When a person with dementia asks about a deceased partner’s health, caregivers and relatives are often unsure how to respond. These interactions involving reality disjunction are ethically and emotionally complex, with no universal ‘right’ answer. Reflecting on such interactions may help people better understand and navigate these situations. We explore how chatbots can complement humans in supporting such reflection. We designed three chatbots that support reflection through role-play, dilemmas, or analysis, and used them as probes in focus groups with 14 relatives and 10 caregivers of people with dementia. Findings reveal complementary strengths. Humans provide irreplaceable reflective support grounded in contextual, emotional, experiential, and relational involvement. Chatbots’ lack of human qualities offers unconstrained suggestions, evidence-based feedback, and emotionally distanced dialogue without relational consequences. We offer empirical insights into reflective support needs in dementia care and provide design implications for chatbots that complement rather than mimic human reflection.

People with dementia often experience social isolation in daily life. Generative AI (GenAI) technologies, producing seemingly new content on the spot and tailoring it to users’ wishes, open new avenues for promoting meaningful social connections in dementia care. This study involved 17 people with dementia in 6 workshops and explored how they responded to and perceived three GenAI models, Copilot, Midjourney, and Suno, with a focus on social connectedness. Our results reveal that people with dementia engage in a relational process when using GenAI together: they collectively evaluate the outcomes of the models and negotiate further prompts. Moreover, they gradually develop an understanding of GenAI and become more critical about its output. We contribute to HCI by demonstrating how GenAI can foster social bonding between people with dementia through the co-creation of shared realities, and by discussing guidelines for designing effective and ethically responsible GenAI for people with dementia.

Time is increasingly researched in HCI, yet design often remains tied to normative temporal constructs, e.g., clocks and calendars. This is especially limiting in dementia contexts, where temporal experience is altered. Existing approaches largely enforce normative time and overlook futures, prioritizing the past for people with dementia. To explore how people with dementia and their partners experience time, we designed the Temporal Snapshots probe for 12 participants to reflect on temporal subjectivity across past and future moments. The probe surfaced layered narratives. Participants articulated fluid temporal associations, anchored narratives to personally meaningful moments, and situated themselves within future and past trajectories. We contribute empirical insights into how couples experience subjective time, a dual temporal lens for HCI, design directions for reframing time in dementia contexts, and methodological reflections on researching temporality. We foreground time as relational and co-constructed, challenging assumptions of linearity and fixed orientation in interaction design.

Social robots are increasingly applied as health behavior change interventions, yet actionable knowledge to guide their design and evaluation remains limited. This systematic review synthesizes (1) the behavior change strategies used in existing HRI studies employing social robots to promote health behavior change, and (2) the evaluation methods applied to assess behavior change outcomes. Relevant literature was identified through systematic database searches and hand searches. Analysis of 39 studies revealed four overarching categories of behavior change strategies: coaching strategies, counseling strategies, social influence strategies, and persuasion-enhancing strategies. These strategies highlight the unique affordances of social robots as behavior change interventions and offer valuable design heuristics. The review also identified key characteristics of current evaluation practices, including study designs, settings, durations, and outcome measures, on the basis of which we propose several directions for future HRI research.

Informed consent is essential for ethical research, but applying it in technology research involving people with dementia can be challenging. We conducted interviews with researchers, participants with dementia, and data stewards to explore these challenges and strategies for obtaining consent. Using communication theory, we examined how linear, dynamic, and contextual communication elements influence consent practices. Our findings show that relying too much on one-way information transfer creates problems in conveying information, documenting agreements, monitoring ongoing consent, and improving the consent processes. However, dynamic, context-sensitive strategies, such as paraphrasing information, fostering personal relationships, and designing supportive environments, can turn consent into a collaborative and inclusive process. We offer practical recommendations and reflective questions to improve consent conversations in dementia research and suggest future directions for more dynamic consent materials. By reframing consent as a dynamic and contextual process, we aim to make technology research in sensitive settings more ethical and inclusive.

Professional caregivers want to provide feelings of security and comfort to people with dementia in advanced care, but limited resources frequently restrict professional caregivers from doing so. One potential solution to make social, non-verbal connections with people in advanced dementia care is the use of artifacts that offer comfort and stimulating tactile experiences. In this study, we explored the role of two design artifacts, the Mano Quilt, a weighted blanket, and the Mano Fold, a foldable pillow, in supporting caregivers to increase feelings of comfort and security in people with advanced dementia through warmth. In a field study, we collected data through observations of 26 residents with dementia who interacted with the two artifacts and 17 interviews with their formal caregivers in three care organizations. We reveal which aesthetic and material qualities evoke haptic and bodily experiences such as presence, comfort, and activity and how the artifacts support existing caregiving practices. We encourage future researchers to design to enrich the senses as an aesthetic experience and provide emotional support and companionship to increase well-being for people with advanced dementia.

