Dr. Katarina Braune and Hanne Ballhausen, The OPEN Project
While automated insulin delivery systems have been shown to be safe and effective in reducing hyper- and hypoglycemia in people with diabetes of various age groups, they are not universally available, accessible, and affordable. Therefore, open-source initiatives of people with diabetes who create their own “Open-Source” or “Do-it-Yourself Artificial Pancreas Systems” (DIYAPS) have become increasingly popular. For the OPEN project, Charité - Universitätsmedizin Berlin has teamed up with academic and non-academic international partners from various disciplines (healthcare, tech, social science, behavioral research, data science, advocacy, diabetes online community) in an interdisciplinary consortium to establish an empirical evidence base for various aspects of the use of DIYAPS, including clinical and quality-of-life outcomes, and to identify challenges and possible solutions to enable wider diffusion of automated insulin delivery.
Dr. Felix Fischer, PROM2PRO
The assessment of health from the patients' perspective is a cornerstone of medical research. Despite questionnaires have often quite similar content, the data collected is hardly comparable. Calibrating these questionnaires on a common scale establishes standard scales for patient-reported outcomes. The aim of this project is to make already collected data available for validation and development of such common metrics. This will be done by providing a web application to collect study metadata and raw data, and make those more readily available for research.
Dr. Toivo Glatz and Jessica Rohmann, PEERSPECTIVES
Peer review is a key component of the current academic publishing landscape, and yet, the vast majority of early career scientists never receive formal training on how to conduct such reviews. PEERSPECTIVES, a semester-long course for PhD students in the health data sciences, aims to change this using a hybrid structure of interactive workshops and hands-on, mentored group reviews of “live” manuscripts. Students who complete the semester-long curriculum developed by experienced editors will not only learn skills needed to critically appraise scientific papers and generate high quality peer reviews, but will also gain critical insights into the scientific publishing system as a whole. This training is of extreme relevance and importance to our target group of up-and-coming scientists, the large majority of whom will complete publication-based PhD dissertations. To evaluate whether the completion of this program within the ongoing doctoral studies framework has an effect on the quality of peer-review among motivated doctoral students, we will run a confirmatory study with pre-/post- assessment.
Dr. Wolf-Julian Neumann, From experiment to open metadata repository: Computational reproducibility for FAIR translational neuromodulation research in clinical neuroscience.
As a recently appointed assistant professor, I work in biomarker characterization and algorithm development for invasive closed - loop neurostimulation in human patients. My research has immediate translational potential for therapeutic improvement. Lack of transparency and reproducibility impedes innovation and obliterates clinical adoption of unambiguously promising advances. The SWTFTPF will help me to trailblaze data strategy development for multimodal human neuromodulation research. The aim of the project is to pioneer automatized data flow algorithms from data collection to computationally reproducible publication.
Dr. Sophie Piper, The iBikE Smart Learner
Statistics is often not a popular subject for medical students and researchers. However, methodological skills are essential for the quality of research and for the correct interpretation of research results. We developed a learning tool called the "iBikE Smart learner“ - an interactive, web-based teaching program. Specifically, we were able to complete the content of the first module "Statistical misconceptions about the p-value" – which we plan to evaluate in the upcoming months. Moreover, we want to create more modules addressing for instance the misinterpretation of correlation and causation and the misuse of bar charts.
Institute of Biometry and Clinical Epidemiology (iBikE)