Less Supervising, More Caring: Design Recommendations for Informal Caregivers' Co-Participation in Cardiac TelerehabilitationInformal caregivers’ engagement with patient data is becoming increasingly central to CSCW and HCI research on health management. Cardiac telerehabilitation (CTR) technologies generate lifestyle and well-being data that support patients and their families in recovery management, yet informal caregivers' roles in CTR remain underexplored. Recreational athletes in rehabilitation are an especially under-researched group, despite their and their support system's unique needs. Focusing on caregivers of recreational athletes, we conducted interviews with ten participants and used six visual scenarios of a dyadic CTR system to explore their perspectives on data and information co-participation. Caregivers reported that co-participation could strengthen dyadic coping and management but emphasized the need to balance important trade-offs. We provide design recommendations for dyadic CTR systems that balance care needs and preferences, promoting caregiver involvement in a supportive, non-supervisory role. We contribute to CSCW research by proposing a conceptual shift in technology-mediated rehabilitation care: positioning caregiver-inclusive CTR systems as negotiation tools that support boundary work and balance competing care values.2025ISIrina Bianca Serban et al.Caregiving & CaregiversCSCW
In-person, Online and Back Again - A Tale of Three Hybrid HackathonsHybrid hackathons, which combine in-person and online participation, present unique challenges for organizers and participants. Although these events are increasingly conducted globally, research on them remains fragmented, with limited integration between hackathon studies and hybrid collaboration. Existing strategies for in-person or online-only events often fail to address the unique challenges of hybrid formats, such as managing communication across physical and virtual spaces and ensuring balanced participation. Our work addresses this gap by examining how hybrid hackathons function through the lens of hybrid collaboration theories, analyzing how organizers structure these events and how participants navigate hybrid-specific challenges. Drawing on established theories of hybrid collaboration, we examine key dimensions -- synchronicity, physical distribution, dynamic transitions, and technological infrastructure -- that shape collaboration in hybrid events. Through an exploratory case study of three hackathon events involving observations and interviews with organizers and participants, we analyze how these dimensions are implemented and their effects on participant experiences. Our findings reveal differing organizer considerations of the hybrid dimensions in the hackathon design, leading to distinct experiences for participants. Implementation styles -- favoring in-person, online, or balanced participation -- led to varied participant experiences, affecting access to resources, communication, and team coordination. Organizers in our study also often relied on technology to bridge hybrid interactions, but sometimes overlooked critical aspects like time-zone management, dynamic transitions, and targeted support for hybrid teams. Additionally, participants in their teams responded to gaps in event scaffolding by adapting collaboration strategies, underscoring that hybrid formats are still not fully integrated into hackathon planning and revealing gaps in organizers’ preparedness for hybrid events. Learning from our findings, we offer practical recommendations when organizing hybrid hackathon events and recommendations to participants when attending hybrid hackathon events.2025AAAbasi-Amefon Obot Affia et al.Hybrid WorkCSCW
What's Happening in the Office: Designing Information Displays for Human-Like Experience to Promote Workspace Awareness in Hybrid WorkWith the rise of hybrid office work, employees often miss workspace awareness when working remotely at home, causing feelings of isolation and preventing communication. To address this, we propose designing information displays that present office activities to promote workspace awareness for hybrid workers. We focus on creating human-like experiences—enabling users to easily perceive information, feel social presence, and make sense of information in context. Informed by previous CSCW research findings, we identified three key design considerations: social cues as information carriers, processing ambiguity, and ambient delivery. Guided by these considerations, we generated multiple designs and selected three distinct ones for evaluation of such experiences in a lab study, where 24 participants experienced and compared the designs. Our analysis shows that these designs indeed provide situational awareness and social presence. The results also offer insights into optimizing design options for different goals. Further research is needed to explore their integration with interactive features and into daily workflows.2025LLLu Liu et al.Hybrid WorkCSCW
