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Abstract Belief in conspiracy theories has significant social and political consequences. While prior research has focused primarily on psychological predispositions as drivers of conspiracy beliefs, relatively less is known about the role of social networks. Here, we examine how information received from different sources is linked to the endorsement of conspiracy theories, using the 2024 attempted assassination of presidential candidate Donald Trump as a case study. In surveys conducted days after the attack, social media was the most commonly reported source of conspiracy theories about the event. At the same time, information consumption on social media was not consistently associated with stronger conspiracy beliefs. In contrast, information received through interpersonal ties was more closely linked to belief in both left-leaning and right-leaning conspiratorial narratives. These findings highlight the importance of examining the social dimensions of conspiracy belief formation. Understanding how interpersonal communication shapes conspiracy beliefs is critical for explaining their spread and persistence. Future research would benefit from further investigating the social contexts that sustain conspiratorial thinking. 

ImportanceEfforts to understand the complex association between social media use and mental health have focused on depression, with little investigation of other forms of negative affect, such as irritability and anxiety. ObjectiveTo characterize the association between self-reported use of individual social media platforms and irritability among US adults. Design, Setting, and ParticipantsThis survey study analyzed data from 2 waves of the COVID States Project, a nonprobability web-based survey conducted between November 2, 2023, and January 8, 2024, and applied multiple linear regression models to estimate associations with irritability. Survey respondents were aged 18 years and older. ExposureSelf-reported social media use. Main Outcomes and MeasuresThe primary outcome was score on the Brief Irritability Test (range, 5-30), with higher scores indicating greater irritability. ResultsAcross the 2 survey waves, there were 42 597 unique participants, with mean (SD) age 46.0 (17.0) years; 24 919 (58.5%) identified as women, 17 222 (40.4%) as men, and 456 (1.1%) as nonbinary. In the full sample, 1216 (2.9%) identified as Asian American, 5939 (13.9%) as Black, 5322 (12.5%) as Hispanic, 624 (1.5%) as Native American, 515 (1.2%) as Pacific Islander, 28 354 (66.6%) as White, and 627 (1.5%) as other (ie, selecting the other option prompted the opportunity to provide a free-text self-description). In total, 33 325 (78.2%) of the survey respondents reported daily use of at least 1 social media platform, including 6037 (14.2%) using once a day, 16 678 (39.2%) using multiple times a day, and 10 610 (24.9%) using most of the day. Frequent use of social media was associated with significantly greater irritability in univariate regression models (for more than once a day vs never, 1.43 points [95% CI, 1.22-1.63 points]; for most of the day vs never, 3.37 points [95% CI, 3.15-3.60 points]) and adjusted models (for more than once a day, 0.38 points [95% CI, 0.18-0.58 points]; for most of the day, 1.55 points [95% CI, 1.32-1.78 points]). These associations persisted after incorporating measures of political engagement. Conclusions and RelevanceIn this survey study of 42 597 US adults, irritability represented another correlate of social media use that merits further characterization, in light of known associations with depression and suicidality. 

ImportanceGenerative artificial intelligence (AI) has rapidly entered mainstream use in the US, but its association with mental health has not been characterized. ObjectiveTo examine the associations of the extent and type of generative AI use among US adults with negative affective symptoms in a large, nationally representative sample. Design, Setting, and ParticipantsThis survey study used data from a 50-state US internet nonprobability survey conducted between April and May 2025. Survey respondents were aged 18 years and older. Data were analyzed in August 2025. ExposureParticipants self-reported generative AI and social media use. Main Outcomes and MeasuresThe outcome of interest, negative affect, was measured using the Patient Health Questionnaire 9-item (PHQ-9). ResultsThere were 20 847 unique participants, with mean (SD) age 47.3 (17.1) years and 10 327 (49.5%) female, 10 386 (49.8%) male, and 134 (0.6%) nonbinary participants; 2152 participants (10.3%) reported using AI at least daily, including 1053 participants (5.1%) who reported daily use and 1099 participants (5.3%) who reported use multiple times per day. Among participants who used daily or more frequently, 1033 (48.0%) reported use for work, 246 (11.4%) for school, and 1875 (87.1%) for personal applications. In survey-weighted regression models, daily or more frequent AI use was significantly more common among men, younger adults, those with higher education and income, and those in urban settings. Greater AI use was associated with greater levels of depressive symptoms in sociodemographic-adjusted regression models: (daily use: β = 1.08 [95% CI, 0.55-1.62]; multiple times per day: β = 0.86 [95% CI, 0.35-1.37]) compared with nonuse, and with greater likelihood of reporting at least moderate depressive symptoms (odds ratio [OR], 1.29 [95% CI, 1.15-1.46]); similar patterns were observed for anxiety and irritability. The highest estimates were observed among individuals using AI for personal use (β = 0.31 [95% CI, 0.10-0.52]) and those aged 25 to 44 years (β = 1.22 [95% CI, 0.70-1.74]) or 45 to 64 years (β = 1.38 [95% CI, 0.72-2.05]). Conclusions and RelevanceThis survey study found that AI use was significantly associated with greater depressive symptoms, with magnitude of differences varying by age group. Further work is needed to understand whether these associations are causal and explain heterogeneous effects. 

