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Mental Health among Adults during the COVID-19 Pandemic Lockdown: A Cross-Sectional Multi-Country Comparison.

Kele DingJingzhen Ginger YangMing-Kai ChinLindsay SullivanGiyasettin DemirhanVeronica Violant-HolzRicardo Ricci UvinhaJianhui DaiXia XuBiljana PopeskaZornitza MladenovaWaheeda KhanGarry KuanGovindasamy BalasekaranGary A Smithnull On Behalf Of Global Community Health-Covid-Collaborative Research Team
Published in: International journal of environmental research and public health (2021)
Despite the global impact of COVID-19, studies comparing the effects of COVID-19 on population mental health across countries are sparse. This study aimed to compare anxiety and depression symptoms during the COVID-19 lockdown among adults from 11 countries and to examine their associations with country-level COVID-19 factors and personal COVID-19 exposure. A cross-sectional survey was conducted among adults (≥18 years) in 11 countries (Brazil, Bulgaria, China, India, Ireland, North Macedonia, Malaysia, Singapore, Spain, Turkey, United States). Mental health (anxiety, depression, resilient coping, hope) and other study data were collected between June-August 2020. Of the 13,263 participants, 62.8% were female and 51.7% were 18-34 years old. Participants living in Brazil had the highest anxiety and depression symptoms while participants living in Singapore had the lowest. Greater personal COVID-19 exposure was associated with increased anxiety and depression symptoms, but country-level COVID-19 factors were not. Higher levels of hope were associated with reduced anxiety and depression; higher levels of resilient coping were associated with reduced anxiety but not depression. Substantial variations exist in anxiety and depression symptoms across countries during the COVID-19 lockdown, with personal COVID-19 exposure being a significant risk factor. Strategies that mitigate COVID-19 exposure and enhance hope and resilience may reduce anxiety and depression during global emergencies.
Keyphrases
  • coronavirus disease
  • sars cov
  • mental health
  • depressive symptoms
  • respiratory syndrome coronavirus
  • machine learning
  • climate change
  • social support
  • big data