Gender and trust in government modify the association between mental health and stringency of social distancing related public health measures to reduce COVID-19: a global online survey

  1. Lily O’Hara
  2. Hanan F Abdul Rahim
  3. Zumin Shi

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Abstract

Objectives

To investigate the associations between stringency of COVID-19 social distancing policies and mental health outcomes, and the moderating effect of trust in government and gender.

Design and setting

Cross sectional study involving secondary analysis of publicly available data from a global online COVID-19 survey and the Oxford COVID-19 Government Response Tracker.

Participants

106,497 participants from 58 countries.

Main outcome measures

Outcomes were a worries index and a depression index. Predictors were stringency of policies, trust in government, and gender. Multivariable regression was conducted to determine the three-way interaction between the predictor variables for mental health outcomes, adjusting for age, income and education.

Results

The median age of participants (56.4% women) was 37 years (interquartile range 29 to 48 years). Women had higher worries and depression scores than men. 45.4% distrusted the government and 43.8% trusted the government to take care of its citizens. Among those who strongly trusted the government, an increase in the stringency of policies was associated with a significant increase in the worries index. Among men who distrusted the government, an increase in policy stringency was associated with an increase in the depression index but not the worries index. In women that strongly distrusted the government, there was an inversed U-shaped association between policy stringency and both the worries and depression indices.

Conclusion

As the stringency of public health measures increases, so too do depression and worries. The association is moderated by gender and trust in government. For safe and effective public health measures, governments should develop strategies to increase trust in their actions.

Article activity feed

  1. Version published to 10.1101/2020.07.16.20155200v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.07.16.20155200: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableA total of 960 participants who reported gender other than male or female were excluded from the analysis.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All the analyses were performed by using STATA 16.1 (Stata Corporation, College Station, TX, USA).
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: This study had a number of strengths and limitations. The large number of participants from 58 countries enabled a robust analysis of the relationships between mental health outcomes, trust in government and the stringency of public health measures for women and men. However, the data were from a convenience sample who completed a cross-sectional online survey, and were therefore not representative of the whole population. Conclusions: Results from our study suggest that there is a relationship between stringency of public health measures and mental health outcomes. The nature of the association depends on the trust in government and gender as well as the level of the stringency. If the easing of restrictions results in a second wave of infections, governments may need to consider reinstating very stringent public health measures in order to mitigate the mental health impacts on their communities. Building trust in the government to care for its citizens should be considered in order to reduce the risk of mental health problems during the pandemic.

    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

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  3. Version published to 10.1101/2020.07.16.20155200v1 on medRxiv