Our aim was to estimate provisional willingness to receive a coronavirus 2019 (COVID-19) vaccine, identify predictive socio-demographic factors, and, principally, determine potential causes in order to guide information provision.

A non-probability online survey was conducted (24th September−17th October 2020) with 5,114 UK adults, quota sampled to match the population for age, gender, ethnicity, income, and region. The Oxford COVID-19 vaccine hesitancy scale assessed intent to take an approved vaccine. Structural equation modelling estimated explanatory factor relationships.

71.7% (n=3,667) were willing to be vaccinated, 16.6% (n=849) were very unsure, and 11.7% (n=598) were strongly hesitant. An excellent model fit (RMSEA=0.05/CFI=0.97/TLI=0.97), explaining 86% of variance in hesitancy, was provided by beliefs about the collective importance, efficacy, side-effects, and speed of development of a COVID-19 vaccine. A second model, with reasonable fit (RMSEA=0.03/CFI=0.93/TLI=0.92), explaining 32% of variance, highlighted two higher-order explanatory factors: ‘excessive mistrust’ (r=0.51), including conspiracy beliefs, negative views of doctors, and need for chaos, and ‘positive healthcare experiences’ (r=−0.48), including supportive doctor interactions and good NHS care. Hesitancy was associated with younger age, female gender, lower income, and ethnicity, but socio-demographic information explained little variance (9.8%). Hesitancy was associated with lower adherence to social distancing guidelines.

COVID-19 vaccine hesitancy is relatively evenly spread across the population. Willingness to take a vaccine is closely bound to recognition of the collective importance. Vaccine public information that highlights prosocial benefits may be especially effective. Factors such as conspiracy beliefs that foster mistrust and erode social cohesion will lower vaccine up-take.

Freeman et al. (2020a, Psychological Medicine, 21, 1–13) argue that there is widespread support for coronavirus conspiracy theories in England. We hypothesise that their estimates of prevalence are inflated due to a flawed research design. When asking respondents to their survey to agree or disagree with pro-conspiracy statements, they used a biased set of response options: four agree options and only one disagree option (and no ‘don't know’ option). We also hypothesise that due to these flawed measures, the Freeman et al. approach under-estimates the strength of the correlation between conspiracy beliefs and compliance. Finally, we hypothesise that, due to reliance on bivariate correlations, Freeman et al. over-estimate the causal connection between conspiracy beliefs and compliance.

In a pre-registered study, we conduct an experiment embedded in a survey of a representative sample of 2057 adults in England (fieldwork: 16−19 July 2020).

Measured using our advocated ‘best practice’ approach (balanced response options, with a don't know option), prevalence of support for coronavirus conspiracies is only around five-eighths (62.3%) of that indicated by the Freeman et al. approach. We report mixed results on our correlation and causation hypotheses.

To avoid over-estimating prevalence of support for coronavirus conspiracies, we advocate using a balanced rather than imbalanced set of response options, and including a don't know option.

An invisible threat has visibly altered the world. Governments and key institutions have had to implement decisive responses to the danger posed by the coronavirus pandemic. Imposed change will increase the likelihood that alternative explanations take hold. In a proportion of the general population there may be strong scepticism, fear of being misled, and false conspiracy theories. Our objectives were to estimate the prevalence of conspiracy thinking about the pandemic and test associations with reduced adherence to government guidelines.

A non-probability online survey with 2501 adults in England, quota sampled to match the population for age, gender, income, and region.

Approximately 50% of this population showed little evidence of conspiracy thinking, 25% showed a degree of endorsement, 15% showed a consistent pattern of endorsement, and 10% had very high levels of endorsement. Higher levels of coronavirus conspiracy thinking were associated with less adherence to all government guidelines and less willingness to take diagnostic or antibody tests or to be vaccinated. Such ideas were also associated with paranoia, general vaccination conspiracy beliefs, climate change conspiracy belief, a conspiracy mentality, and distrust in institutions and professions. Holding coronavirus conspiracy beliefs was also associated with being more likely to share opinions.

In England there is appreciable endorsement of conspiracy beliefs about coronavirus. Such ideas do not appear confined to the fringes. The conspiracy beliefs connect to other forms of mistrust and are associated with less compliance with government guidelines and greater unwillingness to take up future tests and treatment.

To explore the role of psychiatric admission, diagnosis and reported unfair treatment in the relationship between ethnicity and mistrust of mental health services.

The Mental Illness-Related Investigations on Discrimination (MIRIAD) study was a cross-sectional study of 202 individuals using secondary mental health services in South London. Two structural equation models were estimated, one using Admission (whether admitted to hospital for psychiatric treatment in the past 5 years) and one using involuntary admission to hospital in the past 5 years.

Increased mistrust was directly associated with the latent variable ‘unfair treatment by mental health services and staff’ and with Black or mixed ethnicity in both models. Those with a diagnosis of schizophrenia spectrum (as compared to depression and bipolar disorder) had a lower average score on the latent variable, suggesting that on average they reported less unfair treatment. We found evidence of increased reporting of unfair treatment by those who had an admission in the past 5 years, had experienced involuntary admission, and for people of Black of mixed Black and White ethnicity.

Neither prevalence of schizophrenia spectrum nor rates of hospital admission explained the greater mistrust of mental health services found among people of Black and mixed Black and White ethnicity compared with White ethnicity. Rather, people of Black and mixed Black and white ethnicity may be more likely to experience unfair treatment, generating mistrust; furthermore, this group is more likely to express mistrust even after accounting for reporting of unfair treatment by mental health services and staff.