ImportanceTrust in physicians and hospitals has been associated with achieving public health goals, but the increasing politicization of public health policies during the COVID-19 pandemic may have adversely affected such trust. ObjectiveTo characterize changes in US adults’ trust in physicians and hospitals over the course of the COVID-19 pandemic and the association between this trust and health-related behaviors. Design, Setting, and ParticipantsThis survey study uses data from 24 waves of a nonprobability internet survey conducted between April 1, 2020, and January 31, 2024, among 443 455 unique respondents aged 18 years or older residing in the US, with state-level representative quotas for race and ethnicity, age, and gender. Main Outcome and MeasureSelf-report of trust in physicians and hospitals; self-report of SARS-CoV-2 and influenza vaccination and booster status. Survey-weighted regression models were applied to examine associations between sociodemographic features and trust and between trust and health behaviors. ResultsThe combined data included 582 634 responses across 24 survey waves, reflecting 443 455 unique respondents. The unweighted mean (SD) age was 43.3 (16.6) years; 288 186 respondents (65.0%) reported female gender; 21 957 (5.0%) identified as Asian American, 49 428 (11.1%) as Black, 38 423 (8.7%) as Hispanic, 3138 (0.7%) as Native American, 5598 (1.3%) as Pacific Islander, 315 278 (71.1%) as White, and 9633 (2.2%) as other race and ethnicity (those who selected “Other” from a checklist). Overall, the proportion of adults reporting a lot of trust for physicians and hospitals decreased from 71.5% (95% CI, 70.7%-72.2%) in April 2020 to 40.1% (95% CI, 39.4%-40.7%) in January 2024. In regression models, features associated with lower trust as of spring and summer 2023 included being 25 to 64 years of age, female gender, lower educational level, lower income, Black race, and living in a rural setting. These associations persisted even after controlling for partisanship. In turn, greater trust was associated with greater likelihood of vaccination for SARS-CoV-2 (adjusted odds ratio [OR], 4.94; 95 CI, 4.21-5.80) or influenza (adjusted OR, 5.09; 95 CI, 3.93-6.59) and receiving a SARS-CoV-2 booster (adjusted OR, 3.62; 95 CI, 2.99-4.38). Conclusions and RelevanceThis survey study of US adults suggests that trust in physicians and hospitals decreased during the COVID-19 pandemic. As lower levels of trust were associated with lesser likelihood of pursuing vaccination, restoring trust may represent a public health imperative. 

Abstract Americans’ trust in scientists has been stable and high, relative to other political and social institutions, for the last half century (Krause, Brossard, and Scheufele 2019). Yet, underlying this stability lies a dramatic change such that a partisan gap has emerged, with Democrats exhibiting substantially more trust than Republicans. Fifty years ago, Republicans in fact exhibited more relative trust in scientists. This article explains this continuity and change. First, we demonstrate that the demographic correlates of trust in scientists have been remarkably stable for more than a half century: women, Black, rural, religious, non-college educated, and lower/working-class individuals exhibit less trust than their counterparts. Second, we show that the partisan relationship with trust in scientists has flipped (over that same time period) as low-trusting demographic strata shifted partisan allegiances. This is particularly the case when it comes to education and religiosity. Concomitant with the emergent partisan gap is a massive perceptual gap among Democrats, who perceive a partisan divide more than double its actual size. Democrats vastly underestimate Republicans’ trust in scientists. The enduring demographic basis of trust in scientists provides an opportunity to bridge partisan divides by addressing demographic inequities in the practice and application of science. 

