Chronic stress is widespread, yet digital stress-management tools can paradoxically worsen it through screen fatigue and technology-induced anxiety. This study explores a low-tech, non-digital alternative. We conducted ceramic-making workshops with 20 participants experiencing stress, who crafted WarmStones, personalized handheld ceramic objects for haptic comfort and self-soothing. After four weeks of daily use, we conducted artifact analysis and interviews, revealing a design space of shapes, textures, and interaction patterns that support stress regulation. We discuss how everyday ceramic objects can become tactile comfort tools, and offer design implications for texture-rich, personalized objects that foster moment-to-moment calm.

The goal of this study is to identify factors that support and enhance older adults’ creative experiences in human-robot co-creativity. Because the research into the use of robots for creativity support with older adults remains underexplored, we carried out an exploratory case study. We took a participatory approach and collaborated with professional art educators to design a course "Drawing with Robots" for adults aged 65 and over. The course featured human-human and human-robot drawing activities with various types of robots. We observed collaborative drawing interactions, interviewed participants on their experiences, and analyzed collected data. Findings show that participants preferred acting as curators, evaluating creative suggestions from the robot in a teacher or coach role. When we enhanced a robot with a multimodal Large Language Model (LLM), participants appreciated its spoken dialogue capabilities. They reported however, that the robot’s feedback sometimes lacked an understanding of the context, and sensitivity to their artistic goals and preferences. Our findings highlight the potential of LLM-enhanced robots to support creativity and offer future directions for advancing human-robot co-creativity with older adults.

Maintaining the child-robot relationship after a significant break, such as a holiday, is an important step for developing sustainable social robots for education. We ran a four-session user study (n = 113 children) that included a nine-month break between the third and fourth session. During the study, participants practiced math with the help of a social robot math tutor. We found that social personalization is an effective strategy to better sustain the child-robot relationship than the absence of social personalization. To become reacquainted after the long break, the robot summarizes a few pieces of information it had stored about the child. This gives children a feeling of being remembered, which is a key contributor to the effectiveness of social personalization. Enabling the robot to refer to information previously shared by the child is another key contributor to social personalization. Conditional for its effectiveness, however, is that children notice these memory references. Finally, although we found that children's interest in the tutoring content is related to relationship formation, personalizing the topics did not lead to more interest in the content. It seems likely that not all of the memory information that was used to personalize the content was up-to-date or socially relevant.

Smart glasses were perceived to be potentially revolutionary for healthcare, however, there is only limited research on the acceptance and social implications of smart glasses in healthcare. This study aims to get a better insight into the theoretical foundations and the purpose was to identify themes regarding adoption, mediation, and the use of smart glasses from the perspective of healthcare professionals. A qualitative research design with focus groups was used to collect data. Three focus groups with 22 participants were conducted. Data were analyzed using content analysis. Our analysis revealed six overarching themes related to the anticipated adoption of smart glasses: knowledge, innovativeness, use cases, ethical issues, persuasion, and attitude. Nine themes were found related to anticipated mediation and use of smart glasses: attention, emotions, social influences, design, context, camera use, risks, comparisons to known products, and expected reaction and might influence the acceptance of smart glasses.

To benefit from the social capabilities of a robot math tutor, instead of being distracted by them, a novel approach is needed where the math task and the robot's social behaviors are better intertwined. We present concrete design specifications of how children can practice math via a personal conversation with a social robot and how the robot can scaffold instructions. We evaluated the designs with a three-session experimental user study (n = 130, 8-11 y.o.). Participants got better at math over time when the robot scaffolded instructions. Furthermore, the robot felt more as a friend when it personalized the conversation.

This review is the first step in a long-term research project exploring how social robotics and AI-generated content can contribute to the creative experiences of older adults, with a focus on collaborative drawing and painting. We systematically searched and selected literature on human-robot co-creativity, and analyzed articles to identify methods and strategies for researching co-creative robotics. We found that none of the studies involved older adults, which shows the gap in the literature for this often involved participant group in robotics research. The analyzed literature provides valuable insights into the design of human-robot co-creativity and informs a research agenda to further investigate the topic with older adults. We argue that future research should focus on ecological and developmental perspectives on creativity, on how system behavior can be aligned with the values of older adults, and on the system structures that support this best.

