Tamas Foldes
Sessions
Building custom web applications for psychological and behavioural research can seem daunting, but accessible Large Language Models (LLMs) and affordable front- and back-end solutions are making it easier than ever. This workshop provides a hands-on exploration of these advancements through two case studies: Port, a data donation platform for collecting app usage data, and O-ELiDDI, a web-based diary for time-use data. Participants will learn how to fork, modify, and deploy these open-source web applications with minimal coding, leveraging GitHub for version control, LLMs for feature development, and low-cost data storage services.
Whether you are interested in building open-source instruments, gathering user-data for psychological research, or conducting time-use studies, this workshop offers practical strategies for creating or tweaking your own customized solutions suited to your specific research needs.
Causal inference is vital in psychological science, but clearly defining causal questions and relationships remains challenging and rarely achieved—weakening the robustness and clarity of analyses in observational studies. A directed acyclic graph (DAG) is a tool to help researchers illustrate their understanding of causal relationships between variables. Addressing concerns about how the time spent using digital technologies affects young people’s wellbeing, we aim to use DAGs to identify bias and inform appropriate adjustment strategies for analysis of observational time-use data.
We will employ an adapted collaborative DAG development procedure and gather feedback for its refinement. Our goal is to create a DAG that transparently captures experts’ knowledge of sources of bias for the relationship between digital technology time-use and wellbeing. The hackathon offers a chance to develop a DAG relevant to a broader range of young people by encouraging cross-disciplinary discussion with researchers at SIPS.