Value Elicitation for a Socially Assistive Robot Addressing Social Anxiety: A Participatory Design Approach

Social anxiety is a prevalent mental health condition that can significantly impact overall well-being and quality of life. Despite its widespread effects, adequate support or treatment for social anxiety is often insufficient. Advances in technology, particularly in social robotics, offer promising opportunities to complement traditional mental health. As an initial step toward developing effective solutions, it is essential to understand the values that shape what is considered meaningful, acceptable, and helpful. In this study, a participatory design workshop was conducted with mental health academic researchers to elicit the underlying values that should inform the design of socially assistive robots for social anxiety support. Through creative, reflective, and envisioning activities, participants explored scenarios and design possibilities, allowing for systematic elicitation of values, expectations, needs, and preferences related to robot-supported interventions. The findings reveal rich insights into design-relevant values-including adaptivity, acceptance, and efficacy-that are core to support for individuals with social anxiety. This study highlights the significance of a research-led approach to value elicitation, emphasising user-centred and context-aware design considerations in the development of socially assistive robots.

Identifying public values and spatial conflicts in urban planning

Identifying the diverse and often competing values of citizens, and resolving the consequent public value conflicts, are of significant importance for inclusive and integrated urban development. Scholars have highlighted that relational, value-laden urban space gives rise to many diverse conflicts that vary both spatially and temporally. Although notions of public value conflicts have been conceived in theory, there are very few empirical studies that identify such values and their conflicts in urban space. Building on public value theory and using a case-study mixed-methods approach, this paper proposes a new approach to empirically investigate public value conflicts in urban space. Using unstructured participatory data of 4,528 citizen contributions from a Public Participation Geographic Information Systems in Hamburg, Germany, natural language processing and spatial clustering techniques are used to identify areas of potential value conflicts. Four expert workshops assess and interpret these quantitative findings. Integrating both quantitative and qualitative results, 19 general public values and a total of 9 archetypical conflicts are identified. On the basis of these results, this paper proposes a new conceptual tool of Public Value Spheres that extends the theoretical notion of public-value conflicts and helps to further account for the value-laden nature of urban space.