People do change their beliefs about conspiracy theories-but not often.

Recent research has produced a significant body of knowledge about the antecedents and consequences of individual differences in belief in conspiracy theories. What is less clear, however, is the extent to which individuals' beliefs in conspiracy theories vary over time (i.e., within-person variation). In this descriptive and exploratory study, we therefore aimed to describe within-person variability in belief in conspiracy theories. We collected data from 498 Australians and New Zealanders using an online longitudinal survey, with data collected at monthly intervals over 6 months (March to September 2021). Our measure of conspiracy theories included items describing ten conspiracy theories with responses on a 5-point Likert scale. While there was substantial between-person variance, there was much less within-person variance (intraclass r = 0.91). This suggests that beliefs in conspiracy theories were highly stable in our sample. This stability implies that longitudinal studies testing hypotheses about the causes and consequences of belief in conspiracy theories may require large samples of participants and time points to achieve adequate power. It also implies that explanations of belief in conspiracy theories need to accommodate the observation that beliefs in such theories vary much more between people than within people.

The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment.

Interest in the psychology of misinformation has exploded in recent years. Despite ample research, to date there is no validated framework to measure misinformation susceptibility. Therefore, we introduce Verification done, a nuanced interpretation schema and assessment tool that simultaneously considers Veracity discernment, and its distinct, measurable abilities (real/fake news detection), and biases (distrust/naïvité-negative/positive judgment bias). We then conduct three studies with seven independent samples (Ntotal = 8504) to show how to develop, validate, and apply the Misinformation Susceptibility Test (MIST). In Study 1 (N = 409) we use a neural network language model to generate items, and use three psychometric methods-factor analysis, item response theory, and exploratory graph analysis-to create the MIST-20 (20 items; completion time < 2 minutes), the MIST-16 (16 items; < 2 minutes), and the MIST-8 (8 items; < 1 minute). In Study 2 (N = 7674) we confirm the internal and predictive validity of the MIST in five national quota samples (US, UK), across 2 years, from three different sampling platforms-Respondi, CloudResearch, and Prolific. We also explore the MIST's nomological net and generate age-, region-, and country-specific norm tables. In Study 3 (N = 421) we demonstrate how the MIST-in conjunction with Verification done-can provide novel insights on existing psychological interventions, thereby advancing theory development. Finally, we outline the versatile implementations of the MIST as a screening tool, covariate, and intervention evaluation framework. As all methods are transparently reported and detailed, this work will allow other researchers to create similar scales or adapt them for any population of interest.

Why are beliefs in different conspiracy theories positively correlated across individuals? Testing monological network versus unidimensional factor model explanations.

A substantial minority of the public express belief in conspiracy theories. A robust phenomenon in this area is that people who believe one conspiracy theory are more likely to believe in others. But the reason for this "positive manifold" of belief in conspiracy theories is unclear. One possibility is that a single underlying latent factor (e.g. "conspiracism") causes variation in belief in specific conspiracy theories. Another possibility is that beliefs in various conspiracy theories support one another in a mutually reinforcing network of beliefs (the "monological belief system" theory). While the monological theory has been influential in the literature, the fact that it can be operationalised as a statistical network model has not previously been recognised. In this study, we therefore tested both the unidimensional factor model and a network model. Participants were 1553 American adults recruited via Prolific. Belief in conspiracies was measured using an adapted version of the Belief in Conspiracy Theories Inventory. The fit of the two competing models was evaluated both by using van Bork et al.'s (Psychometrika, 83, 2018, 443, Multivariate Behavioral Research, 56, 2019, 175) method for testing network versus unidimensional factor models, as well as by evaluating goodness of fit to the sample covariance matrix. In both cases, evaluation of fit according to our pre-registered inferential criteria favoured the network model.

Communicating expert consensus increases personal support for COVID-19 mitigation policies.