Intertemporal reflection, flexibly thinking forward and backward in time, is vital for one's future planning.Yet, cultivating intertemporal reflection about encountering difficult futures, e.g., developing a progressive cognitive condition like dementia, can be challenging.We assessed people's attitudes towards dementia following conversing with a chatbot presented as either neurotypical or simulating dementia symptoms.While neither the chatbot's presentation nor the framing of participants' future selves impacted attitudes toward dementia, it influenced participants' experiences.When framed as future selves, the chatbot evoked a strong emotional connection, leading to reflection on aging, particularly with the chatbot simulating dementia symptoms.Participants interacting with the chatbot framed as a stranger with simulated symptoms often felt frustrated, especially when they had a task-oriented mindset.Chatbots can be promising tools for prompting reflections on challenging futures, such as dementia, although their effectiveness varies due to the tensions between simulated cognitive decline and expectations for effective communication.

The progression of dementia leads to a loss of initiative and agency, halting daily activities, hobbies, or social encounters. Open-ended play can encourage initiative but remains underexplored in dementia. This paper explores how technology-driven design can support open-ended play, making social interactions more enjoyable and renewing interest in daily activities. We conducted five workshops at dementia daycare facilities, observing people with dementia engage with playful circuit-building toolkits to identify strategies. Findings reveal these toolkits stimulated self-direction and initiative to accomplish self-imposed goals, both independently and collaboratively. We show how open-ended play fosters confidence, resilience, social engagement, and self-expression, allowing people with dementia to exercise choice and share moments of achievement. We provide design implications for technology to stimulate initiative through open-ended play by 1) balancing structure and freedom, 2) emphasizing novelty and material diversity for non-verbal social connection, and 3) considering age-appropriate aesthetics.

This 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.

To design social robots to effectively promote health behavior change, it is essential to understand how people respond to various health communication strategies employed by these robots. This study examines the effectiveness of two types of social control strategies from a social robot-relationship-focused strategies (emphasizing relational consequences) and target-focused strategies (emphasizing health consequences)-in encouraging people to reduce sedentary behavior. A two-session lab experiment was conducted (n = 135), where participants first played a game with a robot, followed by the robot persuading them to stand up and move using one of the strategies. Half of the participants joined a second session to have a repeated interaction with the robot. Results showed that relationship-focused strategies motivated participants to stay active longer. Repeated sessions did not strengthen participants' relationship with the robot, but those who felt more attached to the robot responded more actively to the target-focused strategies. These findings offer valuable insights for designing persuasive strategies for social robots in health communication contexts.

As populations are ageing, innovative solutions are needed to support older adults in living independently. Socially Assistive Robots (SARs) hold significant potential, but their adoption in real-world healthcare settings remains limited, partially due to low user acceptance and diverse end-user needs. Therefore, personalization might be an interesting approach to address these user needs and increase user acceptance. This perspective paper presents a targeted synthesized analysis of findings from four prior studies conducted by the authors, to explore the role of personalized communication in SARs and its impact on user experience. The analysis reveals that both explicit and implicit personalization strategies enhance user engagement, acceptance, and communication effectiveness in SARs. It was found that explicit personalization primarily involves adjustments such as customizing speech characteristics, while implicit personalization focuses more on tailoring message content (e.g., based on individual interests of older adults). By linking empirical findings to existing literature, this paper provides a novel perspective on personalization approaches in SAR design, emphasizing the importance of both individual and group-level explicit and/or implicit adaptations to improve the user experience of SARs for older adults.

Design ideation requires both creative and divergent thinking as well as collaboration and exchange to bring forth new insights and design possibilities. In this paper, we investigate such a collaboration with the use of emerging generative AI tools, and we explore how they may help in achieving agreement and semantic convergence between designers. We conducted workshops using Text-to-Image AI with design students and found that in addition to known advantages of brainstorming, the text prompts required by the AI system engaged students in verbal articulations that aided their design process. In collaborative contexts, the generated images shifted the centre of attention for team members to reach convergence through sharing their interpretations. We conclude that text-to-image AI can be beneficial for students’ design processes as a catalyst for brainstorming rather than a tool for generating design imagery and presentations.

The transition from home to formal residential care is described as stressful and emotionally difficult for people with dementia and their informal caregivers. While HCI research investigated how technology supports people with dementia at home or in formal care, there still is a need to understand how technology can support care transitions. This paper presents a practice-informed approach to gather insights collaboratively between care professionals and HCI researchers. We interviewed 42 informal caregivers of people with dementia to uncover their experiences before, during, and after care transitions. Our findings reveal how informal caregivers were: 1) navigating hurdles of information on care transitions, 2) caught up in the evolving challenges of informal caregiving, and 3) shifting from uncertainty in decision-making to acceptance of admission. Next, we formulate six design opportunities to support transitions in dementia care and encourage HCI researchers to pursue a practice-informed approach to address societal challenges in dementia.

