Many school-age pupils are undecided about their future vocation. This often stems from a lack of occupational information or lack of vocationally related experience. The goal of this study was to develop and evaluate an intervention focused on the possibility of changing vocational interests through the simulation of vocational activities. The sample consisted of 250 pupils who were finishing primary school. The intervention was constructed for practical and artistic interests and consisted of workbooks that aim to simulate these vocational activities. MANCOVA showed no effect in the change of vocational interests among the pupils. An alternative idea of intervention in the form of virtual reality simulations is also presented.

Background: Previous research on the perceived causes of poverty has been carried out in the field of sociology (Strapcová, 2005) as well as social psychology (Nasser & Abouchedid, 2001). This research has looked at individuals' perceptions of the causes of poverty and the effect of various sociodemographic variables such as social class (Kluegel & Smith, 1981), income (Lever & Trejo, 2004), subjective assessment of one's economic situation (Strapcová, 2005), gender (Bullock, 1999), age (Niemelä, 2008), education (Hunt, 1996) and employment (Strapcová, 2005). The majority of these studies have been conducted on people who have not directly experienced poverty such as university students (Cozzarelli et al., 2001), middle-class people (Kluegel & Smith, 1981) and social workers (Bullock, 2004). Therefore, there have only been a few studies done on how poor people perceive the causes of poverty (Bullock, 1999; Davids & Gouws, 2013; Morçöl, 1997). Research goal: The present study has two objectives. The first one was to determine whether there are statistically significant differences in the individualistic, structural and fatalistic perceived causes of poverty between the objectively poor and objectively non-poor as well as between the subjectively poor and subjectively non-poor. Secondly, it was to identify the predictors of the individualistic, structural and fatalistic perceived causes of poverty among selected variables including gender, age, marital status, employment status, education, objective poverty and subjective poverty. It was hypothesized that the objectively poor would prefer less individualistic and more structural as well as fatalistic perceived causes of poverty in comparison with the objectively non-poor. It was also hypothesized that the subjectively poor in comparison with the subjectively non-poor would prefer less individualistic and more structural as well as fatalistic perceived causes of poverty. In addition, it was assumed that sociodemographic variables such as objective poverty, subjective poverty, gender, age, marital status, employment status and education would be significant predictors of the structural, fatalistic and individualistic perceived causes of poverty. In particular, it was hypothesized that objective poverty, subjective poverty, gender, and age would be confirmed as positive predictors of structural and fatalistic perceived causes of poverty while marital status, employment status and education would be confirmed as negative predictors. Within the individualistic perceived causes of poverty, it was hypothesized that marital status, employment status and education would be significant positive predictors while objective poverty, subjective poverty, gender and age would be significant negative predictors. Method: The research sample consisted of 150 respondents (77 men and 73 women) aged between 19 and 64 years old (M = 36.67; SD = 13.23). In terms of education, 17 participants stated that primary school had been their highest level of education, 31 participants stated that they had left secondary school without A level exam, 46 participants had left with A level exam and 56 participants had a university degree (15 of them had a Bachelor's degree, 39 participants had a Master’s and 2 participants had a PhD). In terms of marital status, 73 participants were single, 8 cohabitated, 49 were married, 13 were divorced and 7 widowed. With regards to employment status, 79 participants were full-time employed, 11 worked part-time, 27 were unemployed, 7 were retired, 6 were on sick/disability leave invalid retirees and 20 respondents reported their employment status as “other“ (9 of them were self-employed, 9 were students and 2 were on maternity leave). The data were dichotomized into groups according to age (19-25, 26-45, and 46-64 years old), according to relationship status (those not in a relationship and those who are), groups with lower and higher educational attainment and groups of non-working and working participants. For the data collection, occasional sampling was conducted in seven charitable organizations in the regions of Prešov, Košice, and Banská Bystrica in Slovakia. In addition, voluntary response sampling was used through an online survey. In order to assess the perceived causes of poverty, the Attributions for Poverty questionnaire (Bullock et al., 2003) was used. The subjective assessment of poverty was measured by the question “In your economic situation, is it possible to make ends meet?” (Nygård et al., 2017). The equivalent disposable household income of each respondent was calculated as an indicator of objective poverty. The research data were analysed in the statistical program IBM SPSS Statistics. Both a Welch t-test and Mann-Whitney U test were used to verify the first goal of the study. For the second goal, a multiple hierarchical linear regression analysis stepwise method was used. Results: There were statistically significant differences found in the structural as well as fatalistic perceived causes of poverty between the objectively poor and objectively non-poor as well as between the subjectively poor and subjectively non-poor. The objectively poor and subjectively poor were found to have higher scores in both the structural and fatalistic perceived causes of poverty in comparison with the objectively non-poor and subjectively non-poor. There were no statistically significant differences found between the objectively poor and objectively non-poor nor between the subjectively poor and subjectively non-poor in the individualistic perceived causes of poverty. The results of the regression analysis showed that when the 9 predictors were inputted in three blocks (1. gender, age-3 groups, marital status, 2. education, employment status, 3. objective poverty, subjective poverty), none of them appeared to be significant in terms of the individualistic perceived causes of poverty. For the structural as well as fatalistic perceived causes of poverty only one of the input predictors was shown to be positively significant. Subjective poverty was found to explain 4.2% of the variance in structural and 8.3% in the fatalistic perceived causes of poverty. Conclusion: The findings provide insight into the widely up to now unexplored issue of perceived causes of poverty in Slovakia. Future research on the perceived causes of poverty among the poor could focus on self-assignment of the participant to either the group of the poor or non-poor, distinguish between one's own poverty and the poverty of others and include other variables such as ethnicity, religion, belief in a just world as well as life satisfaction.

