Towards a User Integration Framework for Personal HealthDecision Support and Recommender Systems

Abstract

Supporting personal health with Decision Support Systems (DSS)and, specifically, recommender systems (RS) is a promising and growing area of research. Integrating the user in the loop is vital in such health systems due to the complexity of recommendations, gravity of the decisions and the reliance on user autonomy. However, for such a purpose, to the best of our knowledge, there exists no profound or comprehensive framework nor model to guide system designers to exploit the full potential of integrating users in the system’s reasoning process by design. In this paper, we present a multifaceted user integration framework in personal health-related DSS and RS. This framework, with three main components, has been derived from an iterative mixed-methods development and evaluation procedure, including expert workshops and extensive multidisciplinary literature reviews. Users are accordingly integrated into the whole process from system reasoning until decision making through the following actionable design strategies: (1) Empower: Enabling them to understand the result generation and implications, (2) Encourage: encouraging them to question and reflect system outcomes and to get involved in the generation process and (3) Engage: enabling them to take an active role by facilitating and providing opportunities for user control. The framework offers support to designers of personal health-related DSS and RS in properly integrating users into their systems.

Publication
In * Proceedings of the 29th Conference on User Modeling, Adaptation and Personalization, June 21–25, 2021, Utrecht, the Netherlands & Online*
Avatar
Helma Torkamaan
Researcher

My research interests include Human-computer interaction, recommender systems, e-health and ubiqoutous computing.

Next
Previous

Related