Enhancing Cyclist Safety in the EU: A Study on Lateral Overtaking Distance Across Seven Scenarios Using Lab and Crowdsourced MethodsCyclists face significant risks from vehicles that overtake too closely. Through crowdsourcing (N = 200) and driving simulator (N = 20) experiments, this study examines driver behaviour in seven scenarios: laser projection, road sign, road marking, car projection, centre line and side line markings (baseline), cycle lane and no road markings. Crowdsourced participants consistently underestimated overtaking distances, particularly at wider gaps, despite feeling safer with greater distances. The simulation results showed that drivers maintained an average passing distance of 3.4~m when not constrained by traffic, exceeding the 1.5~m law of the European Union. However, interventions varied in effectiveness: while laser projection was preferred, it did not significantly increase passing distance. In contrast, a dedicated cycle lane and a solid centreline led to the greatest improvements. These findings highlight the discrepancies between perceived and actual safety and provide insight for policy interventions to enhance cyclist protection in the EU.2025GSGiovanni Sapienza et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsV2X (Vehicle-to-Everything) Communication DesignPedestrian & Cyclist SafetyAutoUI
Pedestrian Planet: What YouTube Driving from 233 Countries and Territories Teaches Us About the WorldPedestrian crossing behaviour varies globally. This study analyses dashcam footage from the PYT dataset, covering 133 countries, to examine decision time to cross, crossing speed, and contextual variables, including detected vehicles, traffic mortality, GDP, and Gini. Bulgaria had the longest decision time (10.50 s), while San Marino exhibited the fastest crossing speed (1.14m/s). A global negative correlation between speed and decision time (r = -0.54) suggests that more cautious or uncertain pedestrians cross more slowly. Regional differences reveal stronger inverse correlations in Europe and North America, likely due to varying infrastructure, regulation, and cultures. Pedestrian decision time is positively correlated with the presence of other road users, especially bicycles (r = 0.35). Similar crossing times in countries with different infrastructures, such as Belgium and India, underscore the complex interaction between infrastructure and behavioural adaptation. These findings emphasise the importance of culturally aware road design and the development of adaptive interfaces for vehicles.2025MAMd Shadab Alam et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsV2X (Vehicle-to-Everything) Communication DesignPedestrian & Cyclist SafetyAutoUI
Socially Adaptive Autonomous Vehicles: Effects of Contingent Driving Behavior on Drivers' ExperiencesSocial scientists have argued that autonomous vehicles (AVs) need to act as effective social agents; they have to respond implicitly to other drivers' behaviors as human drivers would. In this paper, we investigate how contingent driving behavior in AVs influences human drivers' experiences. We compared three algorithmic driving models: one trained on human driving data that responds to interactions (a familiar contingent behavior) and two artificial models that intend to either always-yield or never-yield regardless of how the interaction unfolds (non-contingent behaviors). Results show that a familiar contingent behavior significantly reduces drivers' hesitance and stress when interacting with AVs. The direct relationship between familiar contingency and positive experience indicates that AVs should incorporate socially familiar driving patterns through contextually-adaptive algorithms to improve the chances of successful deployment and acceptance in mixed human-AV traffic environments.2025CYChishang "Mario" Yang et al.Automated Driving Interface & Takeover DesignAI-Assisted Decision-Making & AutomationAutoUI
What Researchers Need from Driving Simulator Systems: A Thematic Analysis of Expert InterviewsAutomotive researchers face challenges using diverse driving simulator tools to address their research questions. This paper aims to identify the needs in current driving simulator systems. Numerous driving simulator systems are available and are continuing to be developed, but researchers' needs are often overlooked in the development of such systems. To determine the challenges in this, we conducted 15 video interviews with industry and academic researchers engaged in automotive interface design research, transcribed the interviews, and performed thematic analysis. We identified needs across three broad dimensions including: (1) participant experience, (2) research needs, and (3) operationalization requirements. By categorizing these needs, we aim to inform the development of future simulation tools that are more accessible to researchers from diverse backgrounds.2025SLStacey Li et al.Prototyping & User TestingField StudiesAutoUI
SPAT: Situational Prosocial and Aggressive Behavior Perception in Traffic ScaleAutomated vehicles (AVs) reached technological maturity and will soon arrive on streets as traffic participants. Human traffic participants such as drivers, pedestrians, or cyclists will be increasingly confronted with the presence of AVs within their environment, not necessarily knowing or understanding what to expect and how to interact with them. Although AVs are designed to act safely, effective interaction in mixed traffic scenarios will depend on successful communication, interaction, or even negotiation beyond static rules and regulations. Prosocial behavior, such as yielding one's right of way, will be needed to resolve unclear traffic situations or foster traffic flow. However, what are the characteristics of such prosocial behavior, and how to measure this not only for automated vehicles but for all road users? Here, we describe a new scale to measure perceived social behavior in urban traffic scenarios. Through an online survey on \textit{N} = 318 individuals and a validation study, we developed the Situational Prosocial and Aggressive Behavior in Traffic Scale and assessed it psychometrically.2025HİHatice Şahin İppoliti et al.Teleoperated DrivingV2X (Vehicle-to-Everything) Communication DesignAI-Assisted Decision-Making & AutomationAutoUI
