Not the Right Cue for Me: Investigating VR Cue Design and Biofeedback Integration in Drug Psychotherapy Psychotherapy is vital for identifying and managing craving-triggering cues. In this study, we paired virtual reality (VR) drug-cue scenarios with physiological sensors to capture participants’ real-time responses. Qualitative interviews with nineteen patients and six therapists showed that contextual elements resembling past drug-use experiences reliably provoked cravings, while biofeedback data confirmed that VR effectively elicits measurable physical responses. Our findings further suggest that adjusting the completeness and fidelity of VR scenarios to match a patient’s recovery stage can manage craving intensity and prevent urges from persisting beyond each session. Therapists also see opportunities to integrate virtual reality into clinical practice to address challenges from prior sessions and enhance therapeutic outcomes. This paper offers concrete recommendations for developing clinically deployable VR scenarios and outlines implications for future research and therapeutic applications in drug treatment.
CY
Chuang-Wen You et al. National Tsing Hua University
VR Medical Training & Rehabilitation Affective Feedback & Emotion Regulation Interfaces Mental Health Apps & Online Support Communities
IUI 2026 Fit Matters: Format–Distance Alignment Improves Conversational Search Existing conversational search systems can synthesize information into responses, but they lack principled ways to adapt response formats to users' cognitive states. This paper investigates whether aligning format and distance, which involves matching information granularity and media to users' psychological distance, improves user experience. In a between-subjects experiment (N=464) on travel planning, we crossed two distance dimensions (temporal/spatial × near/far) with four formats varying in granularity (abstract/concrete) and media (text/image-and-text). The experiment established that format-distance alignment reduced users' risk perceptions while increasing decision confidence, perceptions of information usefulness, ease of use, enjoyment, and credibility, and adoption intentions. Concrete formats imposed higher cognitive load, but yielded productive effort when matched to near-distance tasks. Images enhanced concrete but not abstract text, suggesting multimedia benefits depend on complementarity. These findings establish format-distance alignment as a distinctive and important design dimension, enabling systems to tailor response formats to users' psychological distance.
YY
Yitian Yang et al. National University of Singapore
Conversational Chatbots Conversational Search & QA Systems AI-Assisted Decision-Making & Automation
CHI 2026 Beyond Cues and Cravings: Exploring the Design of Assistive Systems for Craving Perception in Drug Psychotherapy with VR and Biofeedback Psychotherapy is crucial for managing cue-induced cravings. However, most research has focused on explicit drug cues that elicit intense cravings, and recreating such high-risk scenarios in practice can inadvertently heighten cravings afterward, making these approaches impractical or ethically problematic in real-world settings. To address this, we developed a cue-exposure technology probe system, VirtualCravingProbe, which integrates VR simulations with real-time biofeedback to enhance self-awareness in clinical drug psychotherapy. We conducted an exploratory study with twelve patients recovering from methamphetamine addiction using the VirtualCravingProbe system, generating design guidelines for future iterations of an integrated VR and biofeedback-assisted therapy tool. Results revealed qualitative evidence that real-time heart-rate monitoring in VR heightened patients’ awareness of triggers and their craving responses. These findings align with the CBT cognitive-triangle framework, which emphasizes the interplay of thoughts, emotions, and behaviors. Moreover, the system demonstrated potential to enrich patient–therapist dialogue and support the adoption of effective coping strategies.
CY
Chuang-Wen You et al. National Tsing Hua University
VR Medical Training & Rehabilitation Telemedicine & Remote Patient Monitoring Sleep & Stress Monitoring
CHI 2026 AI as the Phantom Limb: The Asymmetry of Attribution in Human vs. AI Delegation AI is reshaping workplace dynamics as people increasingly delegate
tasks to intelligent assistants. Yet how AI delegates are perceived
compared to human delegates—and how their performance and
their received feedback shape perceptions—remains unclear. We
conducted a 2×2×2 between-subject experiment where participants
delegated a scheduling task to either a human or an AI agent, vary-
ing their competence (high vs. low) and valence of received feed-
back (positive vs. negative) toward their performance. Participants
generally had higher trust in human assistants; yet a striking asym-
metry emerged: when an AI assistant received negative feedback,
participants felt the criticism as more self-directed—an “AI Phan-
tom Limb” effect—whereas positive feedback transferred less. This
asymmetry did not appear with human delegates. These findings
highlight broader design implications, suggesting that AI delegation
might blur the boundary between self and other. We also discuss
how these findings extend theories of delegation and responsibility
attribution to AI.
