Pro-active positioning of a social robot intervening upon behavioral disturbances of persons with dementia in a smart nursing home

Behavioral disturbances of persons with dementia residing in a nursing home impose a significant burden on other residents and on the care staff. A social robot can provide an adequate technological support tool for the caregivers by approaching a resident that exhibits a behavioral disturbance. In this paper, we focus on how to position the robot in the nursing home, taking into account the profile and location of the residents. We minimize the time between the detection of a behavioral disturbance and the robot having arrived near the resident and starting an interaction scenario. Our algorithm is evaluated using realistic data that was collected during 3 months in two Belgian nursing homes.     

Reducing car use by volitional strategy of action and coping planning enhancement

Personalized travel plans have been regarded as potentially effective soft measures in mobility management. This research conducted a randomized social experiment aiming at citizen car-use reduction, and examined the effect of implementing two personalized travel plans: action plans and coping plans. The two types of plans were designed respectively for enhancing action planning and coping planning as the volitional factors of behavior change. The results supported the effectiveness of the combined action-plus-coping plan intervention in reducing car use, but not of the action plan alone intervention. In addition, the influence of intervention on behavioral intention, action planning, and coping planning, were also presented.     

Vectors into the Future of Mass and Interpersonal Communication Research: Big Data,Social Media,and Computational Social Science

Simultaneous developments in big data, social media, and computational social science have set the stage for how we think about and understand interpersonal and mass communication. This article explores some of the ways that these developments generate 4 hypothetical “vectors”—directions—into the next generation of communication research. These vectors include developments in network analysis, modeling interpersonal and social influence, recommendation systems, and the blurring of distinctions between interpersonal and mass audiences through narrowcasting and broadcasting. The methods and research in these arenas are occurring in areas outside the typical boundaries of the communication discipline but engage classic, substantive questions in mass and interpersonal communication.     

Turning a blind eye: Meritocracy moderates the impacts of social status on corruption perception

Findings on the effect of social status on corruption perception are mixed. To make sense of the mixed results, three studies were conducted to examine whether meritocracy moderates this effect. In Study 1, we measured all variables using a questionnaire-based correlational design. In the preregistered Study 2, we adopted an experimental design in which we manipulated social status using a false feedback paradigm and measured corruption perception and meritocracy. In Study 3, we manipulated meritocracy using a scrambled sentence task and measured its effect on the relationship between social status and corruption perception. The results consistently demonstrated that meritocracy could moderate the influence of social status on corruption perception. Specifically, social status was negatively associated with corruption perception when meritocracy was weak, whereas the association was not significant when meritocracy was strong. Our results suggest that meritocracy critically affects acknowledgment of the pervasiveness of social injustice and even deters the disadvantaged from fighting against corruption.     

A framework for designing socially assistive robot interactions

Robots are increasingly tested in different socially assistive scenarios. Future applications range from dieting, coaching, tutoring to autism therapy. In such applications the success of the system is commonly evaluated by the ability to encourage the user to keep up with a task. Hence, one important requirement for supportive systems is to have an interactional motivational model that formalizes the way how users can be assisted. In this paper we describe our framework for coordinating motivational interaction scenarios with socially assistive robots (SAR) in the context of sport assistance. We exemplify three different sport scenarios where we have used the same motivational interaction model. Furthermore, we show how this model can be used to systematically test the different aspects of motivation in the context of SAR in sport domains. Therefore, we have conducted an experiment to evaluate the importance of acknowledgement from SAR for human interaction partners. The results show that users exercise longer if acknowledgment is included into the motivational model.     

Providing an analytic structure for key system design choices

The design of a system, especially a system architecture, requires the balancing of multiple performance parameters with the system cost and other implementation issues. Multi-attribute utility theory provides a structured, coherent framework for conducting an analysis in which system designs are evaluated on multiple performance parameters. This paper describes the application of multi-attribute utility analysis to the design of the Worldwide Digital Signal Systems Architecture (WWDSA), a telecommunications system, by the United States' Defense Communications Agency (now called the Defense Information Systems Agency). The advantages of using multi-attribute utility theory during the system design are highlighted. In addition, we discuss several key analytical issues that led to this application being a success in the eyes of the decision makers.