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Explaining Variation in Parents' and Their Children's Stress During COVID-19 Lockdowns.

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TLDR
In this paper, the authors examine a variation in parents' and children's stress during the lockdowns in the first half of 2020 and detect the correlates of families' stress, finding that parents raising both pre-school-and school-aged children were at a particular risk of experiencing stress in response to regulations.
Abstract
The coronavirus pandemic poses a substantial threat to people across the globe. In the first half of 2020, governments limited the spread of virus by imposing diverse regulations. These regulations had a particular impact on families as parents had to manage their occupational situation and childcare in parallel. Here, we examine a variation in parents' and children's stress during the lockdowns in the first half of 2020 and detect the correlates of families' stress. Between April and June 2020, we conducted an explorative online survey among n = 422 parents of 3- to 10-year-old children residing in 17 countries. Most participants came from Germany (n = 274), Iran (n = 70), UK (n = 23), and USA (n = 23). Parents estimated their own stress, the stress of their own children, and various information on potential correlates (e.g., accommodation, family constellation, education, community size, playtime for children, contact with peers, media consumption, and physical activity). Parents also stated personal values regarding openness to change, self-transcendence, self-enhancement, and conservation. The results indicate a substantial variation in the stress levels of families and their diverse reactions to regulations. Media consumption by children commonly increased in comparison to the time before the pandemic. Parents raising both pre-school- and school-aged children were at a particular risk of experiencing stress in response to regulations. Estimated stress and reactions varied with the age of children and the personal values of parents, suggesting that such variables need to be considered when implementing and evaluating regulations and supporting young families in the current and future pandemic.

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Journal ArticleDOI

Short-term and long-term effects of the COVID-19 pandemic on child psychological well-being: a four-wave longitudinal study

TL;DR: In this paper , the authors collected parental reports via online questionnaires over four measurement occasions during the COVID-19 pandemic in Germany (non-probabilistic sample) and found evidence for quadratic growth models.
Proceedings ArticleDOI

Mental Stress Analysis of Bangladeshi Job Holders During Covid-19 pandemic: A Machine Learning Approach

TL;DR: In this article , the authors used Logistic Regression, KNN, Naive Bayes, and Decision Tree to evaluate mental fitness of employees who work from home and offices.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI

Simultaneous inference in general parametric models.

TL;DR: This paper describes simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters, and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalizedlinear models, linear mixed effects models, the Cox model, robust linear models, etc.
Journal ArticleDOI

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.
Book

An R Companion to Applied Regression

Sanford Weisberg, +1 more
TL;DR: This tutorial jumps right in to the power of R without dragging you through the basic concepts of the programming language.
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