@article{BeierleSchobelVogeletal.2021, author = {Beierle, Felix and Schobel, Johannes and Vogel, Carsten and Allgaier, Johannes and Mulansky, Lena and Haug, Fabian and Haug, Julian and Schlee, Winfried and Holfelder, Marc and Stach, Michael and Schickler, Marc and Baumeister, Harald and Cohrdes, Caroline and Deckert, J{\"u}rgen and Deserno, Lorenz and Edler, Johanna-Sophie and Eichner, Felizitas A. and Greger, Helmut and Hein, Grit and Heuschmann, Peter and John, Dennis and Kestler, Hans A. and Krefting, Dagmar and Langguth, Berthold and Meybohm, Patrick and Probst, Thomas and Reichert, Manfred and Romanos, Marcel and St{\"o}rk, Stefan and Terhorst, Yannik and Weiß, Martin and Pryss, R{\"u}diger}, title = {Corona Health — A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic}, series = {International Journal of Environmental Research and Public Health}, volume = {18}, journal = {International Journal of Environmental Research and Public Health}, number = {14}, issn = {1660-4601}, doi = {10.3390/ijerph18147395}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242658}, year = {2021}, abstract = {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.}, language = {en} } @article{PrakashUnnikrishnanPryssetal.2021, author = {Prakash, Subash and Unnikrishnan, Vishnu and Pryss, R{\"u}diger and Kraft, Robin and Schobel, Johannes and Hannemann, Ronny and Langguth, Berthold and Schlee, Winfried and Spiliopoulou, Myra}, title = {Interactive system for similarity-based inspection and assessment of the well-being of mHealth users}, series = {Entropy}, volume = {23}, journal = {Entropy}, number = {12}, issn = {1099-4300}, doi = {10.3390/e23121695}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-252333}, year = {2021}, abstract = {Recent digitization technologies empower mHealth users to conveniently record their Ecological Momentary Assessments (EMA) through web applications, smartphones, and wearable devices. These recordings can help clinicians understand how the users' condition changes, but appropriate learning and visualization mechanisms are required for this purpose. We propose a web-based visual analytics tool, which processes clinical data as well as EMAs that were recorded through a mHealth application. The goals we pursue are (1) to predict the condition of the user in the near and the far future, while also identifying the clinical data that mostly contribute to EMA predictions, (2) to identify users with outlier EMA, and (3) to show to what extent the EMAs of a user are in line with or diverge from those users similar to him/her. We report our findings based on a pilot study on patient empowerment, involving tinnitus patients who recorded EMAs with the mHealth app TinnitusTips. To validate our method, we also derived synthetic data from the same pilot study. Based on this setting, results for different use cases are reported.}, language = {en} } @article{SchobelProbstReichertetal.2020, author = {Schobel, Johannes and Probst, Thomas and Reichert, Manfred and Schlee, Winfried and Schickler, Marc and Kestler, Hans A. and Pryss, R{\"u}diger}, title = {Measuring mental effort for creating mobile data collection applications}, series = {International Journal of Environmental Research and Public Health}, volume = {17}, journal = {International Journal of Environmental Research and Public Health}, number = {5}, issn = {1660-4601}, doi = {10.3390/ijerph17051649}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203176}, year = {2020}, abstract = {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.}, language = {en} } @article{UnnikrishnanSchleicherShahetal.2020, author = {Unnikrishnan, Vishnu and Schleicher, Miro and Shah, Yash and Jamaludeen, Noor and Pryss, Ruediger and Schobel, Johannes and Kraft, Robin and Schlee, Winfried and Spiliopoulou, Myra}, title = {The effect of non-personalised tips on the continued use of self-monitoring mHealth applications}, series = {Brain Sciences}, volume = {10}, journal = {Brain Sciences}, number = {12}, issn = {2076-3425}, doi = {10.3390/brainsci10120924}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-219435}, year = {2020}, abstract = {Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients' quality of life. Recent advances in mHealth have enabled patients to maintain a 'disease journal' of ecologically-valid momentary assessments, improving patients' own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients' perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A \& Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.}, language = {en} } @article{SchleeNeffSimoesetal.2022, author = {Schlee, Winfried and Neff, Patrick and Simoes, Jorge and Langguth, Berthold and Schoisswohl, Stefan and Steinberger, Heidi and Norman, Marie and Spiliopoulou, Myra and Schobel, Johannes and Hannemann, Ronny and Pryss, R{\"u}diger}, title = {Smartphone-guided educational counseling and self-help for chronic tinnitus}, series = {Journal of Clinical Medicine}, volume = {11}, journal = {Journal of Clinical Medicine}, number = {7}, issn = {2077-0383}, doi = {10.3390/jcm11071825}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267295}, year = {2022}, abstract = {Tinnitus is an auditory phantom perception in the ears or head in the absence of a corresponding external stimulus. There is currently no effective treatment available that reliably reduces tinnitus. Educational counseling is a