Communication can become challenging for people with dementia due to language, speech, discourse, and memory impairments. Although recent developments in Human-Computer Interaction have addressed some of these communication challenges, little is known about how they affect the self-presentation of people with dementia in everyday interactions. To understand this connection, we conducted interviews with sixteen people with dementia, six spouses, and fourteen formal caregivers. Our qualitative data revealed that people with dementia’s presentation of competence, politeness, engagement, and reality are altered by communication challenges, which can impact their self-esteem, interactions, and relationships. Our study highlights the need for developing technologies that can enhance mutual understanding and acceptance of people with dementia’s evolving presentation of self. Additionally, policy changes are required to reduce the stigma associated with communication challenges to foster social inclusion.

Health-related social control refers to intentional attempts to influence people's health behaviors, often seen in personal relationships. Social robots hold promise in influencing people's health by exerting health-related social control, but it is unclear which social control strategies used by robots are appropriate and potentially effective. This study investigates the effects of positive versus negative, and relationship-oriented versus target-oriented social control strategies from a social robot on people's psychological reactions. In an online video prototype study, participants viewed scenarios of a social robot attempting to change their sedentary behaviors by using different strategies. We found that positive (versus negative) strategies elicited stronger positive affect, enjoyment, and perceived social appropriateness, reduced perceived threats to freedom, and strengthened behavioral intention. Meanwhile, the relationship-oriented (versus target-oriented) strategies elevated people's negative affect, reduced enjoyment and perceived appropriateness, elevated perceived threats to freedom, and weakened behavioral intentions. Given these findings, we give recommendations for designing health influence strategies in social robots.

Users with large domain knowledge can be reluctant to use prediction models. This also applies to the sports domain, where running coaches rarely rely on marathon prediction tools for race-plan advice for their runners’ next marathon. This paper studies the effect of adding interactivity to such prediction models, to incorporate and acknowledge users’ domain knowledge. In think-aloud sessions and an online study, we tested an interactive machine learning tool that allowed coaches to indicate the importance of earlier races feeding into the model. Our results show that coaches deploy rich knowledge when working with the model on runners familiar to them, and their adaptations improved model accuracy. Those coaches who could interact with the model displayed more trust and acceptance in the resulting predictions.

During the pre-design phase of supportive intelligent systems, interviews with future users, such as people with dementia, aim to explore the problems for which technology may present a solution. However, interviewing someone with dementia in this unstructured design phase is reported to be challenging resulting in systems that are not truly addressing the needs of the people with dementia. Existing guidelines on creating engaging interviews are often based on post-hoc reflections of researchers and participants. In this study we performed line-to-line sequential in-depth analyses on transcripts of 10 interviews conducted to co-design an interactive intelligent gaming system. Both interviewers and interviewees were subsequently asked to reflect on their experiences. Results show that information exchange with people with dementia can be supported by carefully constructed questions, well-designed probes, and an appropriate length of the interview. To create a pleasant atmosphere during the interviews, researchers should design the interview as a fulfilling experience, be prepared to respond respectfully to negative responses and be able to adapt to different signs of consent. Improving the engagement with people with dementia during interviews can enhance the design and development of intelligent systems that cater to their unique challenges and requirements.

Gratitude is a moral emotion that demonstrates our appreciation of altruism.In psychology, feeling grateful is linked to an increase in well-being, yet there is a lack of HCI research on if gratitude can be cultivated through and with conversational agents.We quantitatively studied whether a chatbot can increase people's gratitude (N ¼ 133), as well as its influence on people's positive and negative emotions.Compared to the control condition, a chatbot that shared gratitude interventions significantly enhanced people's gratitude and positive emotions, while lowering negative emotions.Interestingly, people's experience of gratitude differed from other positive emotions: Simple positive emotions, like joy, can go up while reported gratitude decreases.We share qualitative observations on how gratitude can be a complex emotional experience, encompassing positive and negative emotions, such as finding relief in admitting to a chatbot about one's sadness over friendship during the COVID-19 pandemic.

It has been shown that providing explanations about AI-based systems’ decisions can be an effective way to increase users’ trust and acceptance. The effect of explanation design in smart home systems on users’ acceptance and perceptions is however less known. We therefore explored the effect of different explanation designs on acceptance in the context of the Philips Hue smart home lighting system. We conducted interviews (N = 10) and an online experiment (N = 452) using three everyday smart home lighting scenarios with different explanation types. The results showed that although participants indicated a positive attitude towards explanations, receiving an explanation can potentially reduce the perceived control of the lighting system. Furthermore, participants preferred system-based explanations rather than user-based explanations. Our study also provides recommendations for the design of explanations in smart home systems.