Abstract Depression can affect individuals’ attitudes by enhancing cognitive biases and altering perceptions of control. We investigate the relationship between depressive symptoms and Americans’ attitudes regarding domestic extremist violence. We develop a theory that suggests the association between depression and support for political violence depends on conspiracy beliefs, participatory inclinations, and their combination. We test our theory using a two‐wave national survey panel from November 2020 and January 2021. We find that among those who hold conspiracy beliefs and/or have participatory inclinations, depression is positively associated with support for election violence and the January 6 Capitol riots. The participatory inclination dynamic is particularly strong for men. Our findings reveal how the intersection of two concerning features of American society—poor mental health and conspiratorial beliefs—strongly relate to another feature: support for political violence. The results also make clear that interventions aimed at addressing depression can potentially have substantial political consequences. 

ImportanceThe frequent occurrence of cognitive symptoms in post–COVID-19 condition has been described, but the nature of these symptoms and their demographic and functional factors are not well characterized in generalizable populations. ObjectiveTo investigate the prevalence of self-reported cognitive symptoms in post–COVID-19 condition, in comparison with individuals with prior acute SARS-CoV-2 infection who did not develop post–COVID-19 condition, and their association with other individual features, including depressive symptoms and functional status. Design, Setting, and ParticipantsTwo waves of a 50-state nonprobability population-based internet survey conducted between December 22, 2022, and May 5, 2023. Participants included survey respondents aged 18 years and older. ExposurePost–COVID-19 condition, defined as self-report of symptoms attributed to COVID-19 beyond 2 months after the initial month of illness. Main Outcomes and MeasuresSeven items from the Neuro-QoL cognition battery assessing the frequency of cognitive symptoms in the past week and patient Health Questionnaire-9. ResultsThe 14 767 individuals reporting test-confirmed COVID-19 illness at least 2 months before the survey had a mean (SD) age of 44.6 (16.3) years; 568 (3.8%) were Asian, 1484 (10.0%) were Black, 1408 (9.5%) were Hispanic, and 10 811 (73.2%) were White. A total of 10 037 respondents (68.0%) were women and 4730 (32.0%) were men. Of the 1683 individuals reporting post–COVID-19 condition, 955 (56.7%) reported at least 1 cognitive symptom experienced daily, compared with 3552 of 13 084 (27.1%) of those who did not report post–COVID-19 condition. More daily cognitive symptoms were associated with a greater likelihood of reporting at least moderate interference with functioning (unadjusted odds ratio [OR], 1.31 [95% CI, 1.25-1.36]; adjusted [AOR], 1.30 [95% CI, 1.25-1.36]), lesser likelihood of full-time employment (unadjusted OR, 0.95 [95% CI, 0.91-0.99]; AOR, 0.92 [95% CI, 0.88-0.96]) and greater severity of depressive symptoms (unadjusted coefficient, 1.40 [95% CI, 1.29-1.51]; adjusted coefficient 1.27 [95% CI, 1.17-1.38). After including depressive symptoms in regression models, associations were also found between cognitive symptoms and at least moderate interference with everyday functioning (AOR, 1.27 [95% CI, 1.21-1.33]) and between cognitive symptoms and lower odds of full-time employment (AOR, 0.92 [95% CI, 0.88-0.97]). Conclusions and RelevanceThe findings of this survey study of US adults suggest that cognitive symptoms are common among individuals with post–COVID-19 condition and associated with greater self-reported functional impairment, lesser likelihood of full-time employment, and greater depressive symptom severity. Screening for and addressing cognitive symptoms is an important component of the public health response to post–COVID-19 condition. 

Abstract 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. 

Abstract Public health requires collective action—the public best addresses health crises when individuals engage in prosocial behaviors. Failure to do so can have dire societal and economic consequences. This was made clear by the disjointed, politicized response to COVID-19 in the United States. Perhaps no aspect of the pandemic exemplified this challenge more than the sizeable percentage of individuals who delayed or refused vaccination. While scholars, practitioners, and the government devised a range of communication strategies to persuade people to get vaccinated, much less attention has been paid to where the unvaccinated could be reached. We address this question using multiple waves of a large national survey as well as various secondary data sets. We find that the vaccine resistant seems to predictably obtain information from conservative media outlets (e.g. Fox News) while the vaccinated congregate around more liberal outlets (e.g. MSNBC). We also find consistent evidence that vaccine-resistant individuals often obtain COVID-19 information from various social media, most notably Facebook, rather than traditional media sources. Importantly, such individuals tend to exhibit low institutional trust. While our results do not suggest a failure of sites such as Facebook's institutional COVID-19 efforts, as the counterfactual of no efforts is unknown, they do highlight an opportunity to reach those who are less likely to take vital actions in the service of public health.