Conspiratorial beliefs can endanger individuals and societies by increasing the likelihood of harmful behaviors such as the flouting of public health guidelines. While scholars have identified various correlates of conspiracy beliefs, one factor that has received scant attention is depressive symptoms. We use three large surveys to explore the connection between depression and conspiracy beliefs. We find a consistent association, with the extent of the relationship depending on individual and situational factors. Interestingly, those from relatively advantaged demographic groups (i.e., White, male, high income, educated) exhibit a stronger relationship between depression and conspiracy beliefs than those not from such groups. Furthermore, situational variables that ostensibly increase stress—such as having COVID‐19 or parenting during COVID‐19—exacerbate the relationship while those that seem to decrease stress, such as social support, vitiate it. The results provide insight about the development of targeted interventions and accentuate the need for theorizing about the mechanisms that lead depression to correlate with conspiracy beliefs.

To what extent do partisan media influence political attitudes and behavior in the United States? Although recent methodological advancements have improved scholars’ ability to identify the persuasiveness of partisan media, past studies typically rely on self-reported measures of media preferences, which may deviate from real-world news consumption. Integrating individual-level web-browsing data with a large-scale survey, we contrast survey-based indicators of stated preferences with behavioral measures of revealed preferences, based on the relative volume and slant of news individuals consume. Overall, we find that these measurement strategies generate differing conclusions regarding heterogeneity in partisan media’s persuasive impact. Whereas the stated preference measures raise the possibility of persuasion by counter-attitudinal sources, the revealed preference measures offer a more nuanced portrait of media effects. Specifically, among respondents who regularly consume ideologically slanted content, partisan media exposure appears to result in limited attitude change, with any observed treatment effects driven primarily by pro-attitudinal outlets.

 

Importance  Persistence of COVID-19 symptoms beyond 2 months, or long COVID, is increasingly recognized as a common sequela of acute infection.

Objectives  To estimate the prevalence of and sociodemographic factors associated with long COVID and to identify whether the predominant variant at the time of infection and prior vaccination status are associated with differential risk.

Design, Setting, and Participants  This cross-sectional study comprised 8 waves of a nonprobability internet survey conducted between February 5, 2021, and July 6, 2022, among individuals aged 18 years or older, inclusive of all 50 states and the District of Columbia.

Main Outcomes and Measures  Long COVID, defined as reporting continued COVID-19 symptoms beyond 2 months after the initial month of symptoms, among individuals with self-reported positive results of a polymerase chain reaction test or antigen test.

Results  The 16 091 survey respondents reporting test-confirmed COVID-19 illness at least 2 months prior had a mean age of 40.5 (15.2) years; 10 075 (62.6%) were women, and 6016 (37.4%) were men; 817 (5.1%) were Asian, 1826 (11.3%) were Black, 1546 (9.6%) were Hispanic, and 11 425 (71.0%) were White. From this cohort, 2359 individuals (14.7%) reported continued COVID-19 symptoms more than 2 months after acute illness. Reweighted to reflect national sociodemographic distributions, these individuals represented 13.9% of those who had tested positive for COVID-19, or 1.7% of US adults. In logistic regression models, older age per decade above 40 years (adjusted odds ratio [OR], 1.15; 95% CI, 1.12-1.19) and female gender (adjusted OR, 1.91; 95% CI, 1.73-2.13) were associated with greater risk of persistence of long COVID; individuals with a graduate education vs high school or less (adjusted OR, 0.67; 95% CI, 0.56-0.79) and urban vs rural residence (adjusted OR, 0.74; 95% CI, 0.64-0.86) were less likely to report persistence of long COVID. Compared with ancestral COVID-19, infection during periods when the Epsilon variant (OR, 0.81; 95% CI, 0.69-0.95) or the Omicron variant (OR, 0.77; 95% CI, 0.64-0.92) predominated in the US was associated with diminished likelihood of long COVID. Completion of the primary vaccine series prior to acute illness was associated with diminished risk for long COVID (OR, 0.72; 95% CI, 0.60-0.86).

Conclusions and Relevance  This study suggests that long COVID is prevalent and associated with female gender and older age, while risk may be diminished by completion of primary vaccination series prior to infection.

Politics and science have become increasingly intertwined. Salient scientific issues such as climate change, evolution, and stem cell research become politicized, pitting partisans against one another. This creates a challenge of how to effectively communicate on such issues. Recent work emphasizes the need for tailored messages to specific groups. Here, we focus on whether generalized messages also can matter. We do so in the context of a highly polarized issue – extreme COVID-19 vaccine resistance. The results show that science-based, moral frame, and social norm messages move behavioral intentions, and do so by the same amount across the population (i.e., homogenous effects). Counter to common portrayals, the politicization of science does not preclude using broad messages that resonate with the entire population.

 

Many topics social scientists study are sensitive in nature. Although we know directly asking

about these issues can lead to nonresponse, we know very little about how such questions could potentially influence responses to questions later in the survey. In this study, we use the Trump administration’s proposal to include a citizenship question on the 2020 Census to demonstrate how such spillover effects can undermine important survey-based estimates, like the number of Hispanics in the United States. Using a large survey experiment (n = 9,035 respondents), we find that asking about citizenship status significantly increases the percent of questions skipped and makes respondents less likely to report having members of their household wh  are of Hispanic ethnicity. Not only does this demonstrate how sensitive questions can have important downstream effects, but our results also speak to an important public policy debate which will likely arise again in the future.