treatment approach that aims to educate patients and inform them about possible coping strategies. For this feasibility study, we implemented educational material and self-help advice in a smartphone app. Participants used the educational smartphone app unsupervised during their daily routine over a period of four months. Comparing the tinnitus outcome measures before and after smartphone-guided treatment, we measured changes in tinnitus-related distress, but not in tinnitus loudness. Improvements on the Tinnitus Severity numeric rating scale reached an effect size of 0.408, while the improvements on the Tinnitus Handicap Inventory (THI) were much smaller with an effect size of 0.168. An analysis of user behavior showed that frequent and intensive use of the app is a crucial factor for treatment success: participants that used the app more often and interacted with the app intensively reported a stronger improvement in the tinnitus. Between study allocation and final assessment, 26 of 52 participants dropped out of the study. Reasons for the dropouts and lessons for future studies are discussed in this paper.}, language = {en} } @article{NandiCrombachElbertetal.2020, author = {Nandi, Corina and Crombach, Anselm and Elbert, Thomas and Bambonye, Manass{\´e} and Pryss, R{\"u}diger and Schobel, Johannes and Weierstall-Pust, Roland}, title = {The cycle of violence as a function of PTSD and appetitive aggression: A longitudinal study with Burundian soldiers}, series = {Aggressive Behavior}, volume = {46}, journal = {Aggressive Behavior}, number = {5}, doi = {10.1002/ab.21895}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-218235}, pages = {391 -- 399}, year = {2020}, abstract = {During deployment, soldiers face situations in which they are not only exposed to violence but also have to perpetrate it themselves. This study investigates the role of soldiers' levels of posttraumatic stress disorder (PTSD) symptoms and appetitive aggression, that is, a lust for violence, for their engaging in violence during deployment. Furthermore, factors during deployment influencing the level of PTSD symptoms and appetitive aggression after deployment were examined for a better comprehension of the maintenance of violence. Semi-structured interviews were conducted with 468 Burundian soldiers before and after a 1-year deployment to Somalia. To predict violent acts during deployment (perideployment) as well as appetitive aggression and PTSD symptom severity after deployment (postdeployment), structural equation modeling was utilized. Results showed that the number of violent acts perideployment was predicted by the level of appetitive aggression and by the severity of PTSD hyperarousal symptoms predeployment. In addition to its association with the predeployment level, appetitive aggression postdeployment was predicted by violent acts and trauma exposure perideployment as well as positively associated with unit support. PTSD symptom severity postdeployment was predicted by the severity of PTSD avoidance symptoms predeployment and trauma exposure perideployment, and negatively associated with unit support. This prospective study reveals the importance of appetitive aggression and PTSD hyperarousal symptoms for the engagement in violent acts during deployment, while simultaneously demonstrating how these phenomena may develop in mutually reinforcing cycles in a war setting.}, language = {en} } @article{HolfelderMulanskySchleeetal.2021, author = {Holfelder, Marc and Mulansky, Lena and Schlee, Winfried and Baumeister, Harald and Schobel, Johannes and Greger, Helmut and Hoff, Andreas and Pryss, R{\"u}diger}, title = {Medical device regulation efforts for mHealth apps during the COVID-19 pandemic — an experience report of Corona Check and Corona Health}, series = {J — Multidisciplinary Scientific Journal}, volume = {4}, journal = {J — Multidisciplinary Scientific Journal}, number = {2}, issn = {2571-8800}, doi = {10.3390/j4020017}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285434}, pages = {206 -- 222}, year = {2021}, abstract = {Within the healthcare environment, mobile health (mHealth) applications (apps) are becoming more and more important. The number of new mHealth apps has risen steadily in the last years. Especially the COVID-19 pandemic has led to an enormous amount of app releases. In most countries, mHealth applications have to be compliant with several regulatory aspects to be declared a "medical app". However, the latest applicable medical device regulation (MDR) does not provide more details on the requirements for mHealth applications. When developing a medical app, it is essential that all contributors in an interdisciplinary team — especially software engineers — are aware of the specific regulatory requirements beforehand. The development process, however, should not be stalled due to integration of the MDR. Therefore, a developing framework that includes these aspects is required to facilitate a reliable and quick development process. The paper at hand introduces the creation of such a framework on the basis of the Corona Health and Corona Check apps. The relevant regulatory guidelines are listed and summarized as a guidance for medical app developments during the pandemic and beyond. In particular, the important stages and challenges faced that emerged during the entire development process are highlighted.}, language = {en} }