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Lifestyle and mental health disruptions during COVID-19.

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TLDR
It is suggested that disruption to physical activity is a leading risk factor for depression during the pandemic and restoration of those habits-either naturally or through policy intervention-has limited impact on restoring mental well-being.
Abstract
Using a longitudinal dataset linking biometric and survey data from several cohorts of young adults before and during the COVID-19 pandemic ([Formula: see text]), we document large disruptions to physical activity, sleep, time use, and mental health. At the onset of the pandemic, average steps decline from 10,000 to 4,600 steps per day, sleep increases by 25 to 30 min per night, time spent socializing declines by over half to less than 30 min, and screen time more than doubles to over 5 h per day. Over the course of the pandemic from March to July 2020 the proportion of participants at risk for clinical depression ranges from 46% to 61%, up to a 90% increase in depression rates compared to the same population just prior to the pandemic. Our analyses suggest that disruption to physical activity is a leading risk factor for depression during the pandemic. However, restoration of those habits through a short-term intervention does not meaningfully improve mental well-being.

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Citations
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Working-from-home persistently influences sleep and physical activity 2 years after the Covid-19 pandemic onset: a longitudinal sleep tracker and electronic diary-based study

TL;DR: In this paper , the authors examined the effects of working from home (WFH) on sleep and activity patterns in the transition to normality during the later stages of the Covid-19 pandemic (Aug 2021-Jan 2022).
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Prepandemic Alzheimer Disease Biomarkers and Anxious-Depressive Symptoms During the COVID-19 Confinement in Cognitively Unimpaired Adults

- 02 Aug 2022 - 
TL;DR: In this article , the authors investigated whether β-amyloid, cortical thickness in medial temporal lobe structures, neuroinflammation, and sociodemographic factors were associated with greater anxious-depressive symptoms during the COVID-19 confinement.
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Predicting the Severity of Lockdown-Induced Psychiatric Symptoms with Machine Learning

TL;DR: A supervised machine learning method is used to identify the predictors of the severity of psychiatric symptoms during the Italian lockdown due to the COVID-19 pandemic and may be used to predict the psychiatric prognosis of individuals under a large-scale lockdown and thus supporting the related clinical decisions.
Journal ArticleDOI

Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations

TL;DR: In this article , two machine learning techniques, eXtreme Gradient Boosting and Shapley Additive explanations (SHAP), were used to identify the leading predictors and explain their associations with poor mental health.
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A Review Study on the Trends of Psychological Challenges, Coping Ways, and Public Support During the COVID-19 Pandemic in the Vulnerable Populations in the United States

TL;DR: The authors' review findings indicate that COVID-19 has a considerable impact on the psychological wellbeing of various age groups differently, especially in the elderly population and HCWs, and in that regard, analysis of wider societal structural factors is recommended.
References
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Journal ArticleDOI

The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

TL;DR: The CES-D scale as discussed by the authors is a short self-report scale designed to measure depressive symptomatology in the general population, which has been used in household interview surveys and in psychiatric settings.
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The psychological impact of quarantine and how to reduce it: rapid review of the evidence.

TL;DR: A review of the psychological impact of quarantine using three electronic databases is presented in this article, where the authors report negative psychological effects including post-traumatic stress symptoms, confusion, and anger.
Journal Article

A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7

TL;DR: The GAD-7 is a valid and efficient tool for screening for GAD and assessing its severity in clinical practice and research.
Journal ArticleDOI

The PHQ-9: A new depression diagnostic and severity measure

TL;DR: A number of case-finding instruments for detecting depression in primary care, ranging from 2 to 28 items, tend to be highly correlated, with little evidence that one measure is superior to any other.
Journal ArticleDOI

The brief resilience scale: assessing the ability to bounce back.

TL;DR: The brief resilience scale (BRS) is a reliable means of assessing resilience as the ability to bounce back or recover from stress and may provide unique and important information about people coping with health-related stressors.
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