Effects of social support on depression risk during the COVID-19 pandemic: What support types and for whom?

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Abstract

Background

Rates of depression have increased worldwide during the COVID-19 pandemic. One known protective factor for depression is social support, but more work is needed to quantify the extent to which social support could reduce depression risk during a global crisis, and specifically to identify which types of support are most helpful, and who might benefit most.

Methods

Data were obtained from participants in the All of Us Research Program who responded to the CO VID-19 P articipant E xperience (COPE) survey administered monthly from May 2020 to July 2020 (N=69,066, 66% female). Social support was assessed using 10 items measuring emotional/informational support (e.g., someone to confide in or talk to about yourself or your problems), positive social interaction support (e.g., someone to do things with to help you get your mind off things), and tangible support (e.g., someone to help with daily chores if sick). Elevated depression symptoms were defined based on having a moderate-to-severe (≥10) score on the Patient Health Questionnaire (PHQ-9). Mixed-effects logistic regression models were used to test associations across time between overall social support and its subtypes with depression, adjusting for age, sex, race, ethnicity, and socioeconomic factors. We then assessed interactions between social support and potential effect modifiers: age, sex, pre-pandemic mood disorder, and pandemic-related stressors (e.g., financial insecurity).

Results

Approximately 16% of the sample experienced elevated depressive symptoms. Overall social support was associated with significantly reduced odds of depression (adjusted odds ratio, aOR [95% CI]=0.44 [0.42-0.45]). Among subtypes, emotional/informational support (aOR=0.42 [0.41-0.43]) and positive social interactions (aOR=0.43 [0.41-0.44]) showed the largest protective associations with depression, followed by tangible support (aOR=0.63 [0.61-0.65]). Sex, age, and pandemic-related financial stressors were statistically significant modifiers of the association between social support and depression.

Conclusions

Individuals reporting higher levels of social support were at reduced risk of depression during the early COVID-19 pandemic. The perceived availability of emotional support and positive social interactions, more so than tangible support, was key. Individuals more vulnerable to depression (e.g., women, younger individuals, and those experiencing financial stressors) may particularly benefit from enhanced social support, supporting a precision prevention approach.

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  1. SciScore for 10.1101/2022.05.15.22274976: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The Institutional Review Board of the All of Us Research Program has approved all study procedures, and 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 Board of the All of Us Research Program has approved all study procedures, and 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 missingness and within-subject correlations across survey measurements (14), we first fitted IPW-adjusted, mixed-effects logistic regression models using the lme4 R package to determine the time-varying relationships between social support and depression with subject-specific random intercepts and fixed effects for the three survey timepoints (i.e., May, June, and July of 2020).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cohort description: The All of Us Research Program (AoU) (8) has enrolled more than 482,000 participants as of April 2022.
    Us Research Program
    suggested: None
    In recent prior work, we found some evidence of “healthy volunteer bias” among the COPE survey participants and demonstrated the utility of inverse probability weighting in offsetting potential bias (10).
    COPE
    suggested: (COPE, RRID:SCR_009153)
    Covariates: We used linked EHR data to establish whether participants had a pre-pandemic history of mood disorder diagnosis at any time prior to January 21st, 2020, the date of the first reported COVID-19 case in the United States (13), defined by two or more qualifying diagnostic codes mapped to “Mood disorder” code 46206005 in the Systematized Nomenclature of Medicine (SNOMED; a common coding scheme for harmonizing different coding vocabularies or ICD versions across health systems).
    Covariates
    suggested: None

    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:
    Several limitations should be noted. First, as with many survey instruments, our measure of social support captures self-reported perceptions of support, which may be influenced by concurrent depressed mood, thereby inflating the association. Notwithstanding, our primary analyses were consistent with lagged models in which baseline social support was associated with subsequent depression even after removing individuals with baseline elevated depression symptoms, suggesting the effect was not purely driven by contemporaneous mood states; however, further causal inference analyses are warranted (26). Second, we selected available variables from the COPE survey to examine their potential role as effect modifiers, but there may be other unmeasured intrinsic or pandemic-related factors (e.g., lockdown exposure) that may also influence the association between social support and depression. Our pre-pandemic mood disorder variable was also conservatively defined using linked EHR data which was available for most, but not all, participants. Third, given that most individuals were research volunteers with Internet access who were relatively well-educated and endorsed minimal financial stressors related to the pandemic, our sample may not generalize to more disadvantaged populations, though we used inverse-probability weighting as an attempt to match COPE survey participants more closely with the broader and more diverse All of Us Research Program study cohort.

    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.