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As practitioners and scientists reflect on what can be learned from COVID, we argue that cultural defaults—commonsense, rational, and taken-for-granted ways of thinking, feeling, and acting —played an important role in how countries responded to the pandemic, and help explain why the United States suffered 4-6 times more deaths per 100,000 people compared to the East Asian countries of Japan, Taiwan, and South Korea. Drawing on a recent review and theoretical integration, we describe six pairs of contrasting cultural defaults that were common in how the U.S. and some East Asian nations responded to the pandemic: (1) optimism-uniqueness vs. realism-similarity, (2) single vs. multiple causes, (3) expression of high vs. low arousal emotions, (4) influ-ence-control vs. wait-adjust, (5) personal choice-self-regulation vs. social choice-social regulation, and (6) pro-motion vs. prevention. These historically-derived defaults are often outside of individual awareness, but are reflected in and reinforced by institutional practices and policies, the media, and everyday interactions. They are infused with cultural values, understood as the “right way” to be or behave, and are adaptive in their respective contexts. Importantly, both constellations of cultural defaults are viable depending on the problem to be solved. We then provide six specific ways in which public health officers might productively consider these and other cultural defaults when preparing for the next crisis and planning how to effectively motivate people to protect their own and others’ health. Our hope is to facilitate efforts to include a focus on culture within the scope of the social determinants of health and to encourage more partnerships between behavioral scientists and public health practitioners. Recognizing the cultural defaults of the various “publics” they seek to protect is critical as U.S. public health officers aim to promote health for all, a significant and complex challenge in the increasingly individualistic U.S. 

As social media becomes a key channel for news consumption and sharing, proliferating partisan and mainstream news sources must increasingly compete for users’ attention. While affective qualities of news content may promote engagement, it is not clear whether news source bias influences affective content production or virality, or whether any differences have changed over time. We analyzed the sentiment of ~30 million posts (ontwitter.com) from 182 U.S. news sources that ranged from extreme left to right bias over the course of a decade (2011–2020). Biased news sources (on both left and right) produced more high arousal negative affective content than balanced sources. High arousal negative content also increased reposting for biased versus balanced sources. The combination of increased prevalence and virality for high arousal negative affective content was not evident for other types of affective content. Over a decade, the virality of high arousal negative affective content also increased, particularly in balanced news sources, and in posts about politics. Together, these findings reveal that high arousal negative affective content may promote the spread of news from biased sources, and conversely imply that sentiment analysis tools might help social media users to counteract these trends. 

Five years after the beginning of the COVID pandemic, one thing is clear: The East Asian countries of Japan, Taiwan, and South Korea outperformed the United States in responding to and controlling the outbreak of the deadly virus. Although multiple factors likely contributed to this disparity, we propose that the culturally linked psychological defaults (“cultural defaults”) that pervade these contexts also played a role. Cultural defaults are commonsense, rational, taken-for-granted ways of thinking, feeling, and acting. In the United States, these cultural defaults include optimism and uniqueness, single cause, high arousal, influence and control, personal choice and self-regulation, and promotion. In Japan, Taiwan, and South Korea, these defaults include realism and similarity, multiple causes, low arousal, waiting and adjusting, social choice and social regulation, and prevention. In this article, we (a) synthesize decades of empirical research supporting these unmarked defaults; (b) illustrate how they were evident in the announcements and speeches of high-level government and organizational decision makers as they addressed the existential questions posed by the pandemic, including “Will it happen to me/us?” “What is happening?” “What should I/we do?” and “How should I/we live now?”; and (c) show the similarities between these cultural defaults and different national responses to the pandemic. The goal is to integrate some of the voluminous literature in psychology on cultural variation between the United States and East Asia particularly relevant to the pandemic and to emphasize the crucial and practical significance of meaning-making in behavior during this crisis. We provide guidelines for how decision makers might take cultural defaults into account as they design policies to address current and future novel and complex threats, including pandemics, emerging technologies, and climate change. 

Social media platforms are too often understood as monoliths with clear priorities. Instead, we analyze them as complex organizations torn between starkly different justifications of their missions. Focusing on the case of Meta, we inductively analyze the company’s public materials and identify three evaluative logics that shape the platform’s decisions: an engagement logic, a public debate logic, and a wellbeing logic. There are clear trade-offs between these logics, which often result in internal conflicts between teams and departments in charge of these different priorities. We examine recent examples showing how Meta rotates between logics in its decision-making, though the goal of engagement dominates in internal negotiations. We outline how this framework can be applied to other social media platforms such as TikTok, Reddit, and X. We discuss the ramifications of our findings for the study of online harms, exclusion, and extraction.