Monday10May 2021

A Large-scale Multifaceted Longitudinal Study of Socioemotional and Behavioral change Across the Pandemic

A Psychology brown-bag lecture by Dr. Uri Maoz

Monday, May 10, 2021 12:00 p.m. PST
2021-05-10 12:00 2021-05-10 13:00 America/Los_Angeles A Large-scale Multifaceted Longitudinal Study of Socioemotional and Behavioral change Across the Pandemic Zoom Rebecca Linden

Free to attend


General Public

Everyone is welcome to attend

The COVID-19 pandemic has caused massive societal upheaval around the world. In the US, with 20% of global COVID-19 cases, the pandemic has also triggered a substantial economic shock and laid bare societal inequities. The extreme and highly volatile nature of this time period affords a unique opportunity to elucidate the dynamics of psychosocial processes. In April of 2020, we launched the pre-registered COVID-Dynamic longitudinal study to capture 1000+ U.S. residents’ personal and collective experiences related to the pandemic and to characterize psychological, emotional, attitudinal, and behavioral change. Participants completed a longitudinal, hour-long battery of psychological measures, including assessments of racial, political, social, moral, and COVID-19-related attitudes and behaviors, and experimental tasks. We describe the ongoing study and provide an assessment of data quality for the first 8 Waves (April to June) across the same 1000+ participants. In particular, we focus on parts of the survey relating to moral choice and volition.
Uri Maoz joined Chapman University in 2017 as an Assistant Professor of Computational Neuroscience at Crean College and at the Institute for Interdisciplinary Brain and Behavioral Sciences. His research lies at the intersection of volition, decision-making, and moral choice. He uses a combination of empirical techniques (e.g., EEG, intracranial recordings, behavioral studies) and theoretical modeling to develop a computational account of volition, with an emphasis on the decision-making processes that lead to voluntary action and on the role of consciousness in such processes. In particular, he uses machine-learning to carry out online, real-time, closed-loop analysis of neural data, as it is recorded. He is further interested in the legal, ethical, conceptual, and economic implications of this work.

You can contact the event organizer, Rebecca Linden at

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