Future robots are expected to be autonomous actors, even capable of moral reasoning. Yet how they can provide transparent explanations while being socially intelligent during morally relevant interactions deserves a close examination. Our mixed-methods lab study on a human-robot moral debate on the footbridge dilemma showed that quantitatively, a robot’s perceived competence was significantly higher with transparency cues (additional information presented on a screen). The robot’s perceived warmth and mind were not influenced by transparency cues, but they did significantly change over time (pre- vs. post-debate). The change in the robot’s perceived mind and social attributes after the debate correlated with people’s trust in the robot; transparency cues did not correlate with trust. Qualitatively, the robot was described to be logical, unemotional, and intentional in making moral decisions; participants focused on its gaze and speech. While transparency may help in theory, if people do not observe relevant cues while attributing intentionality to the robot and its gaze, transparency cues may not be useful during critical decision-making though the robot can seem competent. We discuss the implications and call for broadening the notion of transparency to investigate how robots can be transparent communicators by appealing to both cognition and affect in morally sensitive interactions.

What is it like to hear another person’s heartbeat during communication? How would direct access to a person’s skin conductance influence our sense of interpersonal intimacy or trust? Can biosignal...

Abstract With the Internet of Things (IoT) becoming increasingly prevalent in people’s homes, new threats to residents are emerging such as the cyber-physical attack, i.e. a cyber-attack with physical consequences. In this study, we aimed to gain insights into how people experience and respond to cyber-physical attacks to their IoT devices. We conducted a naturalistic field experiment and provided 9 Dutch and 7 UK households, totalling 18 and 13 participants respectively, with a number of smart devices for use in their home. After a period of adaptation, simulated attacks were conducted, leading to events of varying noticeability (e.g., the light going on or off once or several times). After informing people simulated attacks had occurred, the attacks were repeated one more time. User experiences were collected through interviews and analysed with thematic analyses. Four relevant themes were identified, namely (1) the awareness of and concern about privacy and security risks was rather low, (2) the simulated attacks made little impression on the participants, (3) the participants had difficulties with correctly recognizing simulated attacks, and (4) when informed about simulated attacks taking place; participants noticed more simulated attacks and presented decision rules for them (but still were not able to identify and distinguish them well—see Theme 3). The findings emphasise the need for training interventions and an intrusion detection system to increase detection of cyber-physical attacks.

Social touch is essential to human development and communication. Mediated social touch is suggested as a solution for circumstances where distance prevents skin-to-skin contact. However, past research aimed at demonstrating efficacy of mediated touch in reducing stress and promoting helping have produced mixed findings. These inconsistent findings could possibly be due to insufficient control of contextual factors combined with unnatural interaction scenarios. For example, touch occurs less frequently among strangers and is often accompanied with nonverbal visual cues. We investigated how visual presentation of touch, and interpersonal relationship to the sender influence perception, affective experiences, and autonomic responses the touch evoke. Fifty couples of mixed gender were recruited. A mediated touch was repeatedly applied by either the male partner or male confederate to female participants. The latter witnessed through a webcam as the sender caressed a rubber hand or touchpad to send the touch. Following our hypotheses, touch sent by one's partner was perceived softer and more comforting than stranger touch. The partner's touch also resulted in weaker skin conductance responses, particularly when sent by touching a touchpad. In sum, how a mediated touch is experienced depends both on who is touching, and on how the touch is visually represented.

Model-agnostic explainable AI tools explain their predictions by means of ’local’ feature contributions. We empirically investigate two potential improvements over current approaches. The first one is to always present feature contributions in terms of the contribution to the outcome that is perceived as positive by the user (“positive framing”). The second one is to add “semantic labeling”, that explains the directionality of each feature contribution (“this feature leads to +5% eligibility”), reducing additional cognitive processing steps. In a user study, participants evaluated the understandability of explanations for different framing and labeling conditions for loan applications and music recommendations. We found that positive framing improves understandability even when the prediction is negative. Additionally, adding semantic labels eliminates any framing effects on understandability, with positive labels outperforming negative labels. We implemented our suggestions in a package ArgueView[11].

Measurement of physiological reactions to persuasive messages can improve our understanding of psychological processes of persuasion, and potentially further enhance and personalize current persuasion interventions. However, little is known about the relationship between psychophysiology and persuasive processes. This study focused on four persuasion principles: scarcity, commitment, consensus, and authority, and people's susceptibility to them. Physiological measures included the cardiovascular, respiratory, and electrodermal system, as well as facial motor systems. Psychological measures consisted of self-reported attitude towards oral care and susceptibility to persuasion (STPS). We performed a randomized within-subject experiment in which fifty-six participants viewed persuasive messages deploying the aforementioned persuasion principles to improve their oral care. Results indicated different physiological patterns during persuasion versus rest. We found no different physiological patterns in exposure to distinct persuasion principles, nor a clear correlation with susceptibility to individual persuasion principles. However, mixed model analysis illustrated that overall STPS scores help explain variance in reactivity of skin conductance level and skin conductance response, and reactivity in the zygomaticus major: lower susceptibility relates to higher reactivity. Summarizing, we have found no conclusive support for distinct psychophysiological patterns associated with different persuasion principles, although overall susceptibility seems to be reflected in physiology to some extent.

