ABSTRACT
Stress related to the COVID-19 pandemic may pose acute threats to caregivers' capacity to cope and result in problematic parenting. However, studies have suggested that some caregivers were able to maintain high resilience when facing hardship. The goal of the present study was to examine how COVID-19-related stress affects resilience and parenting of mothers with young children and whether mothers' individual differences in emotion regulation skills lead to different resilience and parenting outcomes. We followed a sample of 298 mothers in the United States with children between 0 and 3 years old over 9 months beginning in April 2020 when most states were on lockdown. Results indicated that both COVID-19-related stress in April 2020 and greater increases/smaller decreases of COVID-19-related stress across 9 months were associated with mothers' lower resilience in January 2021. Low resilience, in turn, was associated with mothers' higher parenting stress, perceptions of parenting incompetence, and risk for child abuse. Furthermore, for mothers with low and moderate levels of cognitive reappraisal, a greater increase/smaller decrease in COVID-19-related stress was associated with their lower resilience after 9 months. In contrast, for mothers with high cognitive reappraisal, the change in COVID-19-related stress was not related to their resilience. This study demonstrates the importance of cognitive reappraisal for mothers of young children to resist and thrive against chronic and uncontrollable external stressors, which are crucial to preventing mothers' child abuse potential and maintaining positive parenting. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
ABSTRACT
We compared the anxiety levels in prisoners before and after the COVID-19 outbreak and analyzed the causes of the changes in anxiety. The first survey was conducted in October 2019 (T0), and the second was conducted in March 2020 (T1). Generalized anxiety disorder-7 (GAD-7), Patient Health Questionnaire-9, and Insomnia Severity Index scales were selected to assess the quality of emotion and sleep among prisoners (N = 803). Three subjective questions were asked to evaluate prisoners' personal feelings on the COVID-19. Paired Samples T-test, Binary, and Multivariate Logistic Stepwise Regression were used to analyze the data. GAD-7 scores decreased at T1 (p < 0.001). For the prisoners without anxiety at T0 (n = 480), GAD-7's mean value at T1 raised (p < 0.001), whereas the mean value decreased (p < 0.001) for the prisoners with anxiety at T0 (n = 323). For the prisoners without anxiety, shorter years of education (OR = 0.843), COVID-19 (OR = 4.936), severer depression at T1 (OR = 1.683), and severer insomnia at T1 (OR = 1.134) were associated with the new onset of anxiety. For the prisoners with anxiety, anxiety was alleviated in 71.2% and exacerbated in 10.5% at T1. For the alleviators, severer depression at T1 (OR = 0.667) and COVID-19 (OR = 0.258) were associated with anxiety unrelief; severer anxiety at T0 (OR = 1.343) was associated with anxiety alleviation. For the exacerbators, severer anxiety at T0 (OR = 0.517) was associated with anxiety unaggravation; severer depression at T1 (OR = 1.196), COVID-19 (OR = 22.882), and severer depression at T0 (OR = 1.181) were associated with anxiety exacerbation. At the outbreak of COVID-19, prisoners' anxiety was reduced. The main factor was the baseline anxiety levels. That may be related to prison management and the Downward Social Comparison.
ABSTRACT
Background: From the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search index (SI), which represents the frequency that keywords are used in searches. Methods: January 9, 2020 is an important date for the outbreak of COVID-19 in China. We compared the changes of SI before and after for 7 keywords, including "fever", "cough", "nausea", "vomiting", "abdominal pain", "diarrhea", "constipation". The slope and peak values of SI change curves are compared. Ten provinces in China were selected for a separate analysis, including Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Hubei, Sichuan, Shanghai, Xinjiang, Tibet. The change of SI was analyzed separately, and the correlation between SI and demographic and economic data was analyzed. Results: During period I, from January 9 to January 25, 2020, the average daily increase (ADI) of the SI for "diarrhea" was lower than that for "cough" (889.47 vs. 1,799.12, F=11.43, P=0.002). In period II, from January 25 to April 8, 2020, the average daily decrease (ADD) of the SI for "diarrhea" was significantly lower than that for "cough", with statistical significance (cough, 191.40 vs. 441.44, F=68.66, P<0.001). The mean SI after January 9, 2020 (pre-SI) was lower than that before January 9, 2020 (post-SI) (fever, 2,616.41±116.92 vs. 3,724.51±867.81, P<0.001; cough, 3,260.04±308.43 vs. 5,590.66±874.25, P<0.001; diarrhea, 4,128.80±200.82 vs. 4,423.55±1,058.01, P<0.001). The pre-SI mean was correlated with population (P=0.004, R=0.813) and gross domestic product (GDP) (P<0.001, R=0.966). The post-SI peak was correlated with population (P=0.007, R=0.789), GDP (P=0.005, R=0.804), and previously confirmed cases (PCC) (P=0.03, R=0.670). The growth rate of the SI was correlated with the post-SI peak (P=0.04, R=0.649), PCC (P=0.003, R=0.835). Conclusions: Diarrhea was of widespread concern in all provinces before and after the COVID-19 outbreak and may be associated with novel coronavirus infection. Internet big data can reflect the public's concern about diseases, which is of great significance for the study of the epidemiological characteristics of diseases.
ABSTRACT
Background From the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search index (SI), which represents the frequency that keywords are used in searches. Methods January 9, 2020 is an important date for the outbreak of COVID-19 in China. We compared the changes of SI before and after for 7 keywords, including “fever”, “cough”, “nausea”, “vomiting”, “abdominal pain”, “diarrhea”, “constipation”. The slope and peak values of SI change curves are compared. Ten provinces in China were selected for a separate analysis, including Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Hubei, Sichuan, Shanghai, Xinjiang, Tibet. The change of SI was analyzed separately, and the correlation between SI and demographic and economic data was analyzed. Results During period I, from January 9 to January 25, 2020, the average daily increase (ADI) of the SI for “diarrhea” was lower than that for “cough” (889.47 vs. 1,799.12, F=11.43, P=0.002). In period II, from January 25 to April 8, 2020, the average daily decrease (ADD) of the SI for “diarrhea” was significantly lower than that for “cough”, with statistical significance (cough, 191.40 vs. 441.44, F=68.66, P<0.001). The mean SI after January 9, 2020 (pre-SI) was lower than that before January 9, 2020 (post-SI) (fever, 2,616.41±116.92 vs. 3,724.51±867.81, P<0.001;cough, 3,260.04±308.43 vs. 5,590.66±874.25, P<0.001;diarrhea, 4,128.80±200.82 vs. 4,423.55±1,058.01, P<0.001). The pre-SI mean was correlated with population (P=0.004, R=0.813) and gross domestic product (GDP) (P<0.001, R=0.966). The post-SI peak was correlated with population (P=0.007, R=0.789), GDP (P=0.005, R=0.804), and previously confirmed cases (PCC) (P=0.03, R=0.670). The growth rate of the SI was correlated with the post-SI peak (P=0.04, R=0.649), PCC (P=0.003, R=0.835). Conclusions Diarrhea was of widespread concern in all provinces before and after the COVID-19 outbreak and may be associated with novel coronavirus infection. Internet big data can reflect the public’s concern about diseases, which is of great significance for the study of the epidemiological characteristics of diseases.
ABSTRACT
Objective: To explore the material basis and potential mechanism of Qufeidu No.1 Prescription in the treatment of corona virus disease 2019 (COVID-19) by network pharmacology and molecular docking technology.