The novel Coronavirus (COVID-19) pandemic has had a far-reaching impact on the US population, and has disproportionately affected race-ethnic minorities, individuals living in or near poverty, and those living in large urban areas. Based on past literature we expect COVID-19 related stressors to have large negative effects on mental health, but we do not yet understand how social and economic factors might moderate those effects. The current supplement would add time-sensitive data by collecting real-time online surveys of both target young adults and their parents (n=1,200) in a representative sample of a disadvantaged population. To better understand how major stressors, like the COVID-19 pandemic, are moderated, we must assess these social, occupational, economic, health, and mental health impacts as they happen, across different cities/states (with different pandemic policies) and in those most at-risk for poor outcomes: low-income and minority families and young adults who are showing disparities in infection and mortality. Thus, by adding this critical, time-sensitive assessment, we will be even better positioned to understand how adversity shapes the ongoing development of RDoC threat and reward circuits, as well as a broader assessment of how COVID-19 is impacting mental health in marginalized, low-income, minority populations. Moreover, we will document the way in which resilience factors including social support, economic policies, and family resources moderate the negative effect of COVID-19 related stressors on mental health. This builds on the parent grant's focus to use data- driven analytics and hypothesis testing to validate multilevel-multimodal models of Threat and Reward constructs in an existing representative longitudinal cohort at risk for psychopathology and to delineate how a history of exposure to adversity links to these domains. The parent grant is assessing 600 young adults twice (at age 20 and 24) from The Fragile Families and Child Wellbeing Study (FFCWS), an ongoing study of 4900 children born 1998-200 in large US cities. Attributes of the FFCWS are: 1) parents and children were surveyed and assessed at birth, 1, 3, 5, 9, 15 years; 2) the sample is nationally representative; 3) Substantial enrichment for low-income (median income to needs ratio=1.4) and minority families (66%), populations are often under- represented in research; and 4) participants are entering early adulthood, a period of heightened risk for psychopathology. Because of the unique social distancing required by COVID-19, having data from multiple family members will be particularly powerful in understanding the economic and social, and in turn, mental health consequences of COVID-19. To predict internalizing symptoms, we will identify biotypes cross- sectionally and longitudinally. Socio-ecological conditions will be deeply assessed (including COVID-19-related adversity, prior public assistance, COVID-19 related public assistance and policies) and used to forecast the onset/intensification of internalizing symptoms at multiple units of analysis from brain to behavior to symptoms.

Public Health Relevance

The novel Coronavirus (COVID-19) pandemic has had a far-reaching impact on the US population, and has disproportionately affected race-ethnic minorities, individuals living in or near poverty, and those living in large urban areas. To better understand the mental health consequences of COVID-19 related stressors and moderators of those stressors on threat and reward construct, we utilize on an existing 22 year longitudinal study of children born in large US cities and parents by adding time-sensitive COVID-19 exposure, economic, and mental health measures to a real-time online interview of subsample the young adults and their parents.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
3R01MH121079-02S1
Application #
10152843
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Murphy, Eric Rousseau
Project Start
2019-08-15
Project End
2024-06-30
Budget Start
2020-08-01
Budget End
2021-06-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Organized Research Units
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109