A Framework for Supporting Well-being using the Character Computing Ontology - Anxiety and Sleep Quality during COVID-19

Abstract The COVID-19 pandemic is affecting human behavior, increasing the demand for the cooperation between psychologists and computer scientists to develop technology solutions that can help people in order to promote well-being and behavior change. According to the conceptual Character-Behavior-Situation (CBS) triad of Character Computing, behavior is driven by an individual’s character (trait and state markers) and the situation. In previous work, a computational ontology for Character Computing (CCOnto) has been introduced. The ontology can be extended with domain-specific knowledge for developing applications for inferring certain human behaviors to be leveraged for different purposes. In this paper, we present a framework for developing applications for dealing with changes in well-being during the COVID-19 pandemic. The framework can be used by psychology domain experts and application developers. The proposed model allows the input of heuristic rules as well as data-based rule extraction for inferring behavior. In this paper, we present how CCOnto is extended with components of physical and mental well-being and how the framework uses the extended domain ontologies in applications for evaluating sleep habits, anxiety, and depression predisposition during the COVID-19 pandemic based on user-input data.