While AI chatbots have been proposed to support wheelchair provision services in low- and middle-income countries (LMICs), the perception of physical therapists regarding how they could be integrated into their service workflow remains unclear. We conducted semi-structured interviews with 11 professionals from Africa and South Asia, using two design probes to investigate the potential and limitations of using chatbots in their everyday wheelchair assessment services. Our findings revealed 13 tensions that arise when the envisioned chatbot use misaligns with three interconnected domains - professional values, practice structures, and contextual readiness, such as conflicts in professional autonomy, evolving responsibilities, and confidence in AI. To guide more situated chatbot design, we proposed a tension-informed design framework that centers professional practice and surfaces tensions as opportunities rather than barriers. We discuss how introducing chatbots in LMICs should aim to amplify professionals’ capacity and align with the nature of assistive technology services.

Positionality is a concept that acknowledges subjectivities, values and experiences of researchers as influencing approaches to and outcomes and implications of research; it underlines the importance of reflexivity and self-awareness. To understand how positionality is used in HCI, we conducted two studies: (i) a scoping review of positionality and reflexivity statements in the CHI papers in the last 11 years and (ii) a survey of HCI researchers (n=75). Our findings show that positionality statements are often a box-ticking exercise and their influence on the research is rarely discussed. While positionality statements are often used and requested in papers, they are often restricted to more sensitive areas of research and impact marginalised identities. We argue that positionality statements can be valuable but not as markers of methodological rigour. Our contributions include a current snapshot of positionality in HCI and reflections on the role of positionality statements in HCI.

Paper-based journaling remains ubiquitous and provides significant potential to support mental wellbeing and inform the design of digital mental health interventions. However, it remains unclear how tangible tools can be designed to facilitate creative and artistic journaling practices. We present the design and evaluation of a tangible toolkit comprising a set of laser-cut stencils and an example-based how-to guide on self-tracking mood through mindful colouring. Drawing on the findings of a two-week field study with university students from diverse backgrounds, we demonstrate how the tangible toolkit scaffolded personally meaningful expression of mood and lived experience. Participant’s visual accounts illustrate creative stencil appropriation and individual colouring preferences in documenting and understanding mood, emotions, and feelings in daily life. Based on this understanding, we suggest shifts towards more tangible mental health approaches to support people in expressing and exploring their felt experiences in creative ways.

Interactive Machine Learning (IML) enables users, including non-experts in ML, to iteratively train and improve ML models. However, limited research has been reported on how non-experts interact with these systems. Focusing on thematic analysis as a practical application, we report on a user study where 20 participants interacted with TACA, a functioning IML tool. Thematic analysis involves individual interpretation of ambiguous data, hence it is suited for and can benefit from the iterative customization of models supported by IML. Through a combination of interaction logs and semi-structured interviews, our findings revealed that, by using TACA, participants critically reflected on their analysis, gained new thematic insights, and adapted their interpretative stance. We also document misconceptions of ML concepts, positivist views, and personal blame for poor model performance. We then discuss how applications could be designed to improve the understanding of IML concepts and foster reflexive work practices.

Flexible working, including in resource-constrained settings such as long-haul flights, poses considerable challenges. While research in mixed reality (MR) offers the potential for enhancing experiences of working on airplanes (WoA), what input modalities and interactions might be suitable for such workspaces is under-explored. To address this gap, we created four design probes and demonstrated their interactions within MR for WoA using a branching decision-based interactive video. 24 participants engaged in the think-aloud study with the video where they selected which probe to watch based on personal preference and order. The follow-up interview further solidified their general preferences for intuitive and friction-free inputs, revealed strong concerns about reliability, discreetness, and portability, and showed high enthusiasm for interactive video. Based on these findings, we contribute a context-driven design space of input modalities for WoA in MR, extending the understanding of design opportunities for inputs with MR in confined spaces.

Engaging end user groups with machine learning (ML) models can help align the design of predictive systems with people's needs and expectations. We present a co-design study investigating the benefits and challenges of using computational notebooks to inform ML models with end user groups. We used a computational notebook to engage young adults, carers, and clinicians with an example ML model that predicted health risk in diabetes care. Through co-design workshops and retrospective interviews, we found that participants particularly valued using the interactive data visualisations of the computational notebook to scaffold multidisciplinary learning, anticipate benefits and harms of the example ML model, and create fictional feature importance plots to highlight care needs. Participants also reported challenges, from running code cells to managing information asymmetries and power imbalances. We discuss the potential of leveraging computational notebooks as interactive co-design tools to meet end user needs early in ML model lifecycles.

