Lectures
Meet the Experts: Using Smartphones to Explore Intra-Individual Processes and Situational Dynamics
Using Smartphones to Explore Intra-Individual Processes and Situational Dynamics
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.
Researchers: Dr. Lukas Otto, Dr. Mareike Wieland
Year: 2024
Guides
GESIS Guide to Digital Behavioral Data: How to Set up and Monitor App-based Data Collections
How to Set up and Monitor App-based Data Collections
Smartphones have become a cornerstone for social science research. However, app-based data collection comes with challenges that can undermine data quality, including participant dropout, technical failures, and biases. While existing guidelines focus on designing and analyzing data from mobile research, less attention is given to strategies for managing risks during the critical phase of active data collection.
This guide addresses that gap by offering practical recommendations to manage the active data collection phase. With a focus on app selection, study setup, and participation and data income monitoring, we provide researchers with actionable strategies to improve response rates, minimize attrition, and navigate the complexities of mobile research under real-world conditions.
Our guide comes with a checklist to facilitate the monitoring of studies.
Researchers: Dr. Vanessa Lux, Dr. Mareike Wieland
Year: 2025
View documentESM Tool Collection
Tools for Mobile Ecological Momentary Assessments
More and more social science researchers are discovering the potential of smartphones as a device for data collection ranging from mobile surveying to mobile sensing. Accordingly, a diverse landscape of tools (software services, technical frameworks) targeting these needs has emerged, but is at the same time characterized by heterogeneous terms and diverse actors, making it difficult to navigate.
With this tool review, we aim to generate a comprehensive yet focused list of tools that enable the collection of intensive-longitudinal data using mobile technologies to study social science phenomena. If you are interested in contributing to the tool review, You can contribute by suggesting a tool you know to be added to the list via this survey. If you notice any incomplete and/or wrong information about a tool, please contact us via: appkit(at)gesis(dot)org. Thank you very much for your contribution!
Researchers: Dr. Mareike Wieland, Annika Herbertz, Julian Kohne, Dr. Lukas Otto
Year: 2025
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