Irritability and Social Media Use in US Adults

JAMA Network Open · 2025-01-08 · 7 citations

Importance: Efforts 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. Objective: To characterize the association between self-reported use of individual social media platforms and irritability among US adults. Design, Setting, and Participants: This 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. Exposure: Self-reported social media use. Main Outcomes and Measures: The primary outcome was score on the Brief Irritability Test (range, 5-30), with higher scores indicating greater irritability. Results: Across 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 Relevance: In 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.

A national survey of neuropsychiatry training experiences

BJPsych Bulletin · 2025-06-03 · 2 citations

AIMS AND METHOD: Neuropsychiatry training in the UK currently lacks a formal scheme or qualification, and its demand and availability have not been systematically explored. We conducted the largest UK-wide survey of psychiatry trainees to examine their experiences in neuropsychiatry training. RESULTS: In total, 185 trainees from all UK training regions completed the survey. Although 43.6% expressed interest in a neuropsychiatry career, only 10% felt they would gain sufficient experience by the end of training. Insufficient access to clinical rotations was the most common barrier, with significantly better access in London compared with other regions. Most respondents were in favour of additional neurology training (83%) and a formal accreditation in neuropsychiatry (90%). CLINICAL IMPLICATIONS: Strong trainee interest in neuropsychiatry contrasts with the limited training opportunities currently available nationally. Our survey highlights the need for increased neuropsychiatry training opportunities, development of a formalised training programme and a clinical accreditation pathway for neuropsychiatry in the UK.

Derivation of a 3-Item Patient Health Questionnaire as a Shortened Survey to Capture Depressive Symptoms

JAMA Network Open · 2025-07-21 · 3 citations

Importance: Screening measures of depressive symptoms (eg, 9-item Patient Health Questionnaire [PHQ-9]) are increasingly used in surveys and remote applications, where shorter versions would be valuable. Objective: To derive shorter versions of the PHQ-9 that maximize the variability in total depressive symptom severity captured. Design, Setting, and Participants: This survey study used data from 4 waves of a 50-state nonprobability web-based survey conducted between November 2, 2023, and July 21, 2024. Survey respondents were aged 18 years or older. The first survey wave data were used to identify shortened question subsets capturing variance in the PHQ-9 and estimating a PHQ-9 score of 10 or higher. Resulting models (eg, 3-item version of the PHQ [PHQ-3]) were validated in subsequent survey waves. Main Outcome and Measure: Performance of PHQ-3 in the full sample and across subgroups of age, gender, race and ethnicity, and educational levels. Depressive symptom severity was measured with the PHQ-9 (total score range: 0-27, with a score ≥10 indicating moderate or greater depressive symptoms). Results: In the 4 survey waves, there were 96 234 total participants (mean [SD] age, 47.3 [17.1] years; 55 245 [57.4%] identifying as women). In the full sample, 4401 participants (4.6%) identified as Asian American, 12 699 (13.2%) as Black or African American, 9776 (10.2%) as Hispanic or Latino, and 65 309 (67.9%) as White individuals, with 4049 (4.2%) who identified as having other race or ethnicity. Among these participants, the mean (SD) PHQ-9 score was 6.5 (6.6), and 25 411 (26.4%) met the criteria for moderate or greater depressive symptoms (PHQ-9 score ≥10). The optimal 3-item version, PHQ-3, used items 2 (subject: depressed mood), 6 (self-esteem or failure), and 1 (interest), yielding a Cronbach α of 0.88 (95% CI, 0.88-0.88) and Pearson correlation with the PHQ-9 total score of 0.93 (95% CI, 0.93-0.94). At a threshold of 3 or greater, the PHQ-3 sensitivity was 0.98 (95% CI, 0.97-0.98) and specificity was 0.76 (95% CI, 0.75-0.76) for moderate or greater depressive symptoms. Performance was consistent across sociodemographic subgroups and survey waves. Conclusions and Relevance: This survey study of US adults identified a 3-item scale that remained highly correlated with the full PHQ-9 instrument. The reduced set of questions could enable more widespread and efficient incorporation of depressive symptom measurement in general population samples.

CHIP50 Report #115: American Attitudes Toward Government Interventions in Science

