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In social science research, the traditional “trait-paradigm” has focused on stable variables, between-person differences, and long-term dynamics. However, new research designs that are possible and scalable through mobile data collections consider that measurement does not take place in a “situative vacuum” and that measurement scores are influenced by not only stable, person-specific variables but also within-person, short-term processes as well as combinations of between- and within-person variability that should not be overlooked Making use of mobile data collection thus implies following an intensive-longitudinal approach. It involves collecting detailed, frequent individual-level data, often daily or multiple times per day; intensive-longitudinal designs usually involve collecting rich, multi-faceted data, including self-reports, behavioral observations, or environmental assessments using built-in sensors. The primary goal of these methods is to understand intra-individual variability, situational aspects, state-like variables, and fast-lived dynamics. Within this talk, we will outline the promises and pitfalls of different data obtained through mobile intensive-longitudinal methods. We will first introduce the idea of within- and between-person effects and show how mobile methods and intensive-longitudinal designs facilitate new designs and tackle new research questions in social science research. We will also show how these designs can be conducted using GESIS services such as the GESIS AppKit. Presenters: Dr. Lukas Otto Dr. Mareike Wieland