Adaptive user interfaces can make technology more accessible. Quite a number of conceptual and technical approaches have been proposed for adaptations to diverse user needs, multiple devices or multiple environments. Little work, however, has been directed at integrating all the essential aspects of adaptive user interfaces for accessibility in one system. In this paper, we present our generic MyUI infrastructure for increased accessibility through automatically generated adaptive user interfaces. The multimodal design patterns repository serves as the basis for a modular approach to individualized user interfaces. This open and extensible pattern repository makes the adaptation rules transparent for designers and developers who can contribute to the repository by sharing their knowledge about accessible design. The adaptation architecture and procedures enable user interface generation and dynamic adaptations during run-time. For the specification of an abstract user interface model, a novel statecharts-based notation has been developed. A development tool supports the interactive creation of the graphical user interface model.

Objective and Background: To contain the COVID-19 pandemic, public health actions have changed the everyday life with an inevitable impact on individuals and their social life. Since intact (socio-)psychological functioning and mental health are protective factors contributing to the immune system and preventing diseases, it is crucial to identify individuals with increased vulnerability.Methods: We conducted a German online survey from April until August 2020 investigating health-related, social, behavioral, and psychological effects of the COVID-19 pandemic. One hundred and seventy three adults participating in the survey were analyzed (39.9% male, age: M = 44.81±13.31). We explored effects on mental health by (a) clustering participants in two clusters and (b) analyzing the clusters using correlations and regression models.Results: Participants belonged either to a cluster characterized by higher general well-being or to a more concerned cluster depending on their responses. The correlation analysis revealed a significant negative relation between age and well-being with younger participants revealing higher depression scores in the concerned cluster. Furthermore, multiple regression models revealed that the number of risk factors only has a significant influence on psychological well-being in the concerned but not in the comfortable cluster.Conclusion: We found that especially participants at (a) younger age and (b) greater risk of a severe course of disease reported reduced mental well-being and seemed to be weakened in their psychological protective factors in our sample. These insights allow to provide tailored recommendations for preventive and immediate actions to promote psychological well-being and reduce stress.

No abstract

No abstract

No abstract