2025-07-01 · 1 citations

•Americans who disapprove of the administration’s science-related policies outnumber those who approve by more than two to one. On average, 48% disapprove or strongly disapprove of recent government actions in that space, while only 21% approve or strongly approve.•The most negatively viewed actions are the pause in public health information dissemination (51% disapproval) and the firing of National Oceanic and Atmospheric Administration (NOAA) employees (50% disapproval).•Approval levels for individual actions are low; only the dismantling of the U.S. Agency for International Development (USAID) (29%) and the layoffs at the Centers for Disease Control and Prevention (CDC) (27%) received more than 25% approval.•Average approval of science-related government actions is highest among Republicans (42%), men (28%), graduate degree holders (30%), and high-income respondents (31%). Disapproval is strongest among Democrats (74%), African Americans (56%), women (53%), and those aged 65 and older (55%).•A majority of Americans support greater government investment in research: 57% favor increased medical research funding and 42% support increased scientific research funding. Relatively few want funding cuts: only 10% for medical research and 16% for science.•Even among Republicans, nearly half (48%) favor more medical research funding, though only 31% support increases in science research funding. A quarter of Republicans support cuts for scientific research and 15% for medical research.•While support for research remains strong, the proportion of Americans reporting high trust in scientists declined from 58% in 2020 to 36% in 2025, with sharper drops among Republicans (from 54% to 26%) than among Democrats (from 67% to 50%).•Despite declines in public confidence, scientists and doctors remain more trusted than most institutions, including Congress, the Supreme Court, and the news media.

Conspiratorial thinking in a 50-state survey of American adults

Journal of Affective Disorders · 2025-07-15 · 1 citations

Pandemic, Governors, and Public Opinion: The Effect of COVID-19 Cases and Deaths on Public Support for America’s Governors

International Journal of Public Opinion Research · 2025-01-01

Abstract A longstanding literature in American foreign policy holds that the American public’s support for war significantly depends on the number of U.S. casualties in the conflict (their number, rate, trend, proximity, etc.). While a pandemic is clearly not a war, many observers and political leaders have characterized the U.S. public policy response to the COVID-19 pandemic using the metaphor of wartime. This raises the question of whether such characterizations are more than mere metaphor. Has the American public’s response to pandemic-related casualties—cases and deaths—followed similar patterns to those found in the literature on public opinion and war? In this study, we assess the public’s responsiveness to COVID-19 casualties at different stages in the pandemic. Utilizing two large, 50-state surveys conducted during the two largest COVID surges, in winter 2021 and winter 2022, we test several hypotheses from the public opinion and war literature, including that proximity—spatial and temporal—influences public responses and that the public becomes desensitized to casualties over time. We find that in many respects, the public’s response to the pandemic does indeed mirror the patterns found with respect to public opinion and war.

Representation in science and trust in scientists in the USA

Nature Human Behaviour · 2025-12-08 · 3 citations

Information from social ties predicts conspiracy beliefs: Evidence from the attempted assassination of Donald Trump

PNAS Nexus · 2025-06-01 · 1 citations

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.

Characterizing population-level changes in human behavior during the COVID-19 pandemic in the United States

Proceedings of the National Academy of Sciences · 2025-09-11 · 3 citations

The transmission of communicable diseases in human populations is known to be modulated by behavioral patterns. However, detailed characterizations of how population-level behaviors change over time during multiple disease outbreaks and spatial resolutions are still not widely available. We used data from 431,211 survey responses collected in the United States, between April 2020 and June 2022, to provide a description of how human behaviors fluctuated during the first 2 y of the COVID-19 pandemic. Our analysis suggests that at the national and state levels, people's adherence to recommendations to avoid contact with others (a preventive behavior) was highest early in the pandemic but gradually-and linearly-decreased over time. Importantly, during periods of intense COVID-19 mortality, adaption to preventive behaviors increased-despite the overall temporal decrease. These spatial-temporal characterizations help improve our understanding of the bidirectional feedback loop between outbreak severity and human behavior. Our findings should benefit both computational modeling teams developing methodologies to predict the dynamics of future epidemics and policymakers designing strategies to mitigate the effects of future disease outbreaks.

Short-term exposure to filter-bubble recommendation systems has limited polarization effects: Naturalistic experiments on YouTube

Proceedings of the National Academy of Sciences · 2025-02-18 · 10 citations

An enormous body of literature argues that recommendation algorithms drive political polarization by creating "filter bubbles" and "rabbit holes." Using four experiments with nearly 9,000 participants, we show that manipulating algorithmic recommendations to create these conditions has limited effects on opinions. Our experiments employ a custom-built video platform with a naturalistic, YouTube-like interface presenting real YouTube videos and recommendations. We experimentally manipulate YouTube's actual recommendation algorithm to simulate filter bubbles and rabbit holes by presenting ideologically balanced and slanted choices. Our design allows us to intervene in a feedback loop that has confounded the study of algorithmic polarization-the complex interplay between supply of recommendations and user demand for content-to examine downstream effects on policy attitudes. We use over 130,000 experimentally manipulated recommendations and 31,000 platform interactions to estimate how recommendation algorithms alter users' media consumption decisions and, indirectly, their political attitudes. Our results cast doubt on widely circulating theories of algorithmic polarization by showing that even heavy-handed (although short-term) perturbations of real-world recommendations have limited causal effects on policy attitudes. Given our inability to detect consistent evidence for algorithmic effects, we argue the burden of proof for claims about algorithm-induced polarization has shifted. Our methodology, which captures and modifies the output of real-world recommendation algorithms, offers a path forward for future investigations of black-box artificial intelligence systems. Our findings reveal practical limits to effect sizes that are feasibly detectable in academic experiments.