YC
Yu-Sheng Chen et al. National Chengchi University
AI-Assisted Decision-Making & Automation AI Ethics, Fairness & Accountability Empathy & Emotional Design
CHI 2026 Ad Recommended
Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work.
Explore Nowopen_in_new AIDED: Augmenting Interior Design with Human Experience Data for Designer–AI Co-Design Interior design often struggles to capture the subtleties of client experiences, leaving gaps between what clients feel and what designers can act upon. We present AIDED, a designer–AI co-design workflow that integrates multimodal client data into generative AI (GAI) design processes. In a within-subjects study with twelve professional designers, we compared four modalities: baseline briefs, gaze heatmaps, questionnaires visualizations, and AI-predicted overlays. Results show that questionnaire data were trusted, creativity-enhancing, and satisfying; gaze heatmaps increased cognitive load; and AI-predicted overlays improved GAI communication but required natural language mediation to earn trust. Interviews confirmed that an authenticity–interpretability trade-off is central to balancing client voices with professional control. Our contributions are: (1) a system that incorporates experiential client signals into GAI design workflows, (2) empirical evidence of how different modalities affect design outcomes, and (3) implications for future AI tools that support human–data interaction in creative practice.
YL
Yang Chen Lin et al. National Tsing Hua University
Generative AI (Text, Image, Music, Video) Human-LLM Collaboration Creative Collaboration & Feedback Systems
CHI 2026 Does Longer Phone Use Always Feel Worse? Examining How Intention and Duration Shape Evaluations of Time Use Prior work has examined how users judge their smartphone use, typically focusing on either usage duration or intention. How these two factors jointly shape such evaluations remains unclear. We conducted a two-week study with 104 participants, who reviewed their screenshots and provided labels of both usage intention and evaluation of time use. Across 73,000 sessions (6.1M screenshots), the relationship between duration and evaluation was initially linear but then bounded: positive evaluations declined and negative ones rose with longer phone use duration but both eventually stabilized, most often judged neutral. Trajectories varied by intention. Entertainment mirrored the overall trend; functional use continually lost positive evaluations, whereas information-seeking became increasingly positive during the first half hour before later declining; messaging-based connections slowly lost positive evaluations, while social media–based connections declined more quickly; finally, “no specific intention” unfolded in phases—from short positive use to regret-prone mid-length episodes to neutral long sessions.
YT
Yi-Hua Tsai et al. National Yang Ming Chiao Tung University
Smartphone Addiction & Digital Wellbeing Behavior Change & Reflection Technology Data-Driven Personal Decision-Making
CHI 2026 Exploring the Design of Collaborative Technological Systems to Assist Patients in Motivating Quitting Gambling with Family Members Gambling addiction can have a profound impact on the mental and financial well-being of individuals and their families. This paper presents an in-depth study on the development of technologies aimed at promoting collaborative efforts between patients and family members to deal with gaming addiction. The study performed interviews with ten pairs of gambling-addicted patients with a family member, six patients without family participation, and four treatment experts. Thematic analysis was conducted from the perspectives of patients and family members with the aim of identifying key themes underlying the development of the three antecedents of Planned Behavioral Theory: attitude, subjective norms, and perceived behavioral control. In accordance with the tenets of Prospect Theory, we sought to elucidate the process of attitude formation during editing and evaluation. We also conducted a thematic analysis of the opportunities and concerns in designing technologies aimed at overcoming gambling addiction. The identified themes provided a basis by which to assess design implications from the perspective of Planned Behavioral Theory. Our analysis revealed three directions for future development: 1) Helping patients to make informed gambling decisions through rational editing and evaluation, as suggested by Prospect Theory (attitude level); 2) promoting communication within families to enhance mutual understanding and trust (subjective norm level); and 3) helping patients to develop personal capabilities, while providing a realistic impression of their progress (perceived behavioral control level).
Facilitating Support and Belonging
CSCW 2025 Not What I Want to Log or Share: Exploring How to Enhance Technological Support through Affordable Behavioral Self-Monitoring and Data Sharing with Key Support Figures Shopping addiction is characterized by unrestrained repetitive purchasing behavior, negatively impacting one’s financial stability and social welfare. This study sought to gain insights into the development of self-monitoring devices and data sharing schemes to assist in dealing with shopping addiction. In this two-phase study, the Bergen Shopping Addiction Scale was first used in the pre-study screening survey to identify individuals with a propensity toward shopping addiction. In the second phase, an online survey was conducted, comprising (1) a study introduction and consent form, (2) the main survey, and (3) follow-up demographic questions. Phase II involved 332 participants meeting this criterion and was conducted to examine behavioral tendencies, evaluate prior intervention experiences, and elicit user preferences pertaining to self-monitoring and data sharing. The majority of respondents expressed a preference for systems that facilitate the tracking of shopping behavior and enable data sharing with intimate partners. Based on these findings, we recommend three directions for the further development of support systems: 1) Reduce the burden of mood tracking; 2) Streamline mechanisms for sharing data with key support figures; and 3) Tailor intervention strategies in accordance with key addiction indicators.
