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The increasing mere presence of robots in everyday life does not automatically result in gradual acceptance of these systems by human users. Over the past years, we have conducted several studies with the goal to provide insight into the long-term process of social robots in domestic environments. This paper presents our overall conclusions from the combined findings of our multiple studies on social robot acceptance. We will provide insights from a user's perspective of what makes robots social, describe a phased framework of the long-term process of robot acceptance, present some key factors for social robot acceptance, offer guidelines to build better sociable robots, and provide some recommendations for conducting research in domestic environments. With sharing our experiences with conducting (long-term) user studies in domestic environments, we aim to serve to push this sub-field of HRI in real-world contexts forward and thereby the community at large

A common description of a social robot is for it to be capable of communicating in a humanlike manner. However, a description of what communicating in a ‘humanlike manner’ means often remains unspecified. This paper provides a set of social behaviors and certain specific features social robots should possess based on user’s experience in a longitudinal home study, discusses whether robots can actually be social, and presents some recommendations to build better social robots.

Older adults have a growing desire to remain independent and age in their own home environment. Policy makers support this wish, as the quality and quantity of institutional care cannot be guaranteed with the present health care budget. Ambient Assisted Living (AAL) technologies can meet the interests of both parties, by facilitating healthy and active aging in the home environment. However, those technologies are still in their infancy and the likelihood of their adoption remains uncertain. By conducting a literature study and a user-requirement study for a conceptual AAL application called SONOPA (Social Networks for Older Adults to Promote an Active Life), benefits and barriers to the adoption of AAL technologies, as perceived by the elderly user, were identified. The user-requirement study consisted of focus groups and interviews with older adults and elder care professionals, conducted in the UK, France and Belgium. Together, the literature study and the user-requirement study led to several design guidelines which direct the future development process of SONOPA and related AAL applications.

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.

In this work, we study social interactions in a work environment and investigate how the presence of other people changes personal behavior patterns. We design the visual processing algorithms to track multiple people in the environment and detect dyadic interactions using a discriminative classifier. The locations of the users are associated with semantic tasks based on the functions of the areas. Our learning method then deduces patterns from the trajectories of people and their interactions. We propose an algorithm to compare the patterns of a user in the presence and absence of social interactions. We evaluate our method on a video dataset collected in a real office. By detecting interactions, we gain insights in not only how often people interact, but also in how these interactions affect the usual routines of the users.

The goal of this study was to improve our understanding about how older people use social robots in domestic environments and in particular whether and how they build relationships with these robots. Three participants interacted with the Nabaztag, a social robot, for a 10-day period in their own home environment. Some of our findings are (1) utilitarian-, hedonic-, and social factors are important when accepting social robots, (2) utilitarian-, hedonic- and social factors are important for building a relationship with the Nabaztag, (3) there is a relationship between name-calling and relationship building and (4) there is a relationship between using non-verbal- and verbal communication and relationship building.

Ambient intelligence (AmI) is a growing interdisciplinary area where the focus is shifted towards users instead of merely emphasizing the technological opportunities of AmI. Different methods are employed to understand the adoption of AmI appliances by users. However, these are often small-scale methods that are focused on specific subgroups. Large scale quantitative studies to understand the adoption of AmI appliances are scarce. In this study, a questionnaire was designed to examine how the Dutch people (n = 1221) perceive AmI appliances for domestic settings. Findings show that intention to adopt AmI appliances was low and that respondents had a negative to neutral attitude towards AmI appliances. On the basis of structural equation analysis, results suggest that adoption of AmI appliances could be explained by outcome expectancies of AmI appliances. The potential implications of the findings are discussed.

Ambient Intelligence (AmI) for the home uses information and communication technologies to make users’ everyday life more comfortable. AmI is still in its developmental phase and is headed towards the first stages of diffusion. Characteristics of AmI design can be observed, among others, in the promotion material of initial producers. A literature study revealed that AmI originally envisioned a central role for the user, convenience that AmI offers them and that attention should be paid to critical policy issues such as privacy and a potential loss of freedom. A content analysis of current promotion material of several high-tech companies revealed that these original ideas are not all reflected in the material. Attributes which were used most in the promotion material were ‘connectedness’, ‘control’, ‘easiness’ and ‘personalization’. An analysis of the pictures in the promotion material showed that almost half of the pictures contained no humans but appliances. These results only partly correspond to the original vision on AmI, since the emphasis is now on technology. The results represent a serious problem, since both users, as well as critical policy issues are underexposed in the current promotion material.

