The objective of the study was to examine the effects of perceived stress on depression and subsequently to examine the effects of depression on alcohol use disorders. The data were obtained by an electronic questionnaire survey during the coronavirus disease 2019 (COVID-19) pandemic (n = 1523 Slovak university students). Descriptive, regression, and correlation analysis were used in the analytical processing, while the analyses included students’ scores in three diagnostic tools (Perceived Stress Scale (PSS), Patient Health Questionnaire for depression (PHQ 9), and Alcohol Use Disorders Identification Test (AUDIT)), as well as gender and income characteristics. The PSS identified an increased level of perceived stress in female students, while in contrast, the AUDIT showed an increased level of alcohol use disorders in male students. Differences in mental and behavioural disorders between the gender and income categories were significant in most of the analysed cases. In terms of gender-income characteristics, it was possible to confirm a significant positive effect of the PSS score on the PHQ 9 score, as well as a significant positive effect of the PHQ 9 score on the AUDIT score. As a result, efforts to reduce stress will be reflected in a reduction of depressive disorders as well as a reduction of excessive alcohol consumption among students.

Global trends indicate a systematic increase in the importance of tourism. From an economic point of view, spending plays an essential role in the spectrum of tourism services indicators. Simultaneously, the competitiveness of economies is a key economic indicator; thus, research in this area is considered beneficial. This study's objective was to assess the significance of the structure of clients' spending on tourism in the context of the global competitiveness of OECD countries, with the primary focus on the effect of individual types of tourism spending on competitiveness. Several analytical procedures were used in the processing, such as descriptive analysis, relationship analysis, regression analysis, and cluster analysis. Secondary data were included in the analyses, and these data represented six variables determining tourism spending obtained from the World Travel & Tourism Council (WTTC) database: i - Business Tourism Spending (BTS), ii - Domestic Tourism Spending (DTS), iii - Internal T&T Consumption (ITTC), iv - Leisure Tourism Spending (LTS), v - Outbound Travel & Tourism Expenditure (OTTE), vi - Visitor Exports (Foreign spending) (VEFS); and one variable determining competitiveness: the Global Competitiveness Index (GCI), which was obtained from reports published by the World Economic Forum (WEF). These data were collected for all OECD countries from 2010 to 2018. The results of the regression analysis clearly confirmed the effect of tourism spending on competitiveness in OECD countries. The most significant effects were found in BTS and OTTE, and the least significant impact was identified in VEFS. The results provide valuable information for strategic and development plan makers and institutions responsible for improving the business environment in tourism. The study and its results also offer space for developing national and international benchmarking indicators in this area.

Tourism spending as well as innovations are characterized by great economic value, which emphasizes the need for their research from a macroeconomic perspective. The objective of the research was to assess the significance of the relations between infrastructure innovations and tourism spending in a sample of developed countries. The analytical processes included macroeconomic indicators expressing tourism spending and innovations. The research sample consisted of 36 countries of the Organization for Economic Co-operation and Development (OECD) (2010–2019). The analytical processes were primarily performed using robust panel regression and cluster analysis. One of the most important findings is that innovations in information and communication technologies (ICTs) were dominant in terms of the effects on tourism visitors' spending. The results showed that innovations in other areas of infrastructure (general infrastructure, ecological sustainability) should not be neglected either. The significant effects of selected innovation indicators showed positive trajectories. As a result, with the strengthening of innovation activities, an increase in tourism spending is expected, which may lead to economic development. It can be assumed that innovation efforts in countries such as Mexico, the Slovak Republic and Turkey could have great potential for improvement. Based on the results, innovations should be considered a part of tourism development strategies, while ICTs play an important role in this issue. It is desirable to support effective tools to increase the number of innovations in tourism. These innovation efforts at the national level may translate into higher tourism spending, which appears to be economically beneficial.

Background: The primary aim of the research in the present study was to determine the effectiveness of health care in classifying health care financing systems from a sample of OECD (Organisation for Economic Co-operation and Development) countries (2012–2017). This objective was achieved through several stages of analysis, which aimed to assess the relations between and relation diversity in selected variables, determining the effectiveness of health care and the health expenditure of health care financing systems. The greatest emphasis was placed on the differences between health care financing systems that were due to the impact of health expenditure on selected health outputs, such as life expectancy at birth, perceived health status, the health care index, deaths from acute myocardial infarction and diabetes mellitus. Methods: Methods such as descriptive analysis, effect analysis (η²), binomial logistic regression analysis, linear regression analysis, continuity analysis (ρ) and correspondence analysis, were used to meet the above objectives. Results: Based on several stages of statistical processing, it was found that there are deviations in several of the relations between different health care funding systems in terms of their predisposition to certain areas of health outcomes. Thus, where one system proves ineffective (or its effectiveness is questionable), another system (or systems) appears to be effective. From a correspondence analysis that compared the funding system and other outputs (converted to quartiles), it was found that a national health system, covering the country as a whole, and multiple insurance funds or companies would be more effective systems. Conclusions: Based on the findings, it was concluded that, in analyzing issues related to health care and its effectiveness, it is appropriate to take into account the funding system (at least to verify the significance of how research premises affect the systems); otherwise, the results may be distorted.

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.