The Gateway Belief Model (GBM) places perception of a scientific consensus as a key "gateway cognition" with cascading effects on personal beliefs, concern, and ultimately support for public policies. However, few studies seeking to evaluate and extend the model have followed the specification and design of the GBM as originally outlined. We present a more complete test of the theoretical model in a novel domain: the COVID-19 pandemic. In a large multi-country correlational study (N = 7,206) we report that, as hypothesized by the model, perceptions of scientific consensus regarding the threat of COVID-19 predict personal attitudes toward threat and worry over the virus, which are in turn positively associated with support for mitigation policies. We also find causal support for the model in a large pre-registered survey experiment (N = 1,856): experimentally induced increases in perceived consensus have an indirect effect on changes in policy support mediated via changes in personal agreement with the consensus. Implications for the role of expert consensus in science communication are discussed.

Transparent communication of evidence does not undermine public trust in evidence.

Does clear and transparent communication of risks, benefits, and uncertainties increase or undermine public trust in scientific information that people use to guide their decision-making? We examined the impact of reframing messages written in traditional persuasive style to align instead with recent "evidence communication" principles, aiming to inform decision-making: communicating a balance of risks and benefits, disclosing uncertainties and evidence quality, and prebunking misperceptions. In two pre-registered experiments, UK participants read either a persuasive message or a balanced and informative message adhering to evidence communication recommendations about COVID-19 vaccines (Study 1) or nuclear power plants (Study 2). We find that balanced messages are either perceived as trustworthy as persuasive messages (Study 1), or more so (Study 2). However, we note a moderating role of prior beliefs such that balanced messages were consistently perceived as more trustworthy among those with negative or neutral prior beliefs about the message content. We furthermore note that participants who had read the persuasive message on nuclear power plants voiced significantly stronger support for nuclear power than those who had read the balanced message, despite rating the information as less trustworthy. There was no difference in vaccination intentions between groups reading the different vaccine messages.

Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys.

OBJECTIVE: Describe demographical, social and psychological correlates of willingness to receive a COVID-19 vaccine. SETTING: Series of online surveys undertaken between March and October 2020. PARTICIPANTS: A total of 25 separate national samples (matched to country population by age and sex) in 12 different countries were recruited through online panel providers (n=25 334). PRIMARY OUTCOME MEASURES: Reported willingness to receive a COVID-19 vaccination. RESULTS: Reported willingness to receive a vaccine varied widely across samples, ranging from 63% to 88%. Multivariate logistic regression analyses reveal sex (female OR=0.59, 95% CI 0.55 to 0.64), trust in medical and scientific experts (OR=1.28, 95% CI 1.22 to 1.34) and worry about the COVID-19 virus (OR=1.47, 95% CI 1.41 to 1.53) as the strongest correlates of stated vaccine acceptance considering pooled data and the most consistent correlates across countries. In a subset of UK samples, we show that these effects are robust after controlling for attitudes towards vaccination in general. CONCLUSIONS: Our results indicate that the burden of trust largely rests on the shoulders of the scientific and medical community, with implications for how future COVID-19 vaccination information should be communicated to maximise uptake.

Effect of Information about COVID-19 Vaccine Effectiveness and Side Effects on Behavioural Intentions: Two Online Experiments.

The success of mass COVID-19 vaccination campaigns rests on widespread uptake. However, although vaccinations provide good protection, they do not offer full immunity and while they likely reduce transmission of the virus to others, the extent of this remains uncertain. This produces a dilemma for communicators who wish to be transparent about benefits and harms and encourage continued caution in vaccinated individuals but not undermine confidence in an important public health measure. In two large pre-registered experimental studies on quota-sampled UK public participants we investigate the effects of providing transparent communication-including uncertainty-about vaccination effectiveness on decision-making. In Study 1 (n = 2097) we report that detailed information about COVID-19 vaccines, including results of clinical trials, does not have a significant impact on beliefs about the efficacy of such vaccines, concerns over side effects, or intentions to receive a vaccine. Study 2 (n = 2217) addressed concerns that highlighting the need to maintain protective behaviours (e.g., social distancing) post-vaccination may lower perceptions of vaccine efficacy and willingness to receive a vaccine. We do not find evidence of this: transparent messages did not significantly reduce perceptions of vaccine efficacy, and in some cases increased perceptions of efficacy. We again report no main effect of messages on intentions to receive a vaccine. The results of both studies suggest that transparently informing people of the limitations of vaccinations does not reduce intentions to be vaccinated but neither does it increase intentions to engage in protective behaviours post-vaccination.