Social robots have been introduced in different fields such as retail, health care and education. Primary education in the Netherlands (and elsewhere) recently faced new challenges because of the COVID-19 pandemic, lockdowns and quarantines including students falling behind and teachers burdened with high workloads. Together with two Dutch municipalities and nine primary schools we are exploring the long-term use of social robots to study how social robots might support teachers in primary education, with a focus on mathematics education. This paper presents an explorative study to define requirements for a social robot math tutor. Multiple focus groups were held with the two main stakeholders, namely teachers and students. During the focus groups the aim was 1) to understand the current situation of mathematics education in the upper primary school level, 2) to identify the problems that teachers and students encounter in mathematics education, and 3) to identify opportunities for deploying a social robot math tutor in primary education from the perspective of both the teachers and students. The results inform the development of social robots and opportunities for pedagogical methods used in math teaching, child-robot interaction and potential support for teachers in the classroom.

In an aging population, the prevalence of people with dementia is increasing. Intelligent environments can offer a solution to support people in the early stages of dementia, who often experience problems with maintaining their day-night rhythm. The focus of this work is developing an Intelligent Environment for assisting these people with their daily structure while living independently at home. Three co-creation methods with several stakeholder groups were used to elicit requirements and develop a prototype of an Intelligent Environment. Participants were involved in sessions using Mind Maps (N=55), Idea Generation Cards (N=35), and in a multidisciplinary design team with representatives of eight organizations. The result of these sessions was a set of 10 requirements for the Intelligent Environment on the following topics: context-awareness, pattern recognition, adaptation, support, personalization, autonomy, modularity, dementia proof interaction, costs, data and privacy. Based on these requirements, several scenarios were developed to explicate such an environment for supporting people with early dementia. The design team translated the requirements to a real-life prototype of an Intelligent Environment integrated into a demonstration home. The prototype serves as a basis for further development of Intelligent Environments to enable people with dementia to live longer independently at home.

Traditional turn-by-turn navigation approaches often do not provide sufficiently detailed information to help people with a visual impairment (PVI) to successfully navigate through an urban environment. To provide PVI with clear and supportive navigation information we created Sidewalk, a new wayfinding message syntax for mobile applications. Sidewalk proposes a consistent structure for detailed wayfinding instructions, short instructions and alerts. We tested Sidewalk with six PVI in the urban center of Amsterdam, the Netherlands. Results show that our approach to wayfinding was positively valued by the participants.

People with a visual impairment (PVI) often experience difficulties with wayfinding. Current navigation applications have limited communication channels and do not provide detailed enough information to support PVI. By transmitting wayfinding information via multimodal channels and combining these with wearables, we can provide tailored information for wayfinding and reduce the cognitive load. This study presents a framework for multimodal wayfinding communication via smartwatch. The framework consists of four modalities: audio, voice, tactile and visual. Audio and voice messages are transmitted using a bone conduction headphone, keeping the ears free to focus on the environment. With a smartwatch vibrations are directed to a sensitive part of the body (i.e., the wrist), making it easier to sense the vibrations. Icons and short textual feedback are viewed on the display of the watch, allowing for hands-free navigation.

Many independent studies in social robotics and human–robot interaction have gained knowledge on various factors that affect people’s perceptions of and behaviors toward robots. However, only a few of those studies aimed to develop models of social robot acceptance integrating a wider range of such factors. With the rise of robotic technologies for everyday environments, such comprehensive research on relevant acceptance factors is increasingly necessary. This article presents a conceptual model of social robot acceptance with a strong theoretical base, which has been tested among the general Dutch population (n = 1,168) using structural equation modeling. The results show a strong role of normative believes that both directly and indirectly affect the anticipated acceptance of social robots for domestic purposes. Moreover, the data show that, at least at this stage of diffusion within society, people seem somewhat reluctant to accept social behaviors from robots. The current findings of our study and their implications serve to push the field of acceptable social robotics forward. For the societal acceptance of social robots, it is vital to include the opinions of future users at an early stage of development. This way future designs can be better adapted to the preferences of potential users.