Physiological responses to persuasion can help to increase our understanding of persuasive processes, and thereby the effectiveness of persuasive interventions. However, a clear relationship between psychophysiology and persuasion is not yet established. This article investigates if peripheral physiology predicts persuasion effectiveness, and whether peripheral physiology yields information that is not represented in other predictors of persuasion. We studied physiological reactions in the cardiovascular, electrodermal, facial muscle and respiratory systems of 75 participants while they read gain- or loss-framed persuasive messages advocating increased oral health care behavior. Persuasion effectiveness was measured as pre to post intervention changes in self-reported attitudes and intentions, as well as through changes in behavioral compliance over three weeks. Overall, participants showed stronger attitudes and intentions directly after the intervention (short-term persuasion), but did not show changes in behavior or attitudes two weeks later (no long-term persuasion). On an individual level, physiological reactivity parameters yielded additional information – next to self-report measures – to predict persuasion effectiveness on attitude, intention and behavioral compliance. To conclude, our findings suggested a positive relationship between physiological reactivity to persuasive messages and subsequent attitudes, intentions and behavior, and quantified the extra personalization that psychophysiological measures might bring to persuasive messaging.

Abstract Psychological theories of habit posit that when a strong habit is formed through behavioral repetition, it can trigger behavior automatically in the same environment. Given the reciprocal relationship between habit and behavior, changing lifestyle behaviors is largely a task of breaking old habits and creating new and healthy ones. Thus, representing users’ habit strengths can be very useful for behavior change support systems, for example, to predict behavior or to decide when an intervention reaches its intended effect. However, habit strength is not directly observable and existing self-report measures are taxing for users. In this paper, building on recent computational models of habit formation, we propose a method to enable intelligent systems to compute habit strength based on observable behavior. The hypothesized advantage of using computed habit strength for behavior prediction was tested using data from two intervention studies on dental behavior change ( $$N = 36$$ N=36 and $$N = 75$$ N=75 ), where we instructed participants to brush their teeth twice a day for three weeks and monitored their behaviors using accelerometers. The results showed that for the task of predicting future brushing behavior, the theory-based model that computed habit strength achieved an accuracy of 68.6% (Study 1) and 76.1% (Study 2), which outperformed the model that relied on self-reported behavioral determinants but showed no advantage over models that relied on past behavior. We discuss the implications of our results for research on behavior change support systems and habit formation.

As robots may take a greater part in our moral decision-making processes, whether people hold them accountable for moral harm becomes critical to explore. Blame and punishment signify moral accountability, often involving emotions. We quantitatively looked into people’s willingness to blame or punish an emotional vs. non-emotional robot that admits to its wrongdoing. Studies 1 and 2 (online video interaction) showed that people may punish a robot due to its lack of perceived emotional capacity than its perceived agency. Study 3 (in the lab) demonstrated that people were neither willing to blame nor punish the robot. Punishing non-emotional robots seems more likely than blaming them, yet punishment towards robots is more likely to arise online than offline. We reflect on if and why victimized humans (and those who care for them) may seek out retributive justice against robot scapegoats when there are no humans to hold accountable for moral harm.

Abstract Cryptocurrencies are proliferating as instantiations of blockchain, which is a transparent, distributed ledger technology for validating transactions. Blockchain is thus said to embed trust in its technical design. Yet, blockchain’s technical promise of trust is not fulfilled when applied to the cryptocurrency ecosystem due to many social challenges stakeholders experience. By investigating a cryptocurrency chatbot (Brokerbot) that distributed information on cryptocurrency news and investments, we explored social tensions of trust between stakeholders, namely the bot’s developers, users, and the bot itself. We found that trust in Brokerbot and in the cryptocurrency ecosystem are two conjoined, but separate challenges that users and developers approached in different ways. We discuss the challenging, dual-role of a Brokerbot as anobject of trustas a chatbot while simultaneously being amediator of trustin cryptocurrency, which exposes the social-technical gap of trust. Lastly, we elaborate on trust as a negotiated social process that people shape and are shaped by through emerging ecologies of interlinked technologies like blockchain and conversational interfaces.

Abstract Self-tracking technologies bring a new set of experiences into our lives. Through sensors and ubiquitous measurements of bodily performance, a new form of automation experience shapes our understanding of our body and our behavior. While for many individuals self-tracking has an important role in their daily lives, a theoretical understanding of the level and behavioral manifestations of commitment to self-tracking is still missing. This paper introduces the concept of commitment to self-tracking and presents the development and first validation of a new 12-item behavior-based scale for its measurement, the Commitment to Self-Tracking (C2ST) scale. Using online survey data from individuals wearing self-tracking technology (N = 300), we explore the underlying factor structure of the scale and determine its reliability and validity. An analysis of the survey data indicates that commitment to self-tracking positively correlates with autonomous motivation for tracking and negatively correlates with controlled motivation. The C2ST scale brings insights on how self-tracking technology, as a novel automation experience, is affecting users’ everyday behaviors. Overall, by emphasizing the feasibility of defining commitment behaviorally, the paper concludes with implications for theory and practice and suggests directions for future research.

