Causal Connections: DAG Hackathon for Mapping Time-Use to Wellbeing
Thomas McGrath, Tamas Foldes, Karen Mansfield, Andy Przybylski
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.
Hackathon
Second floor 210