Using a principled causal approach for causal queries: the Ostracism Causal Project

Ostracism—being ignored or excluded— manifests in many forms in everyday life, such as ghosting, bullying, microaggressions, and cancel culture. For decades, psychologists have examined its real-world impacts, including depression, suicide risk, violence, extremism, societal divides, and inequalities. However, much of this evidence is not causal due to the absence of tools for quantifying the causal effects of naturally occurring exposures in psychological science. Relying on the existing approach will continue to distort scientific conclusions, impede theory advancement, and misguide policies. Re-thinking the current causal approach is critical and overdue.The O-Causal project aims to address this gap by applying the causal inference framework—a principled and well-established approach for causality—to ostracism research. This project will advance the field in four key ways: 1) establishing a fundamental understanding of the prevalence and distribution of lived ostracism experiences in real-life settings; 2) quantifying the time-varying ostracism effects across a wide range of outcomes in behavioral, economic, health, and wellbeing domains; 3) uncovering inequalities in ostracism and identifying at-risk populations; and 4) reformulating causal questions to generate insights that inform public policies aimed at fostering positive social change.To achieve these goals, I will construct a comprehensive, population-based dataset by integrating large longitudinal panel data, daily diary entries, and ecological momentary assessments. Using advanced causal inference techniques and innovative causal estimands, this project will reveal how everyday experiences of ostracism can escalate into serious societal issues, identify vulnerable groups, and provide a foundation for policy development. Ultimately, this project will reorient ostracism research and psychological science toward a more rigorous causal approach toward scientific rigor and real-world impact.