Let’s Talk Menopause: Promoting Intergenerational Dialogue about Menopause through DesignMenopause is an important life transition characterised by physiological, emotional, and social changes. It is surrounded by stigma and taboo. Thus, conversations about menopause are often rare, even among family members, and people often don’t know what to expect from menopause. We leverage design and collaborative making to promote (intergenerational) communication about menopause, between mothers and daughters, and between members of a broader audience. We describe a collaborative Research through Design process where we collaborated with six mother-daughter dyads to create material representations capturing and describing their diverse menopause experiences. Iterating on these representations, we designed and exhibited 5 interactive artifacts at Dutch Design Week 2024. We contribute with empirical findings on plural experiences around menopause, present the five artifacts built upon these experiences, and discuss the importance of pluralizing narratives around menopause through design.2025DODaisy O'Neill et al.Empowerment of Marginalized GroupsDesign FictionDIS
MindFlow: Breathing-Integrated Progressive Muscle Relaxation with a Full-Body Self-Avatar in Virtual RealityBreathing exercises and Progressive Muscle Relaxation (PMR) have complementary effects, making their integration a common practice among relaxation techniques. While numerous virtual reality (VR) exercises support breathing exercises in self-training, integrating breathing support into PMR in VR presents challenges, including maintaining the user's sense of presence and ensuring the effectiveness of breathing guidance. In this paper, we present MindFlow, a system design that combines breathing biofeedback with a full-body self-avatar, using mindfulness-based principles to provide effective, breathing-integrated PMR guidance in VR. The system demonstrates effectiveness in enhancing relaxation and reducing anxiety in novice users, based on empirical results from a 24-participant user study, offering generalizable insights for the design of embodied mindfulness systems and further research on mindfulness support in virtual and mixed reality.2025HYHangcheng Yang et al.Full-Body Interaction & Embodied InputImmersion & Presence ResearchSleep & Stress MonitoringDIS
Knitting with unknown trees: assembling a more-than-human practiceIn this pictorial, we explore alternative ways of knowing urban trees through a more-than-human lens. Using a municipal tree dataset, we focus on “unknown” trees—entries unclassified due to error, decay, or absence—highlighting the limits of quantification and fixed knowledge systems. Urban trees, while critical for ecosystems, are often shaped by technological interventions (e.g., GIS, IoT sensors, AI diagnostics) that prioritize their utility over other expressions. We engage in knitting as a material inquiry to foreground nonhuman agencies and relational entanglements. Through reflective shifts and compromises, this project questions normative design practices, seeking to amplify nonhuman participation. We make two contributions. Firstly, we offer insights into fostering alternative, relational engagements with urban ecologies. Secondly, we reflect on our process of surfacing and working with agentic capacities, articulating guidance for other design researchers. Through this, we advocate for fragmented approaches that embrace complicity and complexity in more-than-human design.2025DODoenja Oogjes et al.Sustainable HCIHuman-Nature Relationships (More-than-Human Design)DIS
A language of one’s own: annotations and layering as design materialAs designers, we often use annotations to add information and reflection to our work. We would like to suggest that these annotations let personal design languages emerge. We experiment with the materiality of the pictorial format itself to show how such languages emerge from a particular body of work, as it travels from sketches, text, and various material artefacts. This emergent language uses annotations and layers as design materials, providing access to the nuances in the thinking behind our research and making processes. Through this language, the voice of the maker emerges revealing subjective and situated knowledges that would not be available otherwise. We reflect on these insights and share a set of strategies using annotations and layerings for others to use. As a result, we contribute an approach of annotations and layering to engage complexity when making, reflecting, and disseminating design research.2025EVElvia Vasconcelos et al.Design FictionPrototyping & User TestingDIS