Beyond AI: Additional Considerations for Enhancing Healthcare
CSCW 2025 emoji_events Bridging Coaching Knowledge and AI Feedback to Enhance Motor Learning in Basketball Shooting Mechanics Through a Knowledge-Based SOP Framework We present a methodology for designing an AI feedback system aimed at assisting basketball beginners in refining their shooting techniques during independent practice sessions. Mastering shooting mechanics requires consistent, precise repetition, which traditionally depends on coaching feedback and the breakdown of movements into steps during the early stages. However, due to limited coaching resources, this guidance is often unavailable, leading to ineffective and even detrimental motor learning. To bridge this gap, we propose a Standard Operating Procedure (SOP) framework grounded in expert human knowledge, or knowledge-based SOP, which allows our AI-driven system to verify and guide players' movements in real-time. Through a formative study involving interviews with 13 coaches and players, we identified key challenges faced by beginners, such as uncertainty in movement correctness and lack of guidance during unsupervised practice. Our AI system addresses these issues by providing immediate, actionable feedback using SOP tailored to individual players. In a study with 28 participants, we confirmed that our system improves shooting form, increases confidence in adjustments, and enhances self-awareness during practice. This work highlights the potential of integrating coaching expertise with AI to empower athletes with more effective tools for self-directed practice.
JW
Jian-Jia Weng et al. National Tsing Hua University, Institute of Service Science
Multiplayer & Social Games Fitness Tracking & Physical Activity Monitoring
CHI 2025 Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation Content As personalized recommendation algorithms become integral to social media platforms, users are increasingly aware of their ability to influence recommendation content. However, limited research has explored how users provide feedback through their behaviors and platform mechanisms to shape the recommendation content. We conducted semi-structured interviews with 34 active users of algorithmic-driven social media platforms (e.g., Xiaohongshu, Douyin). In addition to explicit and implicit feedback, this study introduced intentional implicit feedback, highlighting the actions users intentionally took to refine recommendation content through perceived feedback mechanisms. Additionally, choices of feedback behaviors were found to align with specific purposes. Explicit feedback was primarily used for feed customization, while unintentional implicit feedback was more linked to content consumption. Intentional implicit feedback was employed for multiple purposes, particularly in increasing content diversity and improving recommendation relevance. This work underscores the user intention dimension in the explicit-implicit feedback dichotomy and offers insights for designing personalized recommendation feedback that better responds to users' needs.
WL
Wenqi Li et al. Peking University, Department of Information Management
Explainable AI (XAI) Recommender System UX
CHI 2025 Toward Understanding the Impact of Visualized Focus Levels in Virtual Reality on User Presence and Experience Neurofeedback refers to the process of feeding a sensory representation of brain activity back to users in real time to improve a particular brain function, e.g., their focus and/or attention on a particular task. This study addressed the notable lack of research on methods used to visualize EEG data and their effects on the immersive quality of VR. We developed an algorithm to quantify focus, yielding a focus score. A pre-study with twenty participants confirmed its effectiveness in distinguishing between focused and relaxed mental states. Subsequently, we used this focus score to prototype a VR experience system visualizing the focus score in preconfigured manners, which was utilized in an exploratory study to assess the impact of different neurofeedback visualization methods on user engagement and focus in VR. Among all the visualization methods evaluated, the environmental scheme stood out due to its superior usability during task execution, its ability to evoke positive emotions through the visualization of objects or scenes, and its minimal deviation from user expectations. Additionally, we explored design guidelines based on collected results for future research to further refine the visualization scheme, ensuring effective integration of the focus score within the VR environment. These enhancements are crucial for designing neurofeedback visualization schemes that aim to boost participant focus in VR settings, offering significant insights into the optimization of such technologies.
