Families raising children with ADHD often experience heightened stress and reactive parenting. While digital interventions promise personalization, many remain one-size-fits-all and fail to reflect parents’ lived practices. We present CalmReminder, a watch-based system that detects children’s calm moments and delivers just-in-time prompts to parents. Through a four-week deployment with 16 families (twelve completed) of children with ADHD, we compared notification strategies ranging from hourly to random to only when the child was inferred to be calm. Our sensing-based notifications were frequently perceived as arriving during calm moments. More importantly, parents adopted the system in diverse ways: using notifications for praise, mindfulness, activity planning, or conversation. These findings show that parents are not passive recipients but active designers, reshaping interventions to fit their parenting styles. We contribute a calm detection pipeline, empirical insights into families’ flexible appropriation of notifications, and design implications for intervention systems that foster agency.

Artificial intelligence (AI) is deepening human social experiences within online spaces in increasingly layered ways. Amid these shifts, we designed AmongOthers, an online community populated with 800 AI agents, and rethought human–AI social interactions. Eight participants engaged with AmongOthers for four weeks. For the first two weeks, they were told the community was exclusively for immigrants and international students, after which we disclosed that most users were AI agents. Participants shared periodic reflections and later joined interviews. Initially, AmongOthers was described as warm and respectful. However, after disclosure, participants diverged in their attitudes toward AI in online social communities, ranging from embracing and denying to imagining it only as a conditional possibility. We discuss these tensions in human perceptions of AI and highlight the risks of framing AI as failed replicas or preferable proxies. We finally suggest rethinking AI as distinct social entities in their own right.

Peer Reviewed

Children typically learn to identify and express their emotions by sharing stories and feelings with others, particularly family members. However, it is challenging for parents or siblings to have effective emotion communication with children since children are still developing their communication skills. We present ChaCha, a chatbot that encourages and guides children to share personal events and associated emotions. ChaCha combines a state machine and large language models (LLMs) to keep the dialogue on track while carrying on free-form conversations. Through an exploratory study with 20 children (aged 8–12), we examine how ChaCha prompts children to share personal events and guides them to describe associated emotions. Participants perceived ChaCha as a close friend and shared their stories on various topics, such as family trips and personal achievements. Based on the findings, we discuss opportunities for leveraging LLMs to design child-friendly chatbots to support children in sharing emotions.

Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling. However, there is a lack of a comprehensive public dataset that serves as an open testbed for fair comparison among algorithms. Moreover, prior studies mainly evaluate algorithms using data from a single population within a short period, without measuring the cross-dataset generalizability of these algorithms. We present the first multi-year passive sensing datasets, containing over 700 user-years and 497 unique users’ data collected from mobile and wearable sensors, together with a wide range of well-being metrics. Our datasets can support multiple cross-dataset evaluations of behavior modeling algorithms’ generalizability across different users and years. As a starting point, we provide the benchmark results of 18 algorithms on the task of depression detection. Our results indicate that both prior depression detection algorithms and domain generalization techniques show potential but need further research to achieve adequate cross-dataset generalizability. We envision our multi-year datasets can support the ML community in developing generalizable longitudinal behavior modeling algorithms.

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 the 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.

Live streaming refers to the broadcast of real-time videos, allowing people to have synchronous interactions. While researchers' interest in live streaming has increased recently, the accessibility of live streaming for people with visual impairments is still under-examined. Further studies are necessary to gain a better understanding of how streamers with visual impairments (SVI) engage in various activities on live streaming platforms. Based on semi-structured interviews with 14 participants, we identified SVI's motivations for live streaming, their unique interactions with videos and people on live streaming platforms, and the challenges they face during live streaming. Our analysis of the identified themes revealed the absence of an SVI-centered community and accessibility issues for SVI while learning to live stream, use tools, and interact with people. Based on the results of this study, we present design opportunities to better support SVI on live streaming platforms.