 

Importance  Misinformation about COVID-19 vaccination may contribute substantially to vaccine hesitancy and resistance.

Objective  To determine if depressive symptoms are associated with greater likelihood of believing vaccine-related misinformation.

Design, Setting, and Participants  This survey study analyzed responses from 2 waves of a 50-state nonprobability internet survey conducted between May and July 2021, in which depressive symptoms were measured using the Patient Health Questionnaire 9-item (PHQ-9). Survey respondents were aged 18 and older. Population-reweighted multiple logistic regression was used to examine the association between moderate or greater depressive symptoms and endorsement of at least 1 item of vaccine misinformation, adjusted for sociodemographic features. The association between depressive symptoms in May and June, and new support for misinformation in the following wave was also examined.

Importance  Some studies suggest that social media use is associated with risk for depression, particularly among children and young adults.

Objective  To characterize the association between self-reported use of individual social media platforms and worsening of depressive symptoms among adults.

Design, Setting, and Participants  This survey study included data from 13 waves of a nonprobability internet survey conducted approximately monthly between May 2020 and May 2021 among individuals aged 18 years and older in the US. Data were analyzed in July and August 2021.

Main Outcomes and Measures  Logistic regression was applied without reweighting, with a 5 point or greater increase in 9-item Patient Health Questionnaire (PHQ-9) score as outcome and participant sociodemographic features, baseline PHQ-9, and use of each social media platform as independent variables.

Results  In total, 5395 of 8045 individuals (67.1%) with a PHQ-9 score below 5 on initial survey completed a second PHQ-9. These respondents had a mean (SD) age of 55.8 (15.2) years; 3546 respondents (65.7%) identified as female; 329 respondents (6.1%) were Asian, 570 (10.6%) Black, 256 (4.7%) Hispanic, 4118 (76.3%) White, and 122 (2.3%) American Indian or Alaska Native, Pacific Islander or Native Hawaiian, or other. Among eligible respondents, 482 (8.9%) reported 5 points or greater worsening of PHQ-9 score at second survey. In fully adjusted models for increase in symptoms, the largest adjusted odds ratio (aOR) associated with social media use was observed for Snapchat (aOR, 1.53; 95% CI, 1.19-1.96), Facebook (aOR, 1.42; 95% CI, 1.10-1.81), and TikTok (aOR, 1.39; 95% CI, 1.03-1.87).

Conclusions and Relevance  Among survey respondents who did not report depressive symptoms initially, social media use was associated with greater likelihood of subsequent increase in depressive symptoms after adjustment for sociodemographic features and news sources. These data cannot elucidate the nature of this association, but suggest the need for further study to understand how social media use may factor into depression among adults.

Introduction: The major stressors associated with the COVID‐19 pandemic provide an opportunity to understand the extent to which protective factors against depression may exhibit gender‐specificity.

Method: This study examined responses from multiple waves of a 50 states non‐ probability internet survey conducted between May 2020 and January 2021. Participants completed the PHQ‐9 as a measure of depression, as well as items characterizing social supports. We used logistic regression models with population reweighting to examine association between absence of even mild depressive symptoms and sociodemographic features and social supports, with interaction terms and stratification used to investigate sex‐specificity.

Results: Among 73,917 survey respondents, 31,199 (42.2%) reported absence of mild or greater depression—11,011/23,682 males (46.5%) and 20,188/50,235 (40.2%) females. In a regression model, features associated with greater likelihood of depression‐resistance included at least weekly attendance of religious services (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04–1.16) and greater trust in others (OR: 1.04 for a 2‐unit increase, 95% CI: 1.02–1.06), along with level of social support measured as number of social ties available who could provide care (OR: 1.05, 95% CI: 1.02–1.07), talk to them (OR: 1.10, 95% CI: 1.07–1.12), and help with employment (OR: 1.06, 95% CI: 1.04–1.08). The first two features showed significant interaction with gender (p < .0001), with markedly greater protective effects among women.

Conclusion: Aspects of social support are associated with diminished risk of major depressive symptoms, with greater effects of religious service attendance and trust in others observed among women than men.

After acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a subset of individuals experience persistent symptoms involving mood, sleep, anxiety, and fatigue, which may contribute to markedly elevated rates of major depressive disorder observed in recent epidemiologic studies. In this study, we investigated whether acute coronavirus disease 2019 (COVID-19) symptoms are associated with the probability of subsequent depressive symptoms.

Concerns about misperceptions among the public are rampant. Yet, little work explores the correlates of misperceptions in varying contexts – that is, how do factors such as group affiliations, media exposure, and lived experiences correlate with the number of misperceptions people hold? We address these questions by investigating misperceptions about COVID-19, focusing on the role of racial/ethnic, religious, and partisan groups. Using a large survey, we find the number of correct beliefs held by individuals far dwarfs the number of misperceptions. When it comes to misperceptions, we find that minorities, those with high levels of religiosity, and those with strong partisan identities – across parties – hold a substantially greater number of misperceptions than those with contrasting group affiliations. Moreover, we show other variables (e.g., social media usage, number of COVID-19 cases in one’s county) do not have such strong relationships with misperceptions, and the group-level results do not reflect acquiescence to believing any information regardless of its truth value. Our results accentuate the importance of studying group-level misperceptions on other scientific and political issues and developing targeted interventions for these groups.