The digitization of mental health care holds promises of affordable and ubiquitously available treatment, e.g., with conversational agents (chatbots). While technology can guide people to care for themselves, we examined how people can care for another being as a way to care for themselves. We created a self-compassion chatbot (Vincent) and compared between caregiving and care-receiving conditions. Care-giving Vincent asked participants to partake in self-compassion exercises. Care-receiving Vincent shared its foibles, e.g., embarrassingly arriving late at an IP address, and sought out advice. While self-compassion increased for both conditions, only those with care-receiving Vincent significantly improved. In tandem, we offer qualitative data on how participants interacted with Vincent. Our exploratory research shows that when a person cares for a chatbot, the person's self-compassion can be enhanced. We further reflect on design implications for strengthening mental health with chatbots.

Rapid innovations in electronic healthcare and behavior tracking systems are challenging health coaches (dietitians, personal trainers, etc.) to rethink their traditional roles and healthcare practices. At the same time, many current e-coaching systems have been developed without explicitly incorporating the healthcare professionals' perspective into the design process. In the current paper, we present three consecutive qualitative studies, starting from the health coach's perspective on successful coaching, progressively zooming in on the potential role and impact of technology as part of the coaching process. Our main finding is that coaches are concerned that introducing technology in the coaching process puts too much emphasis on behavioral information, lowering the attention for the client's lived experience, while understanding those experiences is key for successful coaching. We summarize our insights in a multi-channel communication model and draw implications for the design of supporting technology in health coaching.

End-user acceptance is considered as a significant factor influencing the success of enterprise information system (EIS) implementations and operations. This study conceptualizes three aspects of EIS user interfaces (UIs), namely information overload, control familiarity, and UI fit, and proposes a model to understand their effect on two major factors that are considered to influence the end-user acceptance of these systems: EIS end user’s performance expectancy and effort expectancy. We developed a theoretical model and multiitem scales for the proposed EIS UI characteristics and tested the model empirically with data from a survey performed with a sample 98 EIS end users. The results from our test provide evidence for the key role that EIS UI design plays in the end user’s performance and effort expectancy.

The number of people with an age above 65 is increasing, and many live longer. Most seniors prefer to stay at their own home. Within the area of ambient assisted living (AAL) technology solutions have been aimed to assist seniors in the challenges that can arise when wanting to live independently. However, technology acceptance has been rather low, also due to stigmatization when using assistive systems. New technologies, such as the smartwatch, which is unobtrusive and not recognized as an assistive device by outsiders, have the potential to improve the autonomy and independence of seniors. This research aims to investigate the potential barriers and drivers of smartwatch use by seniors, by means of conducting a diary study and interviews. Results showed that the acceptance of the smartwatch depended mainly on the usability, interest and added value of the smartwatch. Additionally, the findings indicate that changes to the smartwatch need to be made in order to address the barriers that are found, and to ultimately enhance acceptance.

Our moral conscience as the “inner light” that guides us shines brighter during moments of ethical conflicts, when we notice a tension between our many oughts and/or wants. We present the first analyses on speech related stress and affect in accounts of moral conflicts. For our exploratory study, we started with interviews on moral and immoral events at work with entrepreneurs. Qualitative analysis revealed that interviewees do share personal moral conflicts without researchers probing for them. Quantitative analysis showed quiet and even toned voice features when discussing moral conflicts, and speech was laced with emotively positive and negative words, though more negative words were used. Moreover, we find promising results on our automatic classification experiment using speech features. How and what moral conflicts people deliberate on in real-life may be pertinent to future research in affective computing, as well as applications for decision-making support, ethical competences coaching, therapy, and healthy moral selfhood.

Personal informatics (PI) systems allow users to collect and review personally relevant information. The purpose commonly envisioned for these systems is that they provide users with actionable, data-driven self-insight to help them change their behavioral patterns for the better. Here, we review relevant theory as well as empirical evidence for this self-improvement hypothesis. From a corpus of 6,568, only 24 studies met the selection criteria of being a peer-reviewed empirical study reporting on actionable, data-driven insights from PI data, using a “clean” PI system with no other intervention techniques (e.g., additional coaching) on a nonclinical population. First results are promising—many of the selected articles report users gaining actionable insights—but we do note a number of methodological issues that make these results difficult to interpret. We conclude that more work is needed to investigate the self-improvement hypothesis and provide a set of recommendations for future work.

In this work we investigate the use of behavior feasibility to adapt and personalize lifestyle-targeting recommender systems for the prevention and treatment of hypertension. Based on survey data (N=300) we model the feasibiliy of 63 behaviors through a Rasch model, describing the engagement in a behavior as a function of the behavior's difficulty and the person's ability. We formulate two feasibility-tailored recommendation strategies that utilize the Rasch model. The engagement maximization strategy aims at maximizing the probability of engagement by proposing very feasible behaviors while the motivation maximization strategy aims to challenge users by matching the difficulty of the advice with the ability of the user, thereby maximizing motivation. In an online study (N=150) we assessed user preference for either strategies (embodied as virtual coaches) in comparison with a random control strategy. Our results show that coaches selecting feasible health advice resonate better with the patient than control. In general patients significantly preferred the engagement maximization strategy over random advice on most factors, while patients with a medium level of ability significantly preferred the motivation maximization strategy on all factors.