The changes in people’s mental health have become one of the hot topics during the COVID-19 pandemic. Parents have been said to be among the most vulnerable groups in terms of the imposed anti-pandemic measures. The present paper analyzes the trends in mental health indicators in a sample of Slovak parents (N = 363) who participated in four waves of data collection over a year and a half of the COVID-19 pandemic. The mental health indicators were represented by general levels of depression and anxiety as well as COVID-related stress and anxiety. While there were only minor changes in depression and anxiety, the dynamic in COVID-related stress and especially anxiety was more noteworthy. Besides some exceptions, the results hold even after controlling for the socioeconomic situation. The gender differences in the mental health trends were found to be negligible. Overall, we observed no substantial deterioration in the mental health indicators across the four waves of the study.

Usually, parents and caregivers are the ones responsible for children's vaccination, their intention to vaccinate children depending on many factors. In a society where almost half of adults have refused to take a jab against COVID-19, it is important to know which factors increase or decrease the odds of a child getting vaccinated. In the present study, we examined parents’ reasons for/against children vaccination and predictors of this intention. We found that about 30% of parents intended to have their children vaccinated to protect the health of children and their close ones. On the other hand, parents who did not intend to have their children vaccinated were typically afraid of long-term consequences of vaccination and its side effects, with less than one fifth of them being skeptical about vaccination per se. Using logistic regression analyses, we found that a higher willingness to vaccinate was in male, older parents, and those with higher (socio)economic status. Parents with a higher adherence to restrictions, and higher trust in government and authorities were more likely to vaccinate their children. Moreover, parents who had themselves been vaccinated or were more positive towards vaccination in general were much more willing to vaccinate their children. On the contrary, belief in conspiracy theories decreased this intention 10-times. No other variables (e.g., demographic characteristics, mental health indicators, or direct experience with COVID-19) significantly predicted parents’ intention to vaccinate their children. The study offers several implications related to the complexity of factors which determine hesitant parents’ intention to vaccinate their children. We aimed to answer questions on how, when, and by whom parents should be approached to improve their awareness on vaccination decisions.

The study had two main goals: Firstly, the authors aimed to verify the validity and reliability of the Slovak adaptation of the Coronavirus Anxiety Scale (CAS). Secondly, the authors examined the associations between the CAS and mental health indicators – depression, insomnia and generalized anxiety disorder. The representative sample consisted of 1625 Slovak participants from the general population (793 men and 832 women, Mage = 42.77 ±12.84). The data were collected in October 2020. The data were analyzed using confirmatory factor analysis and multiple hierarchical regression analysis. The authors confirmed that the psychometric properties of the CAS were adequate. Furthermore, they identified predictors of depression (gender, income, change in economic situation, subjective poverty, CAS), generalized anxiety disorder (gender, age, change in economic situation, subjective poverty, CAS) and insomnia (change in economic situation, subjective poverty, CAS). The results may contribute to our understanding of the pandemic’s impact on mental health.