Intentions to be Vaccinated Against COVID-19:The Role of Prosociality and Conspiracy Beliefs across 20 Countries

Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to encourage vaccine uptake.</p

Using Machine Learning to Identify Important Predictors of COVID-19 Infection Prevention Behaviors During the Early Phase of the Pandemic

Before vaccines for COVID-19 became available, a set of infection prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection prevention behavior in 56,072 participants across 28 countries, administered in March-May 2020. The machine- learning model predicted 52% of the variance in infection prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual- level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically-derived predictors were relatively unimportant

MIGRATION OF POLISH PROFESSIONAL (HIGHLY SKILLED) MEN AND WOMEN: DEPARTURES AND RETURNS

The aim of this study was to explore issues related to emigration of Polish Professional and their return to Poland. The reasons, perceived advantages and disadvantages of each departure and return, as well as further life plans were examined. The research was carried out using semi- structured interviews, the contents of which were then subject to qualitative analysis. The results indicated the desire for personal and professional development as major goals of emigration. Reasons for returning to Poland included: a desire to function in the circle of close friends and family, to prevent child marginalization among peers in the country of migration and to maintain ties with Poland. The professionals researched during their stay abroad were positive about their decision to migrate. Return to Poland is perceived by them as a challenge because of the difficulty of finding employment in line with their very specialized professional competence gained during their time abroad. However, the professionals studied after returning to Poland were mostly well adapted to this situation