The topic of this thesis - the blending of face-to-face and web-based interventions - and the related question of whether a blended treatment offers "the best of both worlds" was taken forward in this thesis in the scope of smoking cessation treatment. In order to contribute to the research on smoking cessation treatment and to improve clinical practice, the Blended Smoking Cessation Treatment (BSCT), which is the focus of this work, was addressed by highlighting three themes: user experience, adherence and effectiveness. Patients experienced BSCT predominantly positively. However, BSCT's UX is characterized by a "hedonistic gap" resulting from the mostly negative identification, stimulation and evocation of the Web-mode. This gap was then compensated for by the F2F-mode, giving an indication that BSCT may be "the best of both worlds", as the strength of one mode (in this case the stronger hedonistic aspects of the F2F-mode) could offset the weaknesses of the other mode. However, this compensation was largely unidirectional: the F2F-mode compensated for the Web-mode but not vice versa. For adherence, to compare face-to-face versus blended treatment, the picture was that patients spent similar amounts of time in BSCT and F2F without it being clear whether this was to be considered high or low adherence, as different measurement procedures and evaluations prevented a simple comparison of the two results in the end. However, at least for BSCT, the two measuring methods brought up an interesting point: On the one hand, BSCT patients showed little activity, but at the same time exhausted the planned treatment time. Also, for BSCT it was noticeable that within BSCT the adherence for the two modes was very different. Contrary to the planned 50-50 distribution, patients only used the Web-mode for about 1/3 of the time and the F2F-mode for 2/3 of the time. For effectiveness, contrary to our expectations, we did not find any evidence of non-inferiority of BSCT to F2F. The most important measurement - cotinine-validated point prevalence abstinence - showed significantly lower abstinence rates of BSCT (4.8%) compared to F2F (17.5%) in the intention-to-treat analysis (difference of 12.7 (95% CI 6.2-19.4); P

Who takes care of our older adults? According to the European Union, smart technologies that support independent living and active aging, introduced as ‘Ambient Assisted Living’ (AAL), are the future for our aging population. Promises of AAL include saving long-term care costs, improving the quality of care, unburdening family caregivers, and increasing the older adults’ independence and overall quality of life. While the policy enthusiasm for AAL technology is high, it is unclear if the potential users of AAL are willing to embrace AAL technologies in their daily lives. This dissertation addressed this issue by focusing on the perspective of older adults and their caregivers. Using a combination of qualitative and quantitative approaches, we developed a comprehensive and theoretically grounded understanding of how and why users perceive AAL technologies in a certain way. Important factors that drive or hinder the acceptance were identified. These insights resulted in a model of AAL acceptance that was validated in a representative sample (n = 1296) of the Dutch older adult population. This dissertation contributes to a more user-driven approach in AAL research and development and has important implications for researchers, developers and policy makers alike. We hope that our results will guide future research efforts, design and policy directions in the AAL field.

Over the most recent decades, the field of social robotics has advanced rapidly. There are a growing number of different types of robots, and their roles within society are expanding. This dissertation has argued that investigating the long-term acceptance of social robots in home environments is necessary for the successful diffusion of these types of robots within society. The findings of this dissertation indicate that usefulness is a requisite for social robot acceptance and that certain additional important acceptance variables may further explain why people continue to use a social robot in their own homes. These additional acceptance variables show that the acceptance of a social robot for domestic use increases when future users believe that they possess the necessary skills to use a social robot, when they perceive that having such a robot enhances their status, and when they expect that such a robot provides more enjoyable interactions, behaves less sociably, and causes fewer privacy concerns. However, when examining the long-term use of social robots in home environments, it appears that the importance of the acceptance variables in explaining social robot acceptance changes over time, shifting from control beliefs to attitudinal beliefs. It is believed that the importance of the acceptance variables depends on the development stage in which the technology is located (Peters, 2011). When people gain experiences with a social robot, other acceptance variables explain people’s intention to continue using it compared to the acceptance variables that explained their initial adoption. Concerning human-robot relationships, the studies presented in this dissertation indicate that people are initially reluctant to build a relationship with a robot and deny the possibility that such a relationship will occur for them. However, after people have adopted a social robot and have begun to use it in their own homes, some people acknowledge that they have established some type of relationship with the robot. However, not all people seem to appreciate a robot’s social behavior, and it seems that people remain unfamiliar with the possibilities of human-robot relationships and that the actual use and interactions with social robots reveal what types of relationships people are willing to establish with these robots. The findings of this dissertation may help both researchers and developers of social robots to further develop an integrated theory or model of social robot acceptance that can describe and explain this acceptance in more real-world contexts, such as the home.