Enhancing Visitor Engagement in Interactive Art Exhibitions with Visual-Enhanced Conversational AgentsConversational agents in art exhibitions can enhance user engagement and understanding of artworks by providing contextual information, especially through voice interactions. However, creating a deeper personal connection with art - which often requires direct aesthetic and visual experiences - remains a challenge. This paper examines how integrating visual perception into conversational agents can enhance alignment with visitors' artistic interpretations, thereby fostering deeper engagement with interactive art exhibitions. We introduce a voice-based conversational agent enhanced with visual capabilities via a multimodal large language model (MLLM), allowing the agent to perceive and discuss artworks in real-time with visitors. The system utilizes a simplified Retrieval-Augmented Generation (RAG) architecture, which collects voice inputs, retrieves relevant information from a domain knowledge graph, and uses the LLM to generate conversational responses, which are then converted into voice outputs. A user study with 36 participants, divided into two groups, was conducted to compare the enhanced system with a baseline system that lacked visual input. Results show that the visually enhanced system significantly improved visitor engagement and satisfaction. Content analysis of the conversational transcripts further revealed a wider range of conversational topics, deeper visitor perceptions, and the agent's ability to provide more nuanced, visually-related discussions.2025HHHoang Phuoc Ho et al.Agent Personality & AnthropomorphismSocial & Collaborative VRMuseum & Cultural Heritage DigitizationIUI
Benefits of Machine Learning Explanations: Improved Learning in an AI-assisted Sequence Prediction TaskResearch in Explainable AI (XAI) has shown that explanations can improve users' understanding of AI models, improve user performance and potentially reduce overreliance on AI predictions. However, this is mostly evaluated by static rather than dynamic measures, and the role of XAI on learning over trials is rarely studied. In this study, we use a context-free sequence prediction task, in which 458 participants predict the next symbol in a fixed sequence (with some noise) over 80 trials. We compare performance with AI and XAI advice against no AI support, and subsequently we test for learning by taking away the AI support after 40 trials (i.e., a reversal study design). Our results show that users learn faster with XAI than with AI without explanations or no AI and are better able to recover in performance from the removal of AI. However, the benefits of XAI on learning are much smaller for more difficult tasks. This work demonstrates the benefits of repeated measures user studies and multilevel modeling to better understand learning processes in XAI. It also shows the potential of AI explanations to help users to learn and poses XAI design suggestions to support learning in human-AI collaboration.2025YLYu Liang et al.Explainable AI (XAI)AI-Assisted Decision-Making & AutomationIUI
Does Care Lead to Bonds? Exploring the Relationship Between Human Caregiving for Robots and Human-Robot BondingThis study investigates how interaction scenarios of human caregiving for robots affect humans’ perceived bond with robots. In a between-subjects lab experiment (n = 88), participants played a game with a social robot during which they provided either 1) emotional care (comforting the robot); 2) instrumental care (helping with battery charging); or 3) no care for the robot. Results indicated that caregiving did not significantly affect human-robot bonding according to explicit relationship measures including closeness, social attraction, or desire for future interaction. However, caregiving mattered when bonding was measured implicitly. Those in the emotional caregiving scenario were more hesitant to replace the robot and invested more effort in a voluntary task requested by the robot than those who provided no care. These findings provide empirical evidence that emotional caregiving interactions can effectively foster initial human-robot bonding, highlighting a promising design scenario for human-robot interaction.2025JXJiaxin Xu et al.Eindhoven University of Technology, Human Technology Interaction groupSocial Robot InteractionHuman-Robot Collaboration (HRC)CHI
What Comes After Noticing?: Reflections on Noticing Solar Energy and What Came NextMany design researchers have been exploring what it means to take a more-than-human design approach in their practice. In particular, the technique of “noticing” has been explored as a way of intentionally opening a designer’s awareness to more-than-human worlds. In this paper we present autoethnographic accounts of our own efforts to notice solar energy. Through two studies we reflect on the transformative potential of noticing the more-than-human, and the difficulties in trying to sustain this change in oneself and one’s practice. We propose that noticing can lead to activating exiled capacities within the noticer, relational abilities that lie dormant in each of us. We also propose that emphasising sense-fullness in and through design can be helpful in the face of broader psychological or societal boundaries that block paths towards more relational ways of living with non-humans.2025AMAngella Mackey et al.Amsterdam University of Applied Sciences, Civic Interaction Design groupSustainable HCIHuman-Nature Relationships (More-than-Human Design)CHI
