Social relationships and depression during the COVID-19 lockdown: longitudinal analysis of the COVID-19 Social Study

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Abstract

Background

The coronavirus disease 2019 (COVID-19) pandemic led to measures that reduced social contact and support. We explored whether UK residents with more frequent or supportive social contact had fewer depressive symptoms during March−August 2020, and potential factors moderating the relationship.

Methods

A convenience sample of UK dwelling participants aged ⩾18 in the internet-based longitudinal COVID-19 Social Study completed up to 22 weekly questionnaires about face-to-face and phone/video social contact frequency, perceived social support, and depressive symptoms using the PHQ-9. Mixed linear models examined associations between social contact and support, and depressive symptoms. We examined for interaction by empathic concern, perspective taking and pre-COVID social contact frequency.

Results

In 71 117 people with mean age 49 years (standard deviation 15), those with high perceived social support scored 1.836 (1.801–1.871) points lower on PHQ-9 than those with low support. Daily face-to-face or phone/video contact was associated with lower depressive symptoms (0.258 (95% confidence interval 0.225–0.290) and 0.117 (0.080–0.154), respectively) compared to no contact. The negative association between social relationships and depressive symptoms was stronger for those with high empathic concern, perspective taking and usual sociability.

Conclusions

We found during lockdown that those with higher quality or more face-to-face or phone/video contact had fewer depressive symptoms. Contact quality was more strongly associated than quantity. People who were usually more sociable or had higher empathy had more depressive symptoms during enforced reduced contact. The results have implications for COVID-19 and potential future pandemic management, and for understanding the relationship between social factors and mental health.

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  1. SciScore for 10.1101/2020.12.01.20241950: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study design and participants: UCL Research Ethics Committee [12467/005] approved the study and all participants gave informed consent.
    Consent: Study design and participants: UCL Research Ethics Committee [12467/005] approved the study and all participants gave informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablePotential moderators: Confounders: We used other variables from the baseline interview which we considered from previous evidence to be potential confounders: age; gender (male, female, other/prefer not to say); ethnicity (White, other); highest educational attainment (lower secondary (GCSE/O-level or lower), higher secondary (A-level or equivalent), graduate or higher); living alone or living with others; marital status (cohabiting with partner or spouse, partner or spouse but living apart, divorced or widowed, single and never married); in employment/study or retired/not working; annual household income less or more than £30,000.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Participants were invited by email to complete online questionnaires using the Redcap online survey tool (https://www.project-redcap.org/).
    https://www.project-redcap.org/
    suggested: (REDCap, RRID:SCR_003445)

    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:
    Limitations: While our large sample size covered an extensive range of sociodemographic characteristics, it was not nationally representative with some groups being underrepresented, for example those from lower sociodemographic groups and minority ethnic groups. However, the potential bias in selection is less relevant for examining risk factor-outcome associations [37]. All variables were by self-report, so negative perspectives common in depression may have influenced report of structural and functional relationships, which would likely overestimate the association. The questionnaire design, whereby respondents had to answer all questions to proceed to the next page, meant that there was little missing data for the different questionnaire domains, but participation varied longitudinally, with around 10% answering only one questionnaire, and only 10% answering all the weekly questionnaires. Our analysis did not account for attrition which may have been higher in those with depressive symptoms, and we could only examine moderation by empathy in the smaller sample of participants who answered that weekly questionnaire. Participants also joined at different stages, with around 40% joining within the first week of the survey in late March 2020, and others joining at any subsequent point. Our analytic approach allowed us to make use of all repeated exposure and outcome variables, and this was particularly relevant for the circumstances of lockdown whereby social contact with oth...

    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.

    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.