開始時刻
前のセッションの直後
この勉強会は終了しました。ご参加ありがとうございました。
As the global population ages and the prevalence of chronic conditions and acute infections rise, it is becoming imperative to understand the many forms of caregiving labor and create sociotechnical systems that support them. In this paper, we report results of a large survey study with 2000 informal caregivers in the USA, highlighting the fundamental challenges that different types of caregivers face when coordinating care with others. Our findings support previous findings on caregivers' coordination challenges, while also offering insights into the situational, mediating factors that influence the extent to which care coordination challenges are felt. These mediating factors include caregivers' relationships, access to a variety of resources including physical, social, and financial support, and physical and mental barriers. We discuss these challenges and mediating factors, and conclude with a discussion on how they can be considered in the design of future sociotechnical systems.
During a global pandemic such as COVID-19, laypeople bear a large burden of responsibility for assessing risks associated with COVID-19 and taking action to manage risks in their everyday lives, yet epidemic-related information is characterized by uncertainty and ambiguity. People perceive risks based on partial, changing information. We draw on crisis informatics research to examine the multiple types of risk people perceive in relation to the COVID-19 pandemic, the information sources that inform perceptions of COVID-19 risks, and the challenges that people have in getting the information they need to understand risks, using qualitative interviews with individuals across the United States. Participants describe multiple pandemic-related threats, including illness, secondary health conditions, economic, socio-behavioral, and institutional risks. We further uncover how people draw on multiple information sources from technological infrastructures, people, and spaces to inform the types of their risk perceptions, uncovering deep challenges to acquiring needed risk information.
Medical making intersects opposing value systems of a medical ``do no harm'' ethos and makers' drive to innovate. Since March 2020, online maker communities have formed to design, manufacture, and distribute personal protective equipment (PPE) and other medical devices needed to fight the COVID-19 pandemic. We present a participant observation study of 14 maker communities, which have developed differing driving principles for efforts with varied access to interdisciplinary expertise on online platforms that mutually shape collective action. Over time, these communities unintentionally align towards action-oriented or regulated practices because they often lack higher level insight and agency in choosing communication platforms. In response, we recommend: regulatory bodies to build coalitions with makers, online platforms to give communities more control over the presentation of information, and repositories to balance needs to distribute information while limiting the spread of misinformation.
Dementia affects over 50 million worldwide, causing progressive cognitive and physical disabilities. Its caregiving burden falls largely onto informal caregivers, who experience their own health problems, and face tremendous stress with little support--all exacerbated during COVID-19. In this paper, we present a new caregiver support perspective, where the lenses of health equity and community health can shape future technology design. Through a 1.5 year long, in-depth research process with dementia community health workers, we learned how caregiving support technology can reflect key concepts in dementia community health practice. This paper makes two contributions: 1) We propose employing embodied cueing, such as imitation or action mimicry, as a communication modality that can align technology with community caregiving approaches, promote agency in people with dementia, and relieve caregiver burden, and 2) We suggest new avenues for HCI research to advance health equity in the context of dementia technology design.
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.
Conversational agents (CAs) such as Google Home or Alexa offer empowering opportunities for dyads composed of older adults with mild cognitive impairment (MCI) and their care partners. CAs support coordination and planning between the two, and can amplify the support that the care partner needs to provide. In this study, we observed how ten such dyads interacted with a Google Home over 10 weeks. We logged and analyzed 3,878 total interactions, interviewed the dyads to better understand their experiences, and also surveyed their individual preferences and priorities for automated assistance in the home. We found that CAs empowered both the people who had MCI, and their care partners. We observed that the utility of the CA in the day-to-day lives of users largely depended on how much the care partner scaffolded promising functionality, contextualizing it for specific needs and desires.
Recently, digital scribe systems have been gaining popularity as a possible work-around solution to the Electronic Medical Record (EMR) documentation burden that affects many physicians. The proposed system would automate the clinical summary physicians take by capturing and extracting the patient-physician conversation during the consultation. While promising in concept, how this system would apply to real-world use and its limitations are still not well understood. To examine these issues, we designed a digital scribe prototype to generate notes of different qualities ranging from the reality of current state-of-the-art technology to the potential of future implementations. We conducted a "Wizard of Oz" study with 24 primary care physicians using our digital scribe prototype in 4 simulated medical encounters followed by a semi-structured interview. This exploratory study provides an understanding of physicians' interaction with digitally scribed notes, their perceptions on note quality, their perceived workflow impact and several directions for improvements.
Major depressive disorder is a debilitating disease affecting 264 million people worldwide. While many antidepressant medications are available, few clinical guidelines support choosing among them. Decision support tools (DSTs) embodying machine learning models may help improve the treatment selection process, but often fail in clinical practice due to poor system integration.
We use an iterative, co-design process to investigate clinicians’ perceptions of using DSTs in antidepressant treatment decisions. We identify ways in which DSTs need to engage with the healthcare sociotechnical system, including clinical processes, patient preferences, resource constraints, and domain knowledge. Our results suggest that clinical DSTs should be designed as multi-user systems that support patient-provider collaboration and offer on-demand explanations that address discrepancies between predictions and current standards of care. Through this work, we demonstrate how current trends in explainable AI may be inappropriate for clinical environments and consider paths towards designing these tools for real-world medical systems.
Effective patient-provider communication is critical to promote patient satisfaction, encourage patient involvement in care, and improve health outcomes. Although prior HCI works aim to enhance dyadic communication by improving patients’ communication skills, little is known about healthcare providers’ communication work to facilitate effective communication with their child patients. Through semi-structured interviews with 10 healthcare providers and clinic observations, our study identified four strategies that providers used in their communication with patients: building rapport, developing familiarity with care settings, respecting patients’ communication modes and preferences, and delegating small decision-making and directing questions to patients. Based on these strategies, we discuss three key elements that providers value and work toward to achieve effective communication in pediatric care practice. Our study also uncovers the detailed process of how the providers develop their strategies to tailor their communication to the patients’ specific needs and preferences, and we describe design opportunities for communication technology.
Telerehabilitation systems for stroke survivors have been predominantly designed to measure and quantify movement in order to guide and encourage rehabilitation regular exercises at home. We set out to study what aspect of the movement data was essential, to better inform sensor design. We investigated face-to-face stroke rehabilitation sessions through a series of interviews and observations involving 16 stroke rehabilitation specialists including physiatrists, physical therapists, and occupational therapists. We found that specialists are not solely interested in movement data, and that experiential information about stroke survivors' lived experience plays an essential role in specialists interpreting movement data and creating a rehabilitation plan. We argue for a reconceptualization in stroke telerehabilitation that is more inclusive of non-movement data, and present design implications to better account for experiential information in telerehabilitation systems.
Traumatic injuries require timely intervention, but medical expertise is not always available at the patient's location. Despite recent advances in telecommunications, surgeons still have limited tools to remotely help inexperienced surgeons. Mixed Reality hints at a future where remote collaborators work side-by-side as if co-located; however, we still do not know how current technology can improve remote surgical collaboration. Through role-playing and iterative-prototyping, we identify collaboration practices used by expert surgeons to aid novice surgeons as well as technical requirements to facilitate these practices. We then introduce ARTEMIS, an AR-VR collaboration system that supports these key practices. Through an observational study with two expert surgeons and five novice surgeons operating on cadavers, we find that ARTEMIS supports remote surgical mentoring of novices through synchronous point, draw, and look affordances and asynchronous video clips. Most participants found that ARTEMIS facilitates collaboration despite existing technology limitations explored in this paper.