Over the last decade, an increasing number of studies have focused on automated recognition of human emotions by machines. However, performances of machine emotion recognition studies are difficult to interpret because benchmarks have not been established. To provide such a benchmark, we compared machine with human emotion recognition. We gathered facial expressions, speech, and physiological signals from 17 individuals expressing 5 different emotional states. Support vector machines achieved an 82% recognition accuracy based on physiological and facial features. In experiments with 75 humans on the same data, a maximum recognition accuracy of 62.8% was obtained. As machines outperformed humans, automated emotion recognition might be ready to be tested in more practical applications.

a b s t r a c tWhat explains the experience of ''being there'' in a simulated or mediated environment?In recent years, research has pointed to various technological and psychological factors deemed important in eliciting this so-called experience of telepresence, including interactivity, sensory-motor integration, media transparency, and distal attribution.However, few theories exist that can combine these findings in a coherent framework.In the present paper, we formulate such a theoretical framework.We will argue that the experience of telepresence is a consequence of the way in which we are embodied, and that it extends naturally from the same ability that allows us to adjust to a slippery surface, or to the weight of a hammer.The importance of embodiment in the understanding of telepresence has been stated before, but these works have not yet fully addressed what it means to be embodied.We argue that ''having a human body'' means having a specific morphology, a body schema, and a body image.Subsequently we describe how tools and technological artifacts may be incorporated at each of these levels of embodiment, and the implications thereof for the experience of telepresence.

People with some signs of binocular dysfunctioning can be susceptible to visual complaints associated with viewing stereoscopic content at large viewing distances. Two performance measurements enabled to distinguish people by their binocular status (BS) in previous research: the ratio of performance of the Wilkins rate of reading test (WRRT) between 2-D and 3-D, and the vergence facility. In an experiment, first, an extensive optometric screening was carried out to differentiate visually asymptomatic young adults with good BS (GBS) (N= 27) from those with a moderate BS (MBS) (N= 6). Second, participants had to perform the WRRT at short viewing distance followed by a questionnaire under different screen disparity settings. The results reveal that the ratio of the WRRT between 0 and -1.5 screen disparity is an appropriate indicator of participants with MBS in comparison with participants with GBS. In addition, the results show that 0.75°of screen disparity is already problematic for people with MBS. We conclude that the WRRT-ratio has potential as a BS test in consumer applications to provide individual settings for comfortable screen disparities based on viewers' BS.

Despite a variety of new communication technologies, loneliness is prevalent in Western countries. Boosting emotional communication through intimate connections has the potential to reduce loneliness. New technologies might exploit biosignals as intimate emotional cues because of their strong relationship to emotions. Through two studies, we investigate the possibilities of heartbeat communication as an intimate cue. In the first study (N = 32), we demonstrate, using self-report and behavioral tracking in an immersive virtual environment, that heartbeat perception influences social behavior in a similar manner as traditional intimate signals such as gaze and interpersonal distance. In the second study (N = 34), we demonstrate that a sound of the heartbeat is not sufficient to cause the effect; the stimulus must be attributed to the conversational partner in order to have influence. Together, these results show that heartbeat communication is a promising way to increase intimacy. Implications and possibilities for applications are discussed.

Social connectedness, i.e. the experience of belonging and relatedness between people, is a central concept in understanding and evaluating communication media, in particular awareness systems. A generic measure based on this construct an support the design of such systems. The current paper describes the construction of two questionnaires for the measurement of this concept. These questionnaires were subsequently applied in survey studies in order to establish the structure of the concept and to identify the items that are suited for the measurement of its dimensions. One questionnaire was subjected to an initial validation. We conclude with some preliminary suggestions regarding (design) approaches to foster social connectedness.

This paper introduces robot intervention, a novel approach to usability testing with children. A social robot is used as a proxy for a test administrator who conducts an active intervention session remotely in a Wizard of Oz fashion. The motivation of the technique is that children will feel at ease and enjoy interacting with the social robot, and thus produce more frequent and informative verbalizations regarding their interaction with the product under test. First experiences regarding this method are positive with regards to the feasibility of the method and with regards to how well it is received by children.

This paper presents Reconexp, a diary method supported by a distributed application, which partly runs on a mobile device and partly on a website, enabling us to survey user attitudes, experiences and requirements in field studies. Reconexp combines aspects of the Experience Sampling Method and the Day Reconstruction Method aiming to reduce data loss, improve data quality and reduce burden put upon participants. We discuss our first experiences of using this method in the context of a study of communication needs of working parents with young children.

