The advent of COVID-19 vaccination meant a moment of hope after months of crisis communication. However, the context of disinformation on social media threatened the success of this public health campaign. This study examines how heads of government and fact-checking organizations in four countries managed communications on Twitter about the vaccination. Specifically, we conduct a content analysis of their discourses through the observation of propaganda mechanisms. The research draws on a corpus of words related to the pandemic and vaccines in France, Spain, the United Kingdom, and the United States (n = 2,800). The data were captured for a five-month period (January–May 2021), during which COVID-19 vaccines became available for elderly people. The results show a trend of clearly fallacious communication among the political leaders, based on the tools of emphasis and appeal to emotion. We argue that the political messages about the vaccination mainly used propaganda strategies. These tweets also set, to a certain extent, the agendas of the most relevant fact-checking initiatives in each country.

Three North Carolina Medicaid surveys conducted from 2000 to 2012 reported increasing numbers of Hispanic children enrolled in Medicaid and much lower trust in providers expressed by their adult caregiver respondents compared with responses for non-Hispanic Black and White children. To verify and explain this apparent trust chasm, we used bivariate and regression analyses. The variables employed included trust (dependent variable); child’s race/ethnicity, age, and sex; satisfaction and health status scales; two utilization measures; respondent’s age, sex, and education; geographical region; and population density of county of residence. Race/ethnicity was strongly associated with trust (p < .001), controlling for other independent variables. Access, satisfaction, and respondent’s age and education were also significant. Our results fit the Behavioral Model for Vulnerable Populations, which maps the role of significant variables in health-seeking behavior. After analyzing the concept of trust, we argue that lower acculturation explains lower Hispanic trust compared with non-Hispanic Blacks. We suggest policies to improve acculturation.

In recent decades, political psychologists have given a lot of attention to the role of emotions in politics. While there have been several different research programs, the dominant paradigm has been set by affective intelligence theory (AIT), developed by George Marcus, Russell Neuman, and Michael Mackuen. AIT has helped explain many puzzles in understanding how emotions influence political decisions, as any good paradigm should. At the same time, I argue it has also had the effect of limiting broader research into the range of discrete emotions, especially contempt. While recognizing the value of AIT, I call for more research that goes beyond its boundaries, showing through several recent studies how a focus on the additional effects of contempt can improve our understanding of voter decision-making.

People vary in climate change skepticism and in their views on disaster cause and prevention. For example, the United States boasts higher rates of climate skepticism than other countries, especially among Republicans. Research into the individual differences that shape variation in climate-related beliefs represents an important opportunity for those seeking ways to mitigate climate change and climate-related disasters (e.g., floods). In this registered report, we proposed a study examining how individual difference in physical formidability, worldview, and affect relate to attitudes about disaster and climate change. We predicted that highly formidable men would tend to endorse social inequality, hold status quo defensive worldviews, report lower levels of empathy, and report attitudes that promote disaster risk accumulation via lesser support for social intervention. The results of an online study (Study 1) support the notion that men’s self-perceived formidability is related to disaster and climate change beliefs in the predicted direction and that this relationship is mediated by hierarchical worldview and status quo defense but not empathy. An analysis of a preliminary sample for the in-lab study (Study 2) suggests that self-perceived formidability relates to disaster views, climate views, and status quo maintaining worldviews.

The stark divide between the political right and left is rooted in conflicting beliefs, values, and personality—and, recent research suggests, perhaps even lower-level physiological differences between individuals. In this registered report, we investigated a novel domain of ideological differences in physiological processes: interoceptive sensitivity—that is, a person’s attunement to their own internal bodily states and signals (e.g., physiological arousal, pain, and respiration). We conducted two studies testing the hypothesis that greater interoceptive sensitivity would be associated with greater conservatism: one laboratory study in the Netherlands using a physiological heartbeat detection task and one large-scale online study in the United States employing an innovative webcam-based measure of interoceptive sensitivity. Contrary to our predictions, we found evidence that interoceptive sensitivity may instead predict greater political liberalism (versus conservatism), although this association was primarily limited to the American sample. We discuss implications for our understanding of the physiological underpinnings of political ideology.

This is a registered report for a study of racial and ethnic variation in the relationship between negativity bias and political attitudes. Pioneering work on the psychological and biological roots of political orientation has suggested that political conservatism is driven in large part by enhanced negativity bias. This work has been criticized on several theoretical fronts, and recent replication attempts have failed. To dig deeper into the contours of when (and among whom) negativity bias predicts conservatism, we investigate a surprisingly overlooked factor in existing literature: race and ethnicity. We propose that political issues represent threat or disgust in different ways depending on one’s race and ethnicity. We recruited 174 White, Latinx, and Asian American individuals (in equal numbers) to examine how the relationship between negativity bias and political orientation varies by race/ethnicity across four domains: policing/criminal justice, immigration, economic redistribution, and religious social conservatism.