Social virtual reality (VR) platforms have increased in popularity with many people turning to these platforms to experience social connection, including a rapid influx of users during the COVID-19 pandemic. However, there is limited understanding of how people appropriate and use emerging social VR applications to actively support their mental health and wellbeing in daily life. Through an online questionnaire and exploratory interviews conducted within the social VR app VRChat during the COVID-19 pandemic, we document how social VR is being used explicitly as a mental health support tool. Participants reported positive wellbeing benefits, mostly attributed to the anonymity provided by avatars and perceived safety within digital worlds and communities of practice. We also report how people use social VR to practice social interaction, reduce negative thoughts and form strong social bonds and connections with others.

Whilst the use of smart home systems has shown promise in recent years supporting older people's activities at home, there is more evidence needed to understand how these systems impact the type and the amount of shared care in the home. It is important to understand care recipients and caregivers' labour is changed with the introduction of a smart home system to efficiently and effectively support an increasingly aging population with technology. Five older households (8 participants) were interviewed before, immediately after and three months after receiving a Smart Home Health System (SHHS). We provide an identification and documentation of critical incidents and barriers that increased inter-household care work and prevented the SHHS from being successfully accepted within homes. Findings are framed within the growing body of work on smart homes for health and care, and we provide implications for designing future systems for shared home care needs.

Type 1 Diabetes (T1D) self-management requires hundreds of daily decisions. Diabetes technologies that use machine learning have significant potential to simplify this process and provide better decision support, but often rely on cumbersome data logging and cognitively demanding reflection on collected data. We set out to use co-design to identify opportunities for machine learning to support diabetes self-management in everyday settings. However, over nine months of interviews and design workshops with 15 people with T1D, we had to re-assess our assumptions about user needs. Our participants reported confidence in their personal knowledge and rejected machine learning based decision support when coping with routine situations, but highlighted the need for technological support in the context of unfamiliar or unexpected situations (holidays, illness, etc.). However, these are the situations where prior data are often lacking and drawing data-driven conclusions is challenging. Reflecting this challenge, we provide suggestions on how machine learning and other artificial intelligence approaches, e.g., expert systems, could enable decision-making support in both routine and unexpected situations.

Explaining health technology platforms to non-technical members of the public is an important part of the process of informed consent. Complex technology platforms that deal with safety-critical areas are particularly challenging, often operating within private domains (e.g. health services within the home) and used by individuals with various understandings of hardware, software, and algorithmic design. Through two studies, the first an interview and the second an observational study, we questioned how experts (e.g. those who designed, built, and installed a technology platform) supported provision of informed consent by participants. We identify a wide range of tools, techniques, and adaptations used by experts to explain the complex SPHERE sensor-based home health platform, provide implications for the design of tools to aid explanations, suggest opportunities for interactive explanations, present the range of information needed, and indicate future research possibilities in communicating technology platforms.

A detailed understanding of the mental health needs of people from refugee backgrounds is crucial for the design of inclusive mental health technologies. We present a qualitative account of the digital mental health experiences of women from refugee backgrounds. Working with community members and community workers of a charitable organisation for refugee women in the UK, we identify social and structural challenges, including loneliness and access to mental health technologies. Participants' accounts document their collective agency in addressing these challenges and supporting social connectedness and personal wellbeing in daily life: participants reported taking part in community activities as volunteers, sharing technological expertise, and using a wide range of non-mental health-focused technologies to support their mental health, from playing games to supporting religious practices. Our findings suggest that, rather than focusing only on individual self-care, research also needs to leverage community-driven approaches to foster social mental health experiences, from altruism to connectedness and belonging.

The COVID-19 2020 lockdown measures altered how families spent time together, with many fathers adopting new household roles and spending more time with their children. This paper contributes an empirical account of technology use and fatherhood during the COVID-19 pandemic, and draws implications for the design of technologies to support fathers. We outline the findings from semi-structured interviews carried out with fathers during lockdown in the UK. Initial interviews (n=19) highlighted challenges in screen viewing, family dynamics, idea generation and self-care. This informed the design of four prototype apps to enrich follow-up interviews (n=12), using these prototypes as prompts to explore the emergent challenges in more depth. The interviews identified significant changes and concerns related to technology use within the context of COVID-19, with new roles for fathers conflicting with traditional ones combined with situational stressors to amplify issues with guilt, shame and self-care related to technology use.

Although the use of voice assistants to support older adults at home shows promise, little is known about how the next generation of these devices, which also include displays, can support health and care needs. This question has become more important during COVID-19, when issues of social isolation for older adults have been exacerbated. During social distancing measures in the UK, eleven older adult households (16 participants) were interviewed before receiving an Amazon Echo Show, shortly after receiving it, and after three months of use. We identify ways in which this multi-modal device is used by people in social isolation to support social, care, and information needs in the home. We frame these findings within the growing research area of smart homes for health and care, and provide implications for the adoption, use and acceptance of these devices to support aging in place together.

