Association of Everyday Discrimination With Depressive Symptoms and Suicidal Ideation During the COVID-19 Pandemic in the All of Us Research Program

  1. Younga H. Lee
  2. Zhaowen Liu
  3. Daniel Fatori
  4. Joshua R. Bauermeister
  5. Rebecca A. Luh
  6. Cheryl R. Clark
  7. Sarah Bauermeister
  8. André R. Brunoni
  9. Jordan W. Smoller

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Abstract

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  1. Version published to 10.1001/jamapsychiatry.2022.1973
  2. ScreenIT

    SciScore for 10.1101/2021.12.06.21266524: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The Institutional Review Boards of the All of Us Research Program approved all study procedures, and all participants provided informed consent to share electronic health records (EHRs), surveys, and other study data with qualified investigators for broad-based research.
    Consent: The Institutional Review Boards of the All of Us Research Program approved all study procedures, and all participants provided informed consent to share electronic health records (EHRs), surveys, and other study data with qualified investigators for broad-based research.
    Sex as a biological variablenot detected.
    RandomizationTo accommodate both missing responses and the correlated nature of repeated measurements (32), we fitted mixed-effects logistic regression models using the lme4 R package to determine the relationships between the repeated survey measures with subject-specific random intercepts and fixed effects for the timing of survey administration (e.g., May, June, and July of 2020).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cohort description: To date, the All of Us Research Program (hereafter, AoU) has enrolled more than 400,000 participants, of which more than 80% are individuals from communities that have been underrepresented in biomedical research, such as racial and ethnic minorities, sexual and gender minorities, and people with low income or limited education (25).
    Us Research Program
    suggested: None
    We further adjusted the mixed-effects models for the experience of COVID-19 symptoms for each survey timing (measured as part of the COPE survey), given the possibility that COVID-19 infection could be a common cause of perceived discrimination (33) and depression (34).
    COPE
    suggested: (COPE, RRID:SCR_009153)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study should also be evaluated in light of several limitations. First, the first COPE survey was administered in May of 2020, after the start of the pandemic. Since we did not have pre-pandemic measurements of discrimination or PHQ-9 scores, we could not capture the evolution of their relationship at the beginning of the pandemic. Second, we also could not establish a causal relationship between perceived discrimination and depression because these were measured concurrently during waves of the survey. Third, while our use of inverse probability weighting should address discrepancies between COPE respondents and the overall AoU cohort, the latter is not a fully representative sample of the U.S. population; thus, the generalizability of these findings warrants caution.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.12.06.21266524 on medRxiv