Research on why people refuse or abandon the use of technology in general, and robots specifically, is still scarce. Consequently, the academic understanding of people's underlying reasons for non-use remains weak. Thus, vital information about the design of these robots including their acceptance and refusal or abandonment by its users is needed. We placed 70 autonomous robots within people's homes for a period of six months and collected reasons for refusal and abandonment through questionnaires and interviews. Based on our findings, the challenge for robot designers is to create robots that are enjoyable and easy to use to capture users in the short-term, and functionally-relevant to keep those users in the longer-term. Understanding the thoughts and motives behind non-use may help to identify obstacles for acceptance, and therefore enable developers to better adapt technological designs to the benefit of the users.

With an expected growth of robots in our future society, we believe that potential implications for robot applications should be addressed. Therefore, we conducted an online questionnaire among the general Dutch population (n= 1162) to map the societal impact of robots by identifying potential benefits and disadvantages of future robot applications. People differentiate between several applications, and more realistic applications were also rated more positively. Overall, people associate a future robot society with the positive consequences of efficiency, decrease of casualties, and convenience, and the negative consequences of job loss and robots' lack of social skills. Our qualitative approach provides an in-depth evaluation of potential future robot applications, which could prompt guidelines for the development of acceptable robots.

The acceptability of robots in homes does not depend solely on the practical benefits they may provide, but also on complex relationships between cognitive, affective and emotional components of people's associations of and attitudes towards robots. This important area of research mainly relies on explicit measures, and alternative measures are rather unexplored. We therefore studied both implicit and explicit associations of robots, and found inconsistent findings between implicit and explicit measures. Our findings speak in favor of the proposition that people are actually more negative about robots than they consciously express. Since associations play an important role when people form attitudes towards robots we stress that caution when researchers and designers solely rely on explicit measures in their research.

Robotics researchers foresee that robots will become ubiquitous in our natural environments, such as our homes. For a successful diffusion of social robots, it is important to study the user acceptance of such robots. In an online survey, we have investigated the acceptance of three different possible roles for domestic social robots and the preferred appearance. The results show that, although most people prefer a humanoid robot for domestic purposes, the role for which a social robot is build affects the choice for a robotic appearance made by potential future users. When comparing the acceptance of the three different roles, people evaluate the companion robot more negatively on the different acceptance variables. Implications of these results are discussed.

People tend to treat robots as social actors and assign personality attributes to them. This study investigates the influence of expectation setting on the users' attribution of personality traits to the robot and their impressions of that robot. Results show that personality attribution is depending on people's prior expectations of the interaction. Moreover, people evaluate a robot better when they assigned it with a complementary personality and when they had high prior expectations of that robot.

This study identifies the design preferences of robots for domestic use. In an online survey, participants rated 16 robot pictures on several evaluation criteria. Results show that overall anthropomorphic robots are more positively rated than either zoomorphic, caricatured or functional robots. Moreover, negative feelings towards robot (e.g. negative attitudes and anxiety towards robots) negatively affected the design evaluations. Providing future users with positive information about domestic robots could improve their feelings towards robots, which, in turn, raises their ratings of robotic designs.

This paper examines the relation between an interaction with a robot and peoples' attitudes and emotion towards robots. In our study, participants have had an acquaintance talk with a social robot and both their general attitude and anxiety towards social robots were measured before and after the interaction. This study has found mixed results as compared to earlier studies. However, the utility of negative attitude and anxiety to explain human behavior in interactions with robots is supported. Furthermore, a human-robot interaction (HRI) changes people's attitudes and anxiety towards robots. Thus, from a design perspective, it seems important to further investigate which aspects of robots evoke what type of emotions and how this influences the overall evaluation of robots.