Gaining an understanding of people's diverse mental health needs is essential for informing the design of inclusive mental health technologies. However, conversations about mental health experiences can be challenging for both researchers and participants. We present the design of visual cards that illustrate an inclusive mental health concept to support researchers and participants in understanding and sharing mental health experiences. We illustrate the iterative design of the visual cards with our reflections and feedback from ethnically diverse participants. We found that designing the visual cards fostered insightful reflections within the design team regarding the roles of identity, gender, and ethnicity in designing culturally sensitive content and research. Participants from minority ethnic backgrounds valued the illustrative elements of the visual cards and highlighted the importance of supporting different languages and visual cultures. We discuss use cases for the visual cards and implications for designing culturally sensitive mental health technologies.

Co-design is a widely applied design process with well-documented values, including mutual learning and collective creativity. However, the real-world challenges of conducting multidisciplinary co-design research to inform the design of self-care technologies are not well established. We provide a qualitative account of a multidisciplinary project that aimed to co-design machine learning applications for Type 1 Diabetes (T1D) self-management. Through interviews, we identify not only perceived social, technological and strategic benefits of co-design but also organisational, translational and pragmatic design challenges: participants with T1D experienced difficulties in co-designing systems that met their individual self-care needs as part of group activities; HCI and AI researchers described challenges resulting from applying co-design outcomes to data-driven ML work; and industry collaborators highlighted academic data sharing regulations as cross-organisational challenges that can impede co-design efforts. Based on this understanding, we discuss opportunities for supporting multidisciplinary collaborations and aligning individual health needs with collaborative co-design activities.

Stairlifts are a widely-used technology in the home that help people with mobility issues to go up and down stairs. However, it is unclear how stairlifts are experienced by all household members and what this understanding implies for home healthcare technologies. We investigated the impact of stairlift installations on older adults' households in the UK through a qualitative study investigating the lived experience of the adoption and acceptance of this technology. Interviews and focus groups with primary users, household residents and service providers showed how the wider household identify misalignments between simplified stairlift installation models from service providers and describe a more complex, nuanced emotional journey which involves decision making, conflict and trauma and catharsis and independence. Findings provide transferrable outcomes for the smart home domain by highlighting the multi-resident home, the emotional intrusiveness of home healthcare technologies and the diversity that comes with providing care, unique to every household.

Self-tracking is an important part of self-care. However, predefined self-tracking approaches can impede people's agency in managing their health. We investigated a customisable and pictorial self-tracking approach in multiple sclerosis self-management by implementing and conducting a field study of Trackly: a prototype app that supports people in defining and colouring pictorial trackers, such as body shapes. We found that participants utilised the elements of Trackly designed to support agentive behaviour: they defined personally meaningful tracking parameters in their own words, and particularly valued being able to flexibly colour in and make sense of their pictorial trackers. Having been able to support their individual self-care intentions with Trackly, participants reported a spectrum of interrelated experiences of agency, including a sense of ownership, identity, self-awareness, mindfulness, and control. Our findings demonstrate the importance of supporting people's individual needs and creative capacities to foster mindful and personally meaningful engagement with health and wellbeing data.

Digital self-tracking technologies offer many potential benefits over self-tracking with paper notebooks. However, they are often too rigid to support people's practical and emotional needs in everyday settings. To inform the design of more flexible self-tracking tools, we examine bullet journaling: an analogue and customisable approach for logging and reflecting on everyday life. Analysing a corpus of paper bullet journal photos and related conversations on Instagram, we found that individuals extended and adapted bullet journaling systems to their changing practical and emotional needs through: (1) creating and combining personally meaningful visualisations of different types of trackers, such as habit, mood, and symptom trackers; (2) engaging in mindful reflective thinking through design practices and self-reflective strategies; and (3) posting photos of paper journals online to become part of a self-tracking culture of sharing and learning. We outline two interrelated design directions for flexible and mindful self-tracking: digitally extending analogue self-tracking and supporting digital self-tracking as a mindful design practice.

Consumer health technologies have an enormous potential to transform the self-management of chronic conditions. However, it is unclear how individuals use self-tracking technologies to manage them. This in-depth interview study explores self-tracking practices in multiple sclerosis (MS), a complex neurological disease that causes physical, cognitive, and psychological symptoms. Our findings illustrate that when faced the unpredictable and degenerative nature of MS, individuals regained a sense of control by intertwining self-care practices with different self-tracking technologies. They engaged in disease monitoring, fitness tracking, and life journaling to quantify the body and care for the mind. We focus attention on the role of emotional wellbeing and the experience of control in self-tracking and managing MS. Finally, we discuss in which ways self-tracking technologies could support the experiential nature of control and foster mindful experiences rather than focusing only on tracking primary disease indicators.