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Mental health effects of COVID-19 lockdowns: a Twitter-based analysis

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Abstract

We use a distinctive methodology that leverages a fixed population of Twitter users located in France to gauge the mental health effects of repeated lockdown orders. To do so, we derive from our population a mental health indicator that measures the frequency of words expressing anger, anxiety and sadness. Our indicator did not reveal a statistically significant mental health response during the first lockdown, while the second lockdown triggered a sharp and persistent deterioration in all three emotions. Our estimates also show a more severe deterioration in mental health among women and younger users during the second lockdown. These results suggest that successive stay-at-home orders significantly worsen mental health across a large segment of the population. We also show that individuals who are closer to their social network were partially protected by this network during the first lockdown, but were no longer protected during the second, demonstrating the gravity of successive lockdowns for mental health.

Suggested Citation

  • Sara Colella & Frédéric Dufourt & Vincent A. Hildebrand & Rémi Vivès, 2022. "Mental health effects of COVID-19 lockdowns: a Twitter-based analysis," AMSE Working Papers 2218, Aix-Marseille School of Economics, France, revised Sep 2023.
    • Handle: RePEc:aim:wpaimx:2218
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    File URL: https://www.amse-aixmarseille.fr/sites/default/files/working_papers/wp_2022_-_nr_18.pdf,File-URL:https://www.amse-aixmarseille.fr/sites/default/files/working_papers/wp_2022_-_nr_18_v2.pdf
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    1. Abi Adams-Prassl & Teodora Boneva & Marta Golin & Christopher Rauh, 2022. "The impact of the coronavirus lockdown on mental health: evidence from the United States," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 37(109), pages 139-155.
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    Cited by:

    1. Apostolos Davillas & Andrew M Jones, 2021. "The first wave of the COVID‐19 pandemic and its impact on socioeconomic inequality in psychological distress in the UK," Health Economics, John Wiley & Sons, Ltd., vol. 30(7), pages 1668-1683, July.

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    More about this item

    Keywords

    COVID-19; lockdown; mental health; Twitter data; well-being;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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