Constituency as a Matter of Practice: Moving a Plant StudioHow more-than-human gatherings configure and change to support designing is not well understood. In the more-than-human theory of designing-with, these gatherings are called constituencies. This paper aims to shed light on the practices of a constituency, by analyzing the moving of a plant studio from one city to another. The plant studio includes over 250 plants and is where living-with and designing-with plants are conceptualized. The move offered an opportunity to understand the dynamics of the plant studio as a constituency using design events, a vocabulary and analytical tool, for understanding practices and temporality. In our analysis, we surface the role of humans as speaking subjects and five repertoires or considered actions that together articulate the practice of a constituency. We also illustrate the use of design events as an analytical tool for nuance and critical reflections on more-than-human design.2025OTOscar Tomico et al.Eindhoven University of TechnologySustainable HCIHuman-Nature Relationships (More-than-Human Design)CHI
Good Performance Isn't Enough to Trust AI: Lessons from Logistics Experts on their Long-Term Collaboration with an AI Planning SystemWhile research on trust in human-AI interactions is gaining recognition, much work is conducted in lab settings that, therefore, lack ecological validity and often omit the trust development perspective. We investigated a real-world case in which logistics experts had worked with an AI system for several years (in some cases since its introduction). Through thematic analysis, three key themes emerged: First, although experts clearly point out AI system imperfections, they still showed to develop trust over time. Second, however, inconsistencies and frequent efforts to improve the AI system disrupted trust development, hindering control, transparency, and understanding of the system. Finally, despite the overall trustworthiness, experts overrode correct AI decisions to protect their colleagues’ well-being. By comparing our results with the latest trust research, we can confirm empirical work and contribute new perspectives, such as understanding the importance of human elements for trust development in human-AI scenarios.2025PKPatricia K. Kahr et al.Eindhoven University of Technology, Human-Technology Interaction GroupAI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityAlgorithmic Transparency & AuditabilityCHI
Towards Personalized Physiotherapy through Interactive Machine Learning: A Conceptual Infrastructure Design for In-Clinic and Out-of-Clinic Support Machine learning (ML) is increasingly used in healthcare practices, due to its potential to support personalization, diagnostic and prediction, automatization, and increase effectiveness. In physiotherapy, most existing ML solutions suggest replacing the physiotherapist, neglecting the complexity of their skills and practice. We articulate an alternative to the design of ML technology for physiotherapy: one that emphasizes the relational aspects of the practice and offers personalized support to physiotherapists and patients alike. Based on domain studies and design explorations with physiotherapists, interaction designers and ML experts, we present 1) insights on physiotherapy's in-clinic and out-of-clinic looped structure, 2) opportunities and requirements to integrate ML in that loop, and 3) a conceptual interactive ML-based infrastructure that exploits those opportunities. Our work widens current ML developmental aims for physiotherapy, proposing a vision that encodes sustainable sociotechnical relationships in healthcare practices.2025LVLaia Turmo Vidal et al.KTH Royal Institute of Technology, Media Technology and Interaction DesignTelemedicine & Remote Patient MonitoringSurgical Assistance & Medical TrainingCHI
"Did you sleep well?": A Multimodal Sleep Diary for Sustained Self-Reporting by ChildrenSleep diaries are essential self-reporting tools for understanding children's sleep patterns, but maintaining sustained engagement and high-quality self-reporting remains challenging. While voice input has been explored in child-computer interaction research as a method to improve engagement, limited evidence exists regarding its effectiveness in supporting sustained self-reporting over time. To address this gap, we conducted a five-day field study with 20 children aged seven to twelve, using a multimodal sleep diary that integrated both voice and text input modalities. Our findings reveal that voice input significantly supports younger children in maintaining engagement over five days, though their response quality remains lower than that of older children. Two distinct response quality patterns over time also emphasize the importance of accounting for individual differences in task performance. Furthermore, input modality preferences varied by age: older children consistently favored text input, while younger children generally preferred voice input over time. These results highlight the potential of incorporating voice input into text-based sleep diaries to better accommodate the diverse needs of children, enhancing both sustained engagement and response quality. Future studies with longer observation periods are needed to validate and extend these findings.2025SCShanshan Chen et al.Eindhoven University of Technology, Department of Industrial DesignSleep & Stress MonitoringKnowledge Worker Tools & WorkflowsParticipatory DesignCHI