Associations between conspiracism and the rejection of scientific innovations.

Public opinion regarding scientific developments such as genetically modified food can be mixed. We suggest such science-based technological innovations are rejected by some because they are perceived to be advanced as part of a conspiracy. In nationally representative samples (Australia n = 1011; New Zealand n = 754), we report the associations between five conspiracism facets and anti-science attitudes. Results indicate broad public opposition to genetically modified food and use of nuclear power, but more acceptance of renewable power, potable recycled water, 5G networks, and childhood vaccinations. There were small to moderate associations between the rejection of scientific innovations and conspiracism. Multivariate models estimating unique associations of conspiracism facets with anti-science attitudes suggested several novel and important relationships, particularly for childhood vaccination, genetically modified food, and 5G networks. We discuss the importance of examining factors such as conspiracism in understanding what may motivate and sustain rejection of scientific evidence-based claims about socially contentious technological innovations.

Changes in perceived scientific consensus shift beliefs about climate change and GM food safety.

Despite an overwhelming scientific consensus, a sizable minority of people doubt that human activity is causing climate change. Communicating the existence of a scientific consensus has been suggested as a way to correct individuals' misperceptions about human-caused climate change and other scientific issues, though empirical support is mixed. We report an experiment in which psychology students were presented with consensus information about two issues, and subsequently reported their perception of the level of consensus and extent of their endorsement of those issues. We find that messages about scientific consensus on the reality of anthropogenic climate change and the safety of genetically modified food shift perceptions of scientific consensus. Using mediation models we also show that, for both these issues, high consensus messages also increase reported personal agreement with the scientific consensus, mediated by changes in perceptions of a scientific consensus. This confirms the role of perceived consensus in informing personal beliefs about climate change, though results indicate the impact of single, one-off messages may be limited.

Pharmacological Preconditioning with GYKI 52466: A Prophylactic Approach to Neuroprotection.

Some toxins and drugs can trigger lasting neuroprotective mechanisms that enable neurons to resist a subsequent severe insult. This "pharmacological preconditioning" has far-reaching implications for conditions in which blood flow to the brain is interrupted. We have previously shown that in vitro preconditioning with the AMPA receptor antagonist GYKI 52466 induces tolerance to kainic acid (KA) toxicity in hippocampus. This effect persists well after washout of the drug and may be mediated via inverse agonism of G-protein coupled receptors (GPCRs). Given the amplifying nature of metabotropic modulation, we hypothesized that GYKI 52466 may be effective in reducing seizure severity at doses well below those normally associated with adverse side effects. Here we report that pharmacological preconditioning with low-dose GYKI imparts a significant protection against KA-induced seizures in vivo. GYKI (3 mg/kg, s.c.), 90-180 min prior to high-dose KA, markedly reduced seizure scores, virtually abolished all level 3 and level 4 seizures, and completely suppressed KA-induced hippocampal c-FOS expression. In addition, preconditioned animals exhibited significant reductions in high frequency/high amplitude spiking and ECoG power in the delta, theta, alpha, and beta bands during KA. Adverse behaviors often associated with higher doses of GYKI were not evident during preconditioning. The fact that GYKI is effective at doses well-below, and at pre-administration intervals well-beyond previous studies, suggests that a classical blockade of ionotropic AMPA receptors does not underlie anticonvulsant effects. Low-dose GYKI preconditioning may represent a novel, prophylactic strategy for neuroprotection in a field almost completely devoid of effective pharmaceuticals.