As life expectancy increases, there is a growing demand for technologies that can support the care and independence needs of older adults. Such assistive technologies as socially assistive robots (SARs) require a vast collection and use of data. However, existing interfaces frequently employ structured privacy frameworks that do not account for personalized preferences, and there is currently a research gap on how to better correspond to user’s intuitive expectations in relation to data and privacy management of care robots. This project proposes a participatory design approach that allows older users to adjust privacy settings. With the goal of exploring how better navigation and personalized settings can increase trust, improve usability, and support adoption. Following preliminary co-design workshops, three interface types were designed and tested with ten older adults who receive care: a basic interface, a guided wizard model, and a model with breadcrumb style navigation. The usability testing assessed task completion, clarity, and user satisfaction. The results demonstrate that participatory design significantly improves both usability and privacy perception, particularly in the Breadcrumb and Wizard interfaces, and guiding the discussion on user-centered SAR development.