Recent ethnomethodological work in context and location awareness has indicated that location cues hold many socially meaningful cues for interaction. Location-aware technologies are therefore expected to bring about a shift in social life. Yet little is known about underlying psychological effects and the role of specific design decisions. The present research aims to experimentally test some of these effects. In a laboratory experiment participants' location in a virtual game world was shared. The effects of location Cueing frequency and Cueing mode (explicit or inferred closeness) on affinity, social presence, awareness, and game experience were explored. Higher cue frequencies resulted in higher perceived challenge and flow experienced in the game. The data also showed trends of heightened awareness and more behavioural engagement. A trend towards more psychological involvement was found when cues explicitly communicated that players shared a location in the game.

JPEG compression of the left and right components of a stereo image pair is a way to save valuable bandwidth when transmitting stereoscopic images. This paper presents results on the effects of camera-base distance (B) and JPEG coding on overall image quality, perceived depth, perceived sharpness, and perceived eye strain. In the experiment, two stereoscopic still scenes were used, varying in depth (three different camera-base distances: 0, 8, and 12 cm) and compression ratio (4 levels: original, 1:30, 1:40, and 1:60). All levels of compression were applied to both the left and right stereo image, resulting in a 4 × 4 matrix of all possible symmetric and asymmetric coding combinations. The observers were asked to assess image quality, sharpness, depth, and eye strain. Results showed that an increase in JPEG coding had a negative effect on image quality, sharpness, and eye strain, but had no effect on perceived depth. An increase in camera-base distance increased perceived depth and reported eye strain, but had no effect on perceived sharpness. Results on asymmetric and symmetric coding showed that the relationship between perceived image quality and average bit rate is not straightforward. In some cases, image quality ratings of a symmetric coded pair can be higher than for an asymmetric coded pair, even if the averaged bit rate for the symmetric pair is lower, than for the asymmetric pair. Furthermore, sharpness and eye strain correlated highly and medium, respectively, with perceived image quality.

In the current paper we hypothesize that providing peripheral awareness information to remotely located but socially close individuals will yield affective user benefits. An experiment in a controlled home-like environment was conducted to investigate the effects of providing different levels of peripheral awareness information on these affective benefits. In the experiment peripheral awareness aimed to support groups of friends to jointly watch a soccer match at remote locations. The experiment has shown that providing awareness information increases the social presence and the group attraction felt by individuals towards their remote partners. The experiment has provided concrete quantitative and qualitative evidence for the hypothesized benefits of supporting primary relationships through awareness systems and of the relevance of social presence as a requirement in the design of peripheral awareness displays.

A high-quality three-dimensional (3-D) broadcast service (3-D TV) is becoming increasingly feasible based on various recent technological developments combined with an enhanced understanding of 3-D perception and human factors issues surrounding 3-D TV. In this paper, 3-D technology and perceptually relevant issues, in particular 3-D image quality and visual comfort, in relation to 3-D TV systems are reviewed. The focus is on near-term displays for broadcast-style single- and multiple-viewer systems. We discuss how an image quality model for conventional two-dimensional images needs to be modified to be suitable for image quality research for 3-D TV. In this respect, studies are reviewed that have focused on the relationship between subjective attributes of 3-D image quality and physical system parameters that induce them (e.g., parameter choices in image acquisition, compression, and display). In particular, artifacts that may arise in 3-D TV systems are addressed, such as keystone distortion, depth-plane curvature, puppet theater effect, cross talk, cardboard effect, shear distortion, picket-fence effect, and image flipping. In conclusion, we summarize the perceptual requirements for 3-D TV that can be extracted from the literature and address issues that require further investigation in order for 3-D TV to be a success.

S.285-287

Two experiments are presented that were aimed to investigate the effects of stereoscopic filming parameters and display duration on observers' judgements of naturalness and quality of stereoscopic images. The paper first presents a literature review of temporal factors in stereoscopic vision, with reference to stereoscopic displays. Several studies have indicated an effect of display duration on performance-oriented (criterion based) measures. The experiments reported were performed to extend the study of display duration from performance to appreciation-oriented measures. In addition, the present study aimed to investigate the effects of manipulating camera separation, convergence distance, and focal length on perceived quality and naturalness, In the first experiment, using display durations of both 5 and 10 s, 12 observers rated the naturalness of depth and the quality of depth for stereoscopic still images. The results showed no significant main effect of the display duration. A small yet significant shift between naturalness and quality was found for both duration conditions. This result replicated earlier findings, indicating that this is a reliable effect, albeit content-dependent. The second experiment was performed using display durations ranging from 1 to 15 s. The results of this experiment showed a small yet significant effect of display duration. Whereas longer display durations do not have a negative impact on the appreciative scores of optimally reproduced stereoscopic images, observers do give lower judgements to monoscopic images and stereoscopic images with unnatural disparity values as display duration increases. In addition, the results of both experiments provide support for the argument that stereoscopic camera toe-in should be avoided if possible.