Maharlou, HamidrezaBössel-Debbert, NicoleLucht, MichaelMaier, Hannah B.Mücke, StefanieMüntefering, FabianNeuhaus, BarbaraProkein, JanaReif-Leonhard, ChristineVoges, JanWeber, HeikeWeihs, AntoineFrieling, HelgeOeltze-Jafra, SteffenKucher, KostiantynDiehl, AlexandraGillmann, Christina2024-05-212024-05-212024978-3-03868-258-5https://doi.org/10.2312/evp.20241081https://diglib.eg.org/handle/10.2312/evp20241081The P4D (Personalised, Predictive, Precise, and Preventive Medicine for Major Depression) study aims at an improved prediction of treatment outcomes based on a more precise stratification of major depression subtypes. It is collecting very complex data from 1,000 patients across five German university hospitals. We have designed a dashboard to monitor the study and share the collected data among the study partners. We employed a state-of-the-art cooperative dashboard design approach by Setlur et al. [SCST24] in two design cycles: user feedback and dashboard revision. We observed a significant improvement in user satisfaction from the first (Mean=3.57 std=0.95) to the second (Mean=3.87 std=0.80) cycle and an overall positive assessment.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Information visualization; Visualization design and evaluation methodsHuman centered computing → Information visualizationVisualization design and evaluation methods10.2312/evp.202410813 pages