Referent: Dipl.-Inform. Rüdiger Pryss, Universität Ulm, Institut für Datenbanken und Informationssysteme (DBIS), 89081 Ulm
Ort: Hörsaal 5, Ebene E, Uniklinik RWTH Aachen
Abstract:
Instead of using traditional paper-based questionnaires, more and more trials rely on electron-ic questionnaires running on smart mobile devices. However, existing survey tools do not allow deploying questionnaires on tablets or they lack substantial functionality. Other aspects not properly covered include user-guidance and the flexible enactment of digital question-naires (e.g., skip questions depending on already given answers).
To enable data collection in clinical trials with smart mobile devices, a domain-specific framework supporting the entire lifecycle of an electronic questionnaire (i.e., its creation, deployment, enactment, analysis and evolution) is required. Such a framework was developed in the QuestionSys project. First, based on methods known from end-user-programming, domain experts (i.e., psychologists or physicians) are enabled to create elec-tronic questionnaires for their trials without need of any programming skills. Second, a process-driven approach is followed to enable a flexible and valid enactment of
questionnaire instances on smart mobile devices. The framework also allows for the integration of external sensors (e.g., pulse tracker) to enhance the data collected. Third, the collected data can be analyzed based on user-defined rules to provide an on-demand evaluation. Altogether, process-driven, electronic questionnaires on smart mobile devices will change the way of collecting data in clinical trials fundamentally.
In the first part of the talk, the QuestionSys project will be presented in detail.
In particular, experiences obtained from several conducted trials with smart mobile devices will be presented. Furthermore, the architecture and goals of the QuestionSys project will presented. In the second part of the talk, the TrackYourTinnitus (TYT) project will be discussed. TYT is a project that gathers patient data in a long-running and large-scale trial using mobile crowd sensing services. The experiences and developed mobile services in this context will be presented and discussed.
