Mental Health and Its Predictors during the Early Months of the COVID-19 Pandemic Experience in the United States

Abstract

To date, there has been relatively little published research on the mental health impacts of COVID-19 for the general public at the beginning of the U.S.’ experience of the pandemic, or the factors associated with stress, anxiety, depression, and post-traumatic growth during this time. The current study provides a longitudinal examination of the predictors of self-reported stress, anxiety, depression, and post-traumatic growth for U.S. residents between April and May, 2020, including the influence of demographic, psychosocial, and behavioral factors on these outcomes. The findings indicate that, generally, the early months of the U.S. COVID-19 experience were characterized by a modest negative impact on mental health. Younger adults, people with pre-existing health conditions, and those experiencing greater perceived risk, higher levels of rumination, higher levels of co-rumination, greater social strain, or less social support reported worse mental health. Positive mental health was associated with the adoption of coping strategies, especially those that were forward-looking, and with greater adherence to national health-protection guidelines. The findings are discussed with regard to the current status of health-protective measures and mental health in the U.S., especially as these impact future management of the on-going pandemic.

The psychological burden of the COVID-19 pandemic severity

“…Particularly, Donnelly and Farina (2020) report worse consequences of household income shock for anxiety and depression during the COVID-19 pandemic among individuals living in red states than those living in blue states. Zhou et al (2020) show that individuals identified as Republicans report higher stress and anxiety compared to Democrats. Our finding on the heterogeneous effects of COVID-19 pandemic severity by political affiliation supports the latter line of studies.…”

“…Some studies show that individuals who identify themselves as Republicans are less likely to be worried about COVID-19 and less likely to adhere to social distancing measures, relative to those who identify themselves as Democrats ( Allcott et al, 2020 , Calvillo et al, 2020 ). However, other studies point to the larger psychological impacts on Republicans ( Donnelly and Farina, 2020 , Zhou et al, 2020 ). Particularly, Donnelly and Farina (2020) report worse consequences of household income shock for anxiety and depression during the COVID-19 pandemic among individuals living in red states than those living in blue states.…”

Female top performers in higher education STEM and humanities: socio-emotional perceptions and digital learning-related characteristics during COVID-19

“…The percentage of male and female students that are also top performers as indicated in our study reflects performance rates captured before the onset of the COVID-19 pandemic. In contrast, the other variables reported refer to the moment at the beginning of the COVID-19 pandemic, when the psychological stress was presumably highest (Zhou, MacGeorge, & Myrick, 2020). The students' answers are more or less strongly influenced by previous experiences before the COVID-19 pandemic.…”

“…During the lockdown caused by the COVID-19 pandemic, and just before the beginning of the 2020 summer semester, we conducted a study with students enrolled at a German university. It was the time when stress, anxiety, and depression were said to be at their highest (Zhou, MacGeorge, & Myrick, 2020). For comparison purposes, we decided to examine STEM as a typical male-dominated field, and Humanities as a typical female-dominated field with regard to the number of students.…”

Emotional impact of health personnel, medical students, and general population samples during COVID-19 pandemic in Lima, Peru: A cross-sectional study.

“…The block, which best explained the data, was chosen using as criterium a smaller AIC. In this case, Block 2 was chosen as the best model that could better explain the data of the ve groups (Block 1: χ 2 (df = 12) = 63.10, AIC = 1139; Block 2: χ 2 (df = 20) = 408.40, AIC = 809; Block 3: χ 2…”