Brain-Computer Interface (BCI) & Neurofeedback Immersion & Presence Research
MobileHCI 2024 Understanding and Designing Multi-level Preventive Medication Support Against HIV for Men who Have Sex with Men in Taiwan Sexual health is an important domain that deserves more HCI attention, such as supporting the practices of men who have sex with men (MSM) against HIV risks. One current clinical approach to addressing this issue is to use preventive medicine like pre-exposure prophylaxis (PrEP). As medication adherence of PrEP is challenging that involves users’ individual knowledge, sex practices, relational status, and community support, technological mediation benefits from a human-centered perspective that goes beyond individual-level support to understand MSM’s needs so as to design a holistic technological intervention for them. With an in-depth interview (n = 22) with MSM from two major cities in Taiwan, we drew on the theoretical framework of the social ecological model and identified three levels of influences, including individual, interpersonal, and sociocultural, that shape the enablers, inhibitors, risks and challenges, and support towards MSM’s PrEP use. We proposed correspondent technological design implications to support what we found based on the understanding of our participants.
CY
Chien Wen (Tina) Yuan et al.
Health
CSCW 2023 Understanding the Benefits and Design of Chatbots to Meet the Healthcare Needs of Migrant Workers Economically disadvantaged migrant workers are one of the most vulnerable groups in healthcare. Studies have shown that chatbots can help patients and health professionals in healthcare settings. However, the design of health chatbots for migrant workers has not been thoroughly investigated. Scenario-based interviews with nineteen participants, including ten economically disadvantaged Thai migrant workers and nine relevant stakeholders, were conducted to examine how they seek healthcare, obtain health information, and communicate with health professionals to gain a deeper understanding of the barriers that migrant workers encounter in healthcare. The findings of the interview show that migrant workers face a variety of barriers, such as a lack of familiarity with the healthcare system in the host country, language barriers, cultural barriers to seeking healthcare, and communication barriers with health professionals. Then, the technological design strategies and the benefits of health chatbots from the perspective of migrant workers were discussed, including their potential to help migrant workers navigate the healthcare system step-by-step, obtain reliable health information, improve their health literacy, and facilitate communication with health professionals. Finally, five design implications for chatbots were proposed to guide future development of health chatbots to help migrant workers. Policymakers and health professionals can benefit from the design implications of migrant worker-centered health chatbots when they develop health chatbots that promote the health and well-being of migrant workers.
Health
CSCW 2023 Mind and Body: The Complex Role of Social Resources in Understanding and Managing Depression in Older Adults Depression is the most common mental health problem in older adults; however, a lack of understanding in the interaction between physical and social causes hinders effective treatment. Unique issues such as age-specific increases in comorbid physical problems and alienation from social contact can make it difficult for health providers to identify instances of depression. These also make it difficult for depressed older adults to communicate with their social resources, such as friends, family, and health providers. Integrating technology-assisted collaboration with members of patients' social network to observe and manage multi-dimensional factors in depressed older adults' states is a potential way to improve the quality of practitioners' treatment-planning around these multi-dimensional factors, as well as provide assistance for family and friends' involvement in managing the depression. We conducted an interview study on stakeholders' perceptions of depression and communication to understand the opportunities and challenges involved in implementing such collaborative design. Interviewees included 16 depressed older adult patients, 10 of their family members, and two psychiatrists. Our findings reveal new insights into 1) patients' and families' social values and understandings of patients' condition, as well as 2) how these values and understandings influenced decision-making on communicating with each other and acting on depression. These insights have implications for the consideration of information and communication systems to aid depressed older adults' recovery and engagement with social network members.
Older Adults
CSCW 2023 Trigger or Treat: Using Technology to Facilitate the Perception of Cravings and Corresponding Cues for Achieving Clinical-friendly Drug Psychotherapy Drug addiction is a chronic condition, marked by compulsive drug use. In previous research, cue exposure and biofeedback technologies proved effective in drug psychotherapy sessions; however, the focus has generally been on the awareness of cravings and the identification of cues. There has been relatively little research on methods aimed at facilitating therapist-patient communication, particularly from a user-centered perspective. In this paper, we describe a qualitative technology probe study exploring the means by which patients identify cues and perceive cravings as well as the way that they communicate with therapists. Our analysis considers the difficulties in cue identification and craving perception, the interactions between the two, and the means by which these characteristics could impact the design of VR support systems in the future.
Mental Health II
CSCW 2023 Scanning or Simply Unengaged in Reading? Opportune Moments for Pushed News Notifications and Their Relationship with Smartphone Users’ Choice of News-reading Modes News notifications on smartphones provide a convenient way to stay informed, but their delivery timing can influence user engagement. Despite this, research on the impact of notification timing on reading behavior remains limited. Therefore, we developed NewsMoment, a news aggregation app that monitors user reading patterns and sends news notifications. Our experience sampling study with 46 NewsMoment users revealed four distinct reading modes: typical, comprehensive, scanning, and unengaged. Deep reading, encompassing typical and comprehensive modes, more often occurred during self-initiated browsing rather than through pushed news. Interestingly, shallow reading modes - unengaged and scanning - showed varying prevalence, associated triggers, and engagement, despite their similarities. Importantly, unengaged reading persisted regardless of users' perceived moment opportuneness, whereas scanning reading was more common during inopportune moments. These findings suggest that identifying opportune moments for news reading may primarily reduce scanning reading, without substantially impacting unengaged reading.
