepancies between participants' expectations for how data might transform advocacy and their on-the-ground experiences collecting and using real data.Finally, we discuss future directions for data-driven worker advocacy, including combining different kinds of data to ameliorate challenges, leveraging advocates as data stewards, and accounting for workers' and organizations' heterogeneous goals.

We present a qualitative study that investigates the implications of current and near-future AI deployment for home care workers (HCWs), an overlooked group of frontline healthcare workers. Through interviews with 22 HCWs, care agency staff, and worker advocates, we find that HCWs do not understand how AI works, how their data can be used, or why AI systems might retain their information. HCWs are unaware that AI is already being utilized in their work, primarily via algorithmic shift-matching systems adopted by agencies. Participants detail the risks AI poses in sensitive care settings for HCWs, patients, and agencies, including threats to workers' autonomy and livelihoods, and express concerns that workers will be held accountable for AI mistakes, with the burden of proving AI's decisions incorrect falling on them. Considering these risks, participants advocate for new regulations and democratic governance structures that protect workers and control AI deployment in home care work.

Home care workers (HCWs) are an important group of frontline workers that deliver essential at-home care services to enable older adults to age in place. Despite their importance in patient care, research has shown that HCWs are an overlooked and undervalued workforce: HCWs work in isolated conditions, are paid low wages, experience high levels of stress and burnout, and more. As a result, despite being motivated to try and be healthy, this essential workforce suffers from poor physical and mental health outcomes. This paper combines data from focus groups, interviews, and a month-long field study with HCWs to investigate the feasibility and utility of using activity tracking devices to provide HCWs with fine-grained awareness and insights into daily activities that affect their health and wellbeing. We explore HCWs' reactions to both their individual and collective data, discussing their efforts towards positive behavior change, but also highlighting systemic and occupational factors that may limit HCWs' agency and control over their own activities. Finally, we discuss the potential for HCWs' collective data to raise awareness about their working conditions and provide data-driven evidence to aid advocacy efforts towards improved policies, better wages, or greater protections for this vital workforce.

Home care workers (HCWs) are professionals who provide care to older adults and people with disabilities at home. However, HCWs are vulnerable and especially susceptible to wage theft, or not being paid their legally-entitled wages in full by their employers. Prior work has examined other low-wage work settings to show how technology is designed and deployed has the potential to both cause and address wage theft. We extend this work by examining the relationship between technology and wage theft in the home care context. We collaborated closely with a local grassroots organization to conduct interviews with workers and labor, legal, and payroll experts. We uncovered how the complex, volatile, and diverse nature of home care complicates the errors in time-tracking systems. Through design provocations and focus groups with workers and experts, we also investigated the potential of technology as a part of broader efforts to curb wage theft through educating and empowering isolated HCWs. While we found that approachable design could reduce errors in existing systems, make employer processes more transparent, and help workers exchange knowledge to build collective power, we also discuss concerns around burden, privacy, and accountability when designing technologies for HCWs and other low-wage workers.

Home care workers (HCWs) deliver essential health services within patients’ homes and are an important part of the US healthcare system. Yet, they are a marginalized workforce, whose physical isolation and lack of access to support structures make them vulnerable to exploitation. Computer-mediated support programs may help bridge this gap and, through critical and liberatory pedagogies, foster material social change. However, such pedagogies typically assume the involvement of a professional facilitator when, in practice, support programs are often led by peers with little to no facilitation training. Based on a three-month study with HCWs, this paper explores how peers can perform critical and liberatory facilitation practice in an online support program. We illustrate the challenges peers faced learning this practice and performing this role in an online environment. Our findings can improve the design of computer-mediated support programs and how to prepare peer leadership, particularly for addressing the needs of marginalized populations.

Home health aides are paid professionals who provide long-term care to an expanding population of adults who need it. However, aides' work is often unrecognized by the broader caregiving team despite being in demand and crucial to care---an invisibility reinforced by ill-suited technological tools. In order to understand the invisible work aides perform and its relationship to technology design, we interviewed 13 aides employed by home care agencies in New York City. These aides shared examples that demonstrated the intertwined nature of both types of invisible work (i.e., emotions- and systems-based) and expanded the sociological mechanisms of invisibility (i.e., sociocultural, sociolegal, sociospatial) to include the sociotechnical. Through these findings, we investigate the opportunities, tensions, and challenges that could inform the design of tools created for these important, but often overlooked, frontline caregivers.