The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data types and recipients, we argue that established social norms shape the acceptance of novel practices of data collection and use. To investigate the willingness to share health data, we conducted a preregistered vignette experiment. The scenarios experimentally varied the vignette dimensions by data type, recipient, and research purpose. While some findings contradict our hypotheses, the results indicate that all three dimensions affected respondents’ data sharing decisions. Additional analyses suggest that institutional and social trust, privacy concerns, technical affinity, altruism, age, and device ownership influence the willingness to share health data.

In 2008, the Chinese government created the Thousand Talents Program (TTP) to recruit overseas expertise to build up China’s science and technology knowledge and innovation base. Ten years later, in 2018, the Federal Bureau of Investigation (FBI) announced a new “China Initiative” that aimed to counter the transfer by U.S.-based scientists involved in the TTP of knowledge and intellectual property that could support China’s military and economic might and pose threats to U.S. national security. This initiative launched a number of investigations into major U.S. federal funding agencies and universities and charged several scientists, many of them life scientists, with failing to accurately report their work and affiliations with Chinese entities and illegally transferring scientific information to China. Although the FBI cases demonstrate a clear problem with disclosure of foreign contracts and research integrity among some TTP recipients, they have failed to demonstrate any harm to U.S. national security interests. At the heart of this controversy are core questions that remain unresolved and need more attention: What is required to transfer and develop knowledge to further a country’s science and technology ambitions? And can the knowledge acquired by a visiting scientist be easily used to further a country’s ambitions? Drawing on literature from the field of science and technology studies, this article discusses the key issues that should be considered in evaluating this question in the Chinese context and the potential scientific, intelligence, and policy implications of knowledge transfer as it relates to the TTP.

While the effects of climate change will impact most Americans, they will likely have a disproportionate influence on the socioeconomic well-being of marginalized communities. Few researchers, however, have investigated public support for policies aimed at ameliorating climate-related disparities. Fewer still have considered how political and (critically) pre-political psychological dispositions might shape environmental justice concern (EJC) and subsequently influence policy support—both of which, I argue, could present roadblocks for effective climate communication and policy action. In this registered report, I (1) propose and validate a new measure of EJC, (2) explore its political correlates and pre-political antecedents, and (3) test for a link between EJC and policy support. In addition to psychometrically validating the EJC scale, I find that pre-political value orientations are associated with EJC, which, in turn, mediates the effects of pre-political values on taking action to mitigate the unequal effects of climate change.

Pre-registration has become an increasingly popular proposal to address concerns regarding questionable research practices. Yet preregistration does not necessarily solve these problems. It also causes additional problems, including raising costs for more junior and less resourced scholars. In addition, pre-registration restricts creativity and diminishes the broader scientific enterprise. In this way, pre-registration neither solves the problems it is intended to address, nor does it come without costs. Pre-registration is neither necessary nor sufficient for producing novel or ethical work. In short, pre-registration represents a form of virtue signaling that is more performative than actual.

This study tests two sets of competing hypotheses about the relationship between trait reactivity to positive and negative stimuli (i.e., motivational reactivity), moral stances on social principles (i.e., social morality), and political ideology. The classic view contends that a specific political ideology or social morality results from a specific motivational reactivity pattern, whereas the dynamic coordination account suggests that trait motivational reactivity modulates an individual’s political ideology and social morality as a result of the majority political beliefs in their immediate social context. A survey using subjects recruited from a liberal-leaning social context was conducted to test these hypotheses. Results support the dynamic coordination account. Reactivity to negativity (indexed by defensive system activation scores) is associated with the adoption of the dominant social morality and political ideology. Reactivity to positivity (indexed by appetitive system activation scores) is associated with the adoption of nondominant social moral and political stances.

Recent research contends that the behavioral immune system, operating largely outside conscious awareness, motivates individuals to exhibit higher levels of prejudice toward unfamiliar out-groups. This research finds that individual variance in disgust sensitivity correlates with support for political policies that facilitate the avoidance of out-groups. We were interested in developing less intrusive indicators of disgust sensitivity via olfactory measures (i.e., ratings of disgusting odors) and behavioral measures (e.g., willingness to touch disgusting objects) and studying the association between measures of disgust sensitivity and in-group bias among children and adults. We submitted a registered report to conduct this research and received an in-principle acceptance. Unfortunately, unforeseen events impaired our data collection, leaving us with a limited sample (nchildren = 32, nadults = 29) and reducing our ability to draw reliable conclusions from our results. In this essay, we describe our motivation and plan of research, the events that made completing the research impossible, and our preliminary results. In doing so, we hope to offer support for studying the effects of the behavioral immune system, even in ways that we did not originally plan. We conclude with a reflection on the value of registered reports for advancing science.

