Designing for geo-referenced in-situ therapeutic scenarios

Abstract

Cognitive behavioral therapy and social competences and skills training sometimes rely on in-situ activities to improve the patients' condition. As the process evolves, therapists concede some autonomy to patients, allowing them to carry out those activities without the need for the former's presence. The ability to remotely track patient's activities provides an interesting solution to ensure their success, still encouraging their autonomy. This paper presents the design process and evaluation of a remote group monitoring and communication system for these two types of procedures. We use traditional group communication directives and augment them with georeferenced information, empowering therapists with critical data to track their patients live and remotely. We describe the design process of a high-fidelity prototype and discuss the results from an experimental study that assessed the system from a usability and functionality perspectives. Results fueled an interesting discussion regarding how geo-referenced information help users maintaining awareness when multi-tasking.

Collaboration technology in teams and organizations: Introduction to the special issue

“…Using mobile technology to remotely track a patient's activity is an interesting solution to ensure the success of the therapy. In their paper, designing for geo-referenced in-situ therapeutic scenarios, Duarte and Carriço (2016) discuss the design process of a tool set called InSiThe, which uses geo-referenced data to improve user awareness, allows different forms of group conversations, and provides region-based user tracking. Furthermore, the authors compare the proposed application suite to existing Google-based web services to assess the performance of the proposed tool.…”

Mobile Services for Green Living

“…Their role went beyond experiments or surveys, and they also tested and helped with the design and operation of certain platforms. Some participants contributed to a citizen science platform (MacDonald et al, 2015), sensor calibration (Bleser et al, 2015), and platform functionality tests (Duarte and Carriço, 2016).…”