Search

This study explores the relation between risk of job automation and participation in adult education and training (AET) and examines variation in that relation across welfare regimes distinguishing between situational and institutional barriers. Using microdata of PIAAC, we analyze participation in formal or nonformal AET for job-related reasons in relation to the risk of automation of the respondents' occupation after controlling for main sociodemographic characteristics. Logistic regression models are run on respondents from 14 European countries representing different welfare regimes: Denmark, Norway, and Sweden (Scandinavian countries); Italy, Greece, and Spain (Southern European); Czech Republic, Slovakia, and Poland (Central and Eastern Europe), Belgium, France, and Germany (Continental); and United Kingdom and Ireland (Anglo-Saxon countries). Our findings confirm that workers in occupations at high risk of automation were found to be consistently less likely to participate in job-related AET, quite irrespective of welfare regime. [The paper was presented at XIII Conferenza Espanet Italia--Il welfare state di fronte alle sfide globali (Venezia, 17 September 2020).]

This study aims to identify the literacy skills of individuals whose highest level of education was in the field 'teacher training and educational sciences'. The study sample comprised 10,618 individuals in the field of teacher training and educational sciences, selected from 31 countries (participating in the International Adult Skills Assessment Programme during the 2014-2015 survey) using a multi-stage sampling method. The study employed multi-level latent class analysis and three-step analysis in order to determine both the number of multi-level latent classes of educators' literacy scores as well as the selected independent variables' success in predicting those latent classes. The analysis revealed that educators in Germany constituted the group with the highest literacy skills while educators from Singapore comprised the group with the lowest literacy skills. [This study was presented at the 9th International Congress of Educational Research. Ordu University, Ordu, Turkey.]

Evidence is accumulating of the negative impact of the COVID‐19 pandemic and related public health measures on mental health. In this emergent field, there has been little research into the role of risk perception on depressive symptoms and the contribution of health‐care resources to model risk perception and mental health. The aim of this paper is to describe the relationship between individual‐level perception of risk and depression, controlling for a set of confounders and for country‐level heterogeneity. A cross‐sectional and observational online survey was conducted using a non‐probability snowball sampling technique. We use data on 11,340 respondents, living in six European countries (Italy, Sweden, United Kingdom, France, Poland, Czech Republic) who completed survey questionnaires during the first months of the pandemic. We used a fixed‐effect approach, which included individual and macro‐level variables. The findings suggest that a high proportion of people suffering from depression and heightened risk perception is positively associated with reporting depressive symptoms, even if this relationship varies significantly between countries. Moreover, the association is moderated by contextual factors including health‐care expenditure as a percentage of Gross Domestic Product, hospital beds for acute care, and number of medical specialists per head of population. Investment in health care offers a concrete means of protecting the mental health of a population living under pandemic restrictions. [ABSTRACT FROM AUTHOR]