In the past decade, international actors have launched “brain projects” or “brain initiatives.” One of the emerging technologies enabled by these publicly funded programs is brain-computer interfaces (BCIs), which are devices that allow communication between the brain and external devices like a prosthetic arm or a keyboard. BCIs are poised to have significant impacts on public health, society, and national security. This research presents the first analytical framework that attempts to predict the dissemination of neurotechnologies to both the commercial and military sectors in the United States and China. While China started its project later with less funding, we find that it has other advantages that make earlier adoption more likely. We also articulate national security risks implicit in later adoption, including the inability to set international ethical and legal norms for BCI use, especially in wartime operating environments, and data privacy risks for citizens who use technology developed by foreign actors.

How might a liberal democratic community best regulate human genetic engineering? Relevant debates widely deploy the usually undefined term “human dignity.” Its indeterminacy in meaning and use renders it useless as a guiding principle. In this article, I reject the human genome as somehow invested with a moral status, a position I call “genetic essentialism.” I explain why a critique of genetic essentialism is not a strawman and argue against defining human rights in terms of genetic essentialism. As an alternative, I propose dignity as the decisional autonomy of future persons, held in trust by the current generation. I show why a future person could be expected to have an interest in decisional autonomy and how popular deliberation, combined with expert medical and bioethical opinion, could generate principled agreement on how the decisional autonomy of future persons might be configured at the point of genetic engineering.

We introduce cognitive-affective maps (CAMs) as a novel tool to assess individual experiences and belief systems. CAMs were first presented by the cognitive scientist and philosopher Paul Thagard as a graphical representation of a mental network, visualizing attitudes, thoughts, and affective connotations toward the topic of interest. While CAMs were originally used primarily to visualize existing data, the recent release of the new software tool Valence has facilitated the applicability of CAMs for empirical data collection. In this article, we explain the concept and the theoretical background of CAMs. We exemplify how CAMs can be applied in research practice, including different options for analysis. We propose CAMs as a user-friendly and versatile methodological bridge between qualitative and quantitative research approaches and encourage incorporating the method into studies to access and visualize human attitudes and experience.

This preregistered study uses a combination of physiological measures to explore both the activation and reduction components of cognitive dissonance theory. More precisely, we use skin conductance to identify dissonance arousal, a short-term affective response to counter-attitudinal stimuli, and then use heart rate variability to measure dissonance reduction, which reflects longer-term patterns of emotional regulation and information processing. Our preliminary tests find weak evidence of dissonance arousal and no evidence of dissonance reduction using this physiological approach. We consequently reconsider (albeit optimistically) the use of physiology in future work on cognitive dissonance. We also discuss the implications of our findings for selective exposure and motivated reasoning.

Several empirical studies have linked political candidates’ electoral success to their physical appearance. We reexamine the effects of candidates’ physical attractiveness by taking into account emotional facial expressions as measured by automated facial recognition software. The analysis is based on an observational case study of candidate characteristics in the 2017 German federal election. Using hierarchical regression modeling and controlling for candidates’ displays of happiness, consistent effects of physical attractiveness remain. The results suggest that a potential interaction effect between displays of happiness and attractiveness positively affects vote shares. The study emphasizes the importance of considering emotional expressions when analyzing the impact of candidate appearance on electoral outcomes.

The U.S. public’s trust in scientists reached a new high in 2019 despite the collision of science and politics witnessed by the country. This study examines the cross-decade shift in public trust in scientists by analyzing General Social Survey data (1978–2018) using interpretable machine learning algorithms. The results suggest a polarization of public trust as political ideology made an increasingly important contribution to predicting trust over time. Compared with previous decades, many conservatives started to lose trust in scientists completely between 2008 and 2018. Although the marginal importance of political ideology in contributing to trust was greater than that of party identification, it was secondary to that of education and race in 2018. We discuss the practical implications and lessons learned from using machine learning algorithms to examine public opinion trends.

Research finds that the perception that immigrants are culturally and economically threatening is associated with negative attitudes toward immigration. In a largely separate body of work, psychophysiological predispositions toward threat sensitivity are connected to a range of political attitudes, including immigration. This article draws together these two literatures, using a lab experiment to explore psychophysiological threat sensitivity and immigration attitudes in the United States. Respondents with higher threat sensitivity, as measured by skin conductance responses to threatening images, tend to be less supportive of immigration. This finding builds on our understanding of the sources of anti-immigrant attitudes.

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter’s standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter’s API version 2.