Previous works have shown that effective communication between parental caregivers and child patients has many benefits to the children, such as providing emotional support and coping skills for health management. Drawing on semi-structured interviews, we have identified the challenges parental caregivers face when communicating with their children about health-related information in daily illness management. Three salient challenges that the parental caregivers encountered include: (i) acknowledging different perceptions and approaches to being a cancer patient, (ii) choosing an appropriate communication method, and (iii) understanding their child's uncommunicated emotions. Based on these challenges, we recognize distinctive, yet implicit, needs that children develop during the illness trajectory, affecting the parent-child dyadic relationship. We discuss design opportunities for a collaborative system that enhances the parent-child dyadic communication by supporting the child's implicit and dynamically changing needs throughout the illness trajectory and beyond.

The diagnosis of cancer brings about significant changes in the life of a child. In addition to physical pain, pediatric patients face psychological and social challenges. At the same time, some patients also have positive experiences with and attitudes toward their illness and treatment. Drawing on 19 semi-structured interviews with pairs of pediatric cancer patients and their parental caregivers, we examined patients' perspectives on their experience of living with cancer. We identified four salient themes in patients' positive experiences: future-oriented thinking, developing strong personal bonds and relationships, gaining knowledge and life experience, and developing self-management and coping skills. Collectively, the patients' positive experiences indicate that they adapt to their new lives through an evolving process. Based on this process, we provide design implications for health technologies to support and promote positive experiences during illness and treatment.

A deep understanding of how discrimination impacts psychological health and well-being of students could allow us to better protect individuals at risk and support those who encounter discrimination. While the link between discrimination and diminished psychological and physical well-being is well established, existing research largely focuses on chronic discrimination and long-term outcomes. A better understanding of the short-term behavioral correlates of discrimination events could help us to concretely quantify such experiences, which in turn could support policy and intervention design. In this paper we specifically examine, for the first time, what behaviors change and in what ways in relation to discrimination. We use actively-reported and passively-measured markers of health and well-being in a sample of 209 first-year college students over the course of two academic quarters. We examine changes in indicators of psychological state in relation to reports of unfair treatment in terms of five categories of behaviors: physical activity, phone usage, social interaction, mobility, and sleep. We find that students who encounter unfair treatment become more physically active, interact more with their phone in the morning, make more calls in the evening, and spend more time in bed on the day of the event. Some of these patterns continue the next day. Our results further our understanding of the impact of discrimination and can inform intervention work.

In pediatric chronic care, the treatment process affects not just the child's physical health, but his or her psychosocial and emotional development. As a result, caring for pediatric patients with a chronic illness such as cancer is becoming a daunting task for parental caregivers. They are expected to fulfill the caregiving needs of managing the child's health condition and treatment while also meeting the parenting needs of translating knowledge, communicating about the illness, and making numerous decisions on a daily basis for their sick child due to the child's young age. Drawing on 15 semi-structured interviews, we examined parental caregivers' perspectives on raising a child while also managing the child's health. We identified three tensions that participants encountered as they balanced parenting and caregiving responsibilities: (i) tension between ensuring the child's health and safety and attending to the child's social development, (ii) tension between disclosing health-related information and minimizing the psychological burden on the child, and (iii) tension between rewarding the child's cooperation in treatment and maintaining discipline. Together, these tensions reveal an ongoing process through which caregivers assess and interpret their actions and responsibilities relative to anticipated consequences across multiple time scales. These findings reveal opportunities for sociotechnical systems to account for and support this active process of iterative cycles of assessment.

We explore a community of blind or visually impaired (BVI) people through video blogs (vlogs) on YouTube. Many researchers have used vlogs as a means of identifying communities of video bloggers (vloggers). Nevertheless, little is still known about how BVI vloggers interact through vlogs in video-based social media. To fill the gap, we identified BVI vloggers and types of the vlogs they produced by analyzing videos on YouTube. Also, we found how BVI vloggers were connected with each other through vlogs. To our knowledge, this is the first attempt utilizing vlogs to understand the community of BVI people on YouTube.