TY - JOUR A1 - Beierle, Felix A1 - Schobel, Johannes A1 - Vogel, Carsten A1 - Allgaier, Johannes A1 - Mulansky, Lena A1 - Haug, Fabian A1 - Haug, Julian A1 - Schlee, Winfried A1 - Holfelder, Marc A1 - Stach, Michael A1 - Schickler, Marc A1 - Baumeister, Harald A1 - Cohrdes, Caroline A1 - Deckert, Jürgen A1 - Deserno, Lorenz A1 - Edler, Johanna-Sophie A1 - Eichner, Felizitas A. A1 - Greger, Helmut A1 - Hein, Grit A1 - Heuschmann, Peter A1 - John, Dennis A1 - Kestler, Hans A. A1 - Krefting, Dagmar A1 - Langguth, Berthold A1 - Meybohm, Patrick A1 - Probst, Thomas A1 - Reichert, Manfred A1 - Romanos, Marcel A1 - Störk, Stefan A1 - Terhorst, Yannik A1 - Weiß, Martin A1 - Pryss, Rüdiger T1 - Corona Health — A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic JF - International Journal of Environmental Research and Public Health N2 - Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures. KW - mobile health KW - ecological momentary assessment KW - digital phenotyping KW - longitudinal studies KW - mobile crowdsensing Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-242658 SN - 1660-4601 VL - 18 IS - 14 ER - TY - JOUR A1 - Schobel, Johannes A1 - Probst, Thomas A1 - Reichert, Manfred A1 - Schlee, Winfried A1 - Schickler, Marc A1 - Kestler, Hans A. A1 - Pryss, Rüdiger T1 - Measuring mental effort for creating mobile data collection applications JF - International Journal of Environmental Research and Public Health N2 - To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N=80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials. KW - data collection KW - smart mobile devices KW - end-user programming KW - mental effort KW - usability study Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-203176 SN - 1660-4601 VL - 17 IS - 5 ER - TY - JOUR A1 - Schickler, Marc A1 - Reichert, Manfred A1 - Geiger, Philip A1 - Winkler, Jens A1 - Funk, Thomas A1 - Weilbach, Micha A1 - Pryss, Rüdiger T1 - Flexible development of location-based mobile augmented reality applications with AREA BT - Implementation of a serious game shows the flexibility of AREA JF - Journal of Ambient Intelligence and Humanized Computing N2 - Mobile applications have garnered a lot of attention in the last years. The computational capabilities of mobile devices are the mainstay to develop completely new application types. The provision of augmented reality experiences on mobile devices paves one alley in this field. For example, in the automotive domain, augmented reality applications are used to experience, inter alia, the interior of a car by moving a mobile device around. The device’s camera then detects interior parts and shows additional information to the customer within the camera view. Another application type that is increasingly utilized is related to the combination of serious games with mobile augmented reality functions. Although the latter combination is promising for many scenarios, technically, it is a complex endeavor. In the AREA (Augmented Reality Engine Application) project, a kernel was implemented that enables location-based mobile augmented reality applications. Importantly, this kernel provides a flexible architecture that fosters the development of individual location-based mobile augmented reality applications. The work at hand shows the flexibility of AREA based on a developed serious game. Furthermore, the algorithm framework and major features of it are presented. As the conclusion of this paper, it is shown that mobile augmented reality applications require high development efforts. Therefore, flexible frameworks like AREA are crucial to develop respective applications in a reasonable time. KW - Mobile augmented reality KW - Location-based algorithms KW - Mobile application engineering KW - Serious game KW - Mobile augmented reality game Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232773 SN - 1868-5137 VL - 11 ER -