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BackgroundThe hesitancy in taking the COVID-19 vaccine is a global challenge. The need to identify predictors of COVID-19 vaccine reluctance is critical. Our objectives were to evaluate sociodemographic, psychological, and behavioral factors, as well as attitudes and beliefs that influence COVID-19 vaccination hesitancy in the general population of Italy.MethodsA total of 2,015 people were assessed in two waves (March, April and May, 2021). Participants were divided into three groups: (1) individuals who accepted the vaccination (“accepters”); (2) individuals who refused the vaccination (“rejecters”); and (3) individuals who were uncertain about their attitudes toward the vaccination (“fence sitters”). Group comparisons were performed using ANOVA, the Kruskal-Wallis test and chi-square tests. The strength of the association between the groups and the participants' characteristics was analyzed using a series of multinomial logistic regression models with bootstrap internal validation (one for each factor).ResultsThe “fence sitters” group, when compared to the others, included individuals of younger age, lower educational level, and worsening economic situation in the previous 3 months. After controlling for sociodemographic factors, the following features emerged as the main risk factors for being “fence sitters” (compared with vaccine “accepters”): reporting lower levels of protective behaviors, trust in institutions and informational sources, frequency of use of informational sources, agreement with restrictions and higher conspirative mentality. Higher levels of COVID-19 perceived risk, trust in institutions and informational sources, frequency of use of informational sources, agreement with restrictions and protective behaviors were associated with a higher likelihood of becoming “fence sitters” rather than vaccine “rejecters.”ConclusionsThe “fence sitters” profile revealed by this study is intriguing and should be the focus of public programmes aimed at improving adherence to the COVID-19 vaccination campaign.

In two experimental studies, we tested the effect of COVID‐19 vaccine scarcity on vaccine hesitancy. Based on extensive scarcity literature, we initially predicted that high (vs. low) scarcity would increase demand for vaccines, operationalized as one's willingness to receive a vaccine. Contrary to this prediction, Study 1 showed that scarcity of vaccines reduced participants’ sense of priority which, in turn, also reduced their vaccination intentions. Trust in doctors moderated the effect of perceived vaccination priority on vaccination intentions such that for individuals with high trust in doctors, reduced perceived priority did not reduce their vaccination intentions as much. Study 2 replicated these effects with a more general population sample, which included at‐risk individuals for COVID‐19 complications. At‐risk participants (vs. low‐risk) had higher perceived vaccination priority, but describing vaccine doses as scarce reduced vaccination intentions similarly across both groups. Moreover, Study 2 demonstrated that compassion for others is a boundary condition of the effect of vaccine scarcity on vaccination intentions. For participants with high compassion, scarcity reduces willingness to receive a vaccine; for participants with low compassion, scarcity increases their willingness to be vaccinated. Our results suggest that health policymakers need to deemphasize the scarcity of vaccines to increase vaccine acceptance.

COVID-19 pandemic had a negative impact on the mental health and well-being (WB) of citizens. This cross-sectional study included 4 waves of data collection aimed at identifying profiles of individuals with different levels of WB. The study included a representative stratified sample of 10,013 respondents in Italy. The WHO 5-item well-being scale (WHO-5) was used for the assessment of WB. Different supervised machine learning approaches (multinomial logistic regression, partial least-square discriminant analysis—PLS-DA—, classification tree—CT—) were applied to identify individual characteristics with different WB scores, first in waves 1–2 and, subsequently, in waves 3 and 4. Forty-one percent of participants reported “Good WB”, 30% “Poor WB”, and 28% “Depression”. Findings carried out using multinomial logistic regression show that Resilience was the most important variable able for discriminating the WB across all waves. Through the PLS-DA, Increased Unhealthy Behaviours proved to be the more important feature in the first two waves, while Financial Situation gained most relevance in the last two. COVID-19 Perceived Risk was relevant, but less than the other variables, across all waves. Interestingly, using the CT we were able to establish a cut-off for Resilience (equal to 4.5) that discriminated good WB with a probability of 65% in wave 4. Concluding, we found that COVID-19 had negative implications for WB. Governments should support evidence-based strategies considering factors that influence WB (i.e., Resilience, Perceived Risk, Healthy Behaviours, and Financial Situation).