COVID-19 supplement to a computational examination of threat and reward constructs in a predominantly low-income, longitudinal sample at increased risk for internalizing disorders

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 3R01MH121079-02S1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2019
    2024
  • Known Financial Commitments (USD)

    $155,961
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    Christopher Stephen Monk
  • Research Location

    United States of America
  • Lead Research Institution

    University Of Michigan At Ann Arbor
  • Research Priority Alignment

    N/A
  • Research Category

    Secondary impacts of disease, response & control measures

  • Research Subcategory

    Indirect health impacts

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Adults (18 and older)

  • Vulnerable Population

    Minority communities unspecified

  • Occupations of Interest

    Unspecified

Abstract

Abstract: The novel Coronavirus (COVID-19) pandemic has had a far-reaching impact on the US population, and hasdisproportionately affected race-ethnic minorities, individuals living in or near poverty, and those living in largeurban areas. Based on past literature we expect COVID-19 related stressors to have large negative effects onmental 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 targetyoung adults and their parents (n=1,200) in a representative sample of a disadvantaged population. To betterunderstand 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 (withdifferent pandemic policies) and in those most at-risk for poor outcomes: low-income and minority families andyoung adults who are showing disparities in infection and mortality. Thus, by adding this critical, time-sensitiveassessment, we will be even better positioned to understand how adversity shapes the ongoing developmentof RDoC threat and reward circuits, as well as a broader assessment of how COVID-19 is impacting mentalhealth in marginalized, low-income, minority populations. Moreover, we will document the way in whichresilience factors including social support, economic policies, and family resources moderate the negativeeffect 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 Rewardconstructs in an existing representative longitudinal cohort at risk for psychopathology and to delineate how ahistory 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 4900children born 1998-200 in large US cities. Attributes of the FFCWS are: 1) parents and children were surveyedand assessed at birth, 1, 3, 5, 9, 15 years; 2) the sample is nationally representative; 3) Substantial enrichmentfor 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 forpsychopathology. Because of the unique social distancing required by COVID-19, having data from multiplefamily members will be particularly powerful in understanding the economic and social, and in turn, mentalhealth 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-relatedadversity, prior public assistance, COVID-19 related public assistance and policies) and used to forecast theonset/intensification of internalizing symptoms at multiple units of analysis from brain to behavior to symptoms.