Social Platform Design & User Behavior Notification & Interruption Management
MobileHCI 2023 What is in the Cards: Exploring Uses, Patterns, and Trends in Design Cards Card-based design tools–design cards–increasingly present opportunities to support practitioners. However, the breadth and depth of the design card landscape remain underexplored. In this work, we surveyed 103 design practitioners to assess current usages and associated barriers. Additionally, we analyzed and classified 161 decks of design cards from 1952-2020. We held a workshop with four experienced practitioners to generate initial categories, and then coded the remaining decks. We found that the cards contain seven different types of design knowledge: Creative Inspiration; Human Insights; Material & Domain; Methods & Tooling; Problem Definition; Team Building; and Values in Practice. The content of these cards can support designers across design stages; however, most are intended to support the early stages of design (e.g., research and ideation) rather than later design stages (e.g., prototyping and implementation). We share additional patterns uncovered and provide recommendations to support the future development and adoption of these tools.
GH
Gary Hsieh et al. University of Washington
Universal & Inclusive Design Participatory Design
CHI 2023 I Like Their Autonomy and Closeness to Me: Uncovering the Perceived Appeal of Social-Media Influencers The proliferation of influencers on social-media platforms has drawn considerable research attention, particularly in the field of marketing. Nevertheless, there is limited understanding among HCI and communication researchers of what leads these social-media influencers’ (SMIs’) audiences to favor and choose their content over traditional media. To fill this gap, we conducted semi-structured interviews with 45 SMI audience members. Our findings revealed a total of eight categories of SMIs’ appeals, i.e., factors that made the interviewees favor their content over traditional media. These appeals can further be grouped into three categories: content, presentation, and closeness. In particular, we identified the key role of SMIs’ perceived high autonomy and independence, which led both their content and their presentation styles to be seen as distinct from and more appealing than traditional media. Likewise, four closeness appeals made our participants feel emotionally attached to SMIs, resulting in sustained engagement.
YC
Yu-Ling Chou et al. National Yang Ming Chiao Tung University
Agent Personality & Anthropomorphism AI Ethics, Fairness & Accountability Social Platform Design & User Behavior
CHI 2023 Get Distracted or Missed the Stop? Investigating Public Transit Passengers’ Travel-Based Multitasking Behaviors, Motives, and Challenges Mobile users commonly multitask during travel, but doing so on public transit can be challenging due to the dynamic nature of the environment as well as long-standing lack of infrastructural support. Nevertheless, HCI scholars and practitioners have devoted relatively little attention to developing technology for enhancing travel multitasking. To facilitate such development, we sought to understand travel multitaskers’ practices and challenges while on public transit, and to that end, conducted a multi-methods study that involved shadowing and interviewing 30 of them. We identified four travel-multitasking patterns, characterized by distinct motives that affected these travelers’ multitasking practices, receptivity to environmental stimuli, and task persistence. The two main challenges they encountered during travel multitasking resulted from mutual interference from their tasks and from the dynamic nature of transit environments. Based on these findings, design recommendations for public-transit agencies and mobile services are also provided.
HL
Hsinju Lee et al. National Tsing Hua University
Notification & Interruption Management Public Transit & Trip Planning
CHI 2023 To Use or Abuse: Opportunities and Difficulties in the Use of Multi-channel Support to Reduce Technology Abuse by Adolescents Technology abuse among adolescents refers to the problematic use of technology devices, and the negative impact it can have on lifestyle and one’s physical and mental health. This paper reports on in-depth interviews with 15 dyads of adolescent patients, their parents, and four experts with the objective of unraveling the issue of technology abuse. We conducted qualitative analysis aimed at unpacking the contextual factors affecting technology abuse, and differences between adolescents and their parents pertaining to this issue. Our discussions led us to formulate solutions to technology abuse: (1) motivating adolescents by sending timely reminders and providing interactive micro-incentives; (2) promoting communication between adolescents and their parents by sharing usage data related to device usage; and (3) incorporating social supports to complement parental support, while fulfilling the adolescent’s social needs. This paper provides valuable insights into the design of technological solutions aimed at mediating technology abuse.
Health and Consultation Practices, Addictive Behaviors, and Social Re-entry; Health and Consultation Practices, Addictive Behaviors, and Social Re-entry
CSCW 2022