There has been a widespread increase in affective disorders after the emergence of the COVID-19 pandemic. In the current study, we investigated the effects of exposure to and perceived accuracy of news media and demographic characteristics on anxiety and depressive symptoms. We conducted an online survey of US adults (N = 480) using hierarchical linear regression models to understand the predictive roles of duration and frequency of news media exposure, as well as the perceived accuracy of COVID-19 portrayal by the news media, on anxiety and depression. Increased exposure duration predicted greater anxiety, and decreased frequency of exposure and perceived overreaction in the news media coverage of COVID-19 were linked to greater anxiety and depression. Perceived accuracy moderated the relationship of exposure frequency to both affective outcomes. Accordingly, our data support the importance of adequate levels of accurate and trusted information to help mitigate the overall mental health burden of the pandemic.
Given the varied emotional and behavioral responses to the COVID-19 pandemic across the United States, further attention to the personal and societal influences on such responses is necessary. We investigated the predictive influence of personal political affiliation and the congruity of personal and governor political affiliation on COVID-19 emotional and behavioral responses, with specific attention to the influence of intolerance of uncertainty (IU) on emotional response. These factors were assessed in two studies of adults in the United States (
N
= 480,
N
= 272). We utilized a series of hierarchical linear and logistic regressions to assess predictors of 4 outcomes: (1) trust in governor’s response to the pandemic, (2) COVID-19 related worry, and the (3) usage and (4) perceived efficacy of protective health behaviors (e.g., wearing a mask). Across these studies, we found that IU predicted increased COVID-19 related worry. Further, age and personal political affiliation, but not concordance with governor affiliation, predicted COVID-19 behavioral responses. These findings are discussed in relation to the potential importance of linking health messaging to personal characteristics.
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