Home care workers (HCWs) provide essential care in patients' homes but are often underappreciated and work in stressful and isolated environments with diverse and intersecting support needs. This paper describes a computer-mediated peer support program that centers around sharing circles: spaces for personal, narrative storytelling to encourage HCWs to collaboratively reflect on their home care experiences and build rapport and shared identity with their peers. We describe the design of this program and a 12-week deployment that we conducted to evaluate the program with 42 HCWs in New York City. Our findings show that participants engaged in multiple types of peer support including emotional validation, learning how to navigate the workplace and patient care, defining and enabling good home care praxis, and building understanding around purpose and identity as HCWs. We discuss how these findings inform the design of technology and use of holistic pedagogies, such as storytelling, to enable this support in computer-mediated peer support programs. Such programs can help researchers and practitioners interested in addressing diverse needs that occur in intersectional contexts, such as that of HCWs and other marginalized populations.

Frontline health workers provide essential services for their communities, but much of their work remains invisible—undervalued and underappreciated. Examining this invisible work ensures new technologies do not amplify or reinforce inequitable power structures, especially as governments and organizations push to digitize health work processes. We build on a burgeoning conversation by studying how invisible work manifests and how this invisibility can be challenged in two contexts of frontline health: home health aides in New York City, USA and Accredited Social Health Activists (ASHAs) in Uttar Pradesh, India. We highlight three shared manifestations of invisible work: (1) work done outside of the workers’ boundaries (2) work done to gain and share knowledge and (3) work done to manage relationships. These common categories are experienced differently in the two contexts, raising nuances to consider when designing technology for frontline health workers. We discuss these nuances and other tensions through concrete examples of how workers can escalate feedback and conflicts, quantify implicit expertise about patients, or build more awareness of their situation. Our paper guides the creation of technologies that take into account a more comprehensive understanding of the frontline health workers’ processes and highlight more of their contributions.

Home care workers (HCWs) are increasingly central to post-acute and long-term health services in the United States. Despite being a critical component of the day-to-day care of home-dwelling adults, these workers often feel underappreciated and isolated on the job and come from low-income and marginalized backgrounds. Leveraging the support of peers is one potential way to empower HCWs, but peer support encompasses a broad range of activities and aspects. Traditional conceptions of workplace support may not be appropriate to the home care context, as HCWs are a distributed workforce who have few opportunities to interact with each other. In this study, we explore how HCWs value and conceptualize peer support. Our findings demonstrate the importance of peer support in performing the emotional labor of home care work and ongoing attempts to strategically frame the home care profession as essential and medical in nature. Our results ground design implications for technology-enabled peer support based on the power dynamics of our participants' context and allow us to engage with issues where technology design for empowerment intersects with exploitation in distributed or crowd work, emotional labor, and tacit knowledge.

HCI researchers have increasingly studied how technology might improve the lives of marginalized workers. We explored this question through a qualitative study with home health aides in New York City, a vulnerable group of frontline caregivers whose work with patients is poorly paid and highly stressful, often involving life-or-death situations. To elicit the perspectives of aides and their supervisors on how technology interventions might contribute to moving aides towards a better future, we created a design provocation that centers aides' needs and suggests more equitable roles for them within the home care ecosystem. Findings from design sessions with 16 aides, nurses, and aide coordinators illuminate the ethical and pragmatic dilemmas inherent in this complex ecosystem, and show that designing technology for equity requires attention to structural problems in addition to workers' stated needs. We analyze our findings through the lens of social justice-oriented interaction design, and discuss how our work extends key strategies within this framework.

Home health aides (HHAs) increasingly being used by adults with heart failure for long-term assistance and post-hospitalization care. Despite being heavily involved in numerous aspects of heart failure management, most HHAs have not received heart failure training. They also struggle to get in touch with supervising nurses or other members of the care team when they have clinical questions, which may result in unnecessary visits to the emergency room. In addition, despite serving as a backbone in the health system for patients, HHAs, who are mostly women and minorities, are a marginalized and vulnerable group of frontline caregivers, enduring erratic employment, low wages, discrimination, and high levels of burnout. Although digital technologies could help to address many of the challenges HHAs face, little is known about the current impact of technology on HHAs work practices. To this end, we conducted a multi-stakeholder qualitative study with 38 participants in New York City using semi-structured interviews and focus groups. We uncover the ways in which technology is used, the complex socio-technical factors that underpin heart failure care, and stakeholder suggestions for how technology could improve HHAs work. Building on these insights, we synthesize design opportunities for researchers and designers interested in developing tools that support the delivery of home health care for patients suffering from life-threatening diseases like heart failure.