Prevalence, predictors and reasons for COVID-19 vaccine hesitancy: Results of a global online survey

Individual predictors of vaccine hesitancy in the Italian post COVID-19 pandemic era

A wide range of survey studies have explored vaccination hesitancy/resistance during the COVID-19 pandemic and provided evidence that this can be explained by several individual variables from the ideological, clinical, and socio-affective domain. However, evidence about which individual variables predict vaccine hesitancy in the post-pandemic state of COVID-19 is meager. We administered a battery of questionnaires to a group of 120 Italian participants with high and low scores on the adult vaccine hesitancy scale (aVHS) to investigate the predictive role of ideological (i.e. political orientation), clinical (i.e. anxiety, interoceptive accuracy), and socio-affective (i.e. alexithymia, disgust sensitivity/propensity, empathy) variables on vaccine hesitancy/resistance. This study provides evidence that lower interoceptive awareness and cognitive empathy are predictors of a greater hesitancy to get vaccinated in the post-pandemic COVID-19 state.

Access to healthcare services during the COVID-19 pandemic: a cross-sectional analysis of income and user-access across 16 economically diverse countries

BACKGROUND

National health systems have different strengths and resilience levels. During the COVID-19 pandemic, resources often had to be reallocated and this impacted the availability of healthcare services in many countries. To date there have been few quantitative contemporary studies of inequalities in access to healthcare within and between countries. In this study, we aim to compare inequality within and between 16 economically diverse countries.

METHODS

Online surveys were conducted on 22 150 adults in 16 countries across six continents in 2022. Quota sampling and post-stratification weighting was used to obtain an age, gender, geographically, and educationally representative sample. The study assesses the differences in challenges in access to healthcare during the pandemic (for GP, surgical/clinical and digital GP services) using country-specific expanded health-needs-adjusted Erreygers' concentration indices and compares these values between countries using a Spearman's rank correlation coefficient.

RESULTS

Results show wide variation in income-related challenges in access within countries for different types of care. For example, Erreygers' concentration index for digital services in Colombia exhibited highly regressive inequality at 0·17, compared to Japan with an index of -0·15. Inequalities between countries were also evident, with Spearman rank coefficients of -0·69 and -0·65 (p-values of 0·003 and 0·006) for digital and surgical access, indicating that lower income countries had greater inequality in healthcare access challenges.

CONCLUSION

During the pandemic, inequalities in challenges to accessing healthcare were greatest in low and middle-income countries. Digital technologies offer a reasonable means to address some of this inequality if adequate support is provided and accessible digital infrastructure exists.

Links between Vaccination Fear-, Anxiety-, Alexithymia-, and Type D Personality-Related Vaccination Decisions: A Network Analysis in a Multicultural Sample

This study examines the links between vaccination status, fear of vaccination (cognitive and somatic symptoms), anxiety, alexithymia, and type D personality (negative affect and social inhibition), to propose policies to increase vaccination rates. A sample of university students (n = 2535; mean age = 20.59, SD = 2.04; male: 26.75%, female: 73.25%) from Spain, Italy, Lebanon, Nigeria, Turkey, and Ukraine completed the Vaccination Fear Scale (VFS-6), the Generalised Anxiety Disorder scale (GAD-7), the Perth Alexithymia Questionnaire-Short Form (PAQ-S), the Type D Scale (DS14), and also a question on vaccination status. Correlation, regression, and network analyses were applied. Cognitive symptoms of fear of vaccination and negative affect were the most significant in the correlation and regression analyses. In the network analysis, negative affect showed the highest values in all centrality indices and positive relationships with other nodes. Vaccination status showed negative relationships with fear of vaccination, alexithymia, and social inhibition. The network structure is similar between the sexes but varies between cultures and sexes within cultures. The relationship between vaccination status and cognitive symptoms of fear of vaccination was the most consistent, allowing for interventions at this level to be advised across cultures. For more specific interventions, cultural context must be considered for optimal results.

A Theory and Evidence-Based Artificial Intelligence-Driven Motivational Digital Assistant to Decrease Vaccine Hesitancy: Intervention Development and Validation

Vaccine hesitancy is one of the top ten threats to global health. Artificial intelligence-driven chatbots and motivational interviewing skills show promise in addressing vaccine hesitancy. This study aimed to develop and validate an artificial intelligence-driven motivational digital assistant in decreasing COVID-19 vaccine hesitancy among Hong Kong adults. The intervention development and validation were guided by the Medical Research Council's framework with four major steps: logic model development based on theory and qualitative interviews (n = 15), digital assistant development, expert evaluation (n = 5), and a pilot test (n = 12). The Vaccine Hesitancy Matrix model and qualitative findings guided the development of the intervention logic model and content with five web-based modules. An artificial intelligence-driven chatbot tailored to each module was embedded in the website to motivate vaccination intention using motivational interviewing skills. The content validity index from expert evaluation was 0.85. The pilot test showed significant improvements in vaccine-related health literacy (p = 0.021) and vaccine confidence (p = 0.027). This digital assistant is effective in improving COVID-19 vaccine literacy and confidence through valid educational content and motivational conversations. The intervention is ready for testing in a randomized controlled trial and has high potential to be a useful toolkit for addressing ambivalence and facilitating informed decision making regarding vaccination.

Dataset on a reliability generalization meta-analysis of the Oxford COVID-19 vaccine hesitancy scale

The Oxford COVID-19 Vaccine Hesitancy Scale is a 7-item psychometric scale developed by Freeman and colleagues a year after detecting the first case of the disease in 2019. The scale assesses people's thoughts, feelings, and behavior toward COVID-19 vaccines. A comprehensive search of major electronic databases, including Scopus, Clarivate Analytics, and PubMed, was conducted to extract eligible articles for inclusion in this meta-analysis. This paper reports information on data collected for a reliability generalization meta-analysis of the Oxford COVID-19 Vaccine Hesitancy Scale. The dataset incorporates information on the average reliability of the scale as measured with Cronbach's alpha in 20 studies included in the meta-analysis. Several benefits can be derived from the dataset. In particular, the research community would find this dataset beneficial as it can enhance their understanding of the health challenges of COVID-19, helping them come up with better solutions to eradicate the disease.