BACKGROUND: Population health is vital to a nation's overall well-being and development. To achieve sustainable human development, a reduction in health inequalities and an increase in interstate convergence in health indicators is necessary. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. This study investigates the progressive changes in the convergence and divergence patterns in health status across major states of India from 1990 to 2018. METHODS: Sigma plots (σ), kernel density plots, and log t-test methods are used to test the convergence, divergence, and club convergence patterns in the health indicators at the state level. RESULTS: The result of the sigma convergence suggests that life expectancy at birth has converged across all states. After 2006, however, the infant mortality rate, neonatal mortality rate, and total fertility rate experienced a divergence pattern. The study's findings indicate that life expectancy at birth converges in the same direction across all states, falling into the same club (Club One). However, considerable cross-state variations and evidence of clubs' convergence and divergence are observed in the domains of infant mortality rate, neonatal death rate, and total fertility rate. As suggested by the kernel density estimates, life expectancy at birth stratifies, polarizes, and becomes unimodal over time, although with a single stable state. A bimodal distribution was found for infant, neonatal, and total fertility rates. CONCLUSIONS: Therefore, healthcare strategies must consider each club's transition path while focusing on divergence states to reduce health variations and improve health outcomes for each group of individuals.
Our research aims to support decision-making regarding the financing of healthcare projects by structural funds with policies targeting reduction of the development gap among different regions and countries of the European Union as well as the achievement of economic and social cohesion. A fuzzy decision support model for the evaluation and selection of healthcare projects should rank the project applications for the selected region, accounting for the investor's wishes in the form of a regional coefficient in order to reduce the development gap between regions. On the one hand, our proposed model evaluates project applications based on selected criteria, which may be structured, weakly structured, or unstructured. On the other hand, it also incorporates information on the level of healthcare development in the region. The obtained ranking increases the degree of validity of the decision regarding the selection of projects for financing by investors, considering the level of development of the region where the project will be implemented. At the expense of European Union (EU) structural funds, a village, city, region, or state can receive funds for modernization and development of the healthcare sector and all related processes. To minimize risks, it is necessary to implement adequate support systems for decision-making in the assessment of project applications, as well as regional policy in the region where the project will be implemented. The primary goal of this study was to develop a complex fuzzy decision support model for the evaluation and selection of projects in the field of healthcare with the aim of reducing the development gap between regions. Based on the above description, we formed the following scientific hypothesis for this research: if the project selected for financing can successfully achieve its stated goals and increase the level of development of its region, it should be evaluated positively. This evaluation can be obtained using a complex fuzzy model constructed to account for the region's level of development in terms of the availability and quality of healthcare services in the region where the project will be implemented.
This study proposes an approach to the external evaluation of medical education programs' quality based on a combination of indicators, including international rankings, external stakeholders' input, and independent agencies' assessments. We modify the success equation with a detailed consideration of the skill component and its decomposition into internal and external quality assurance elements along with authority. We carried out a bibliometric analysis regarding the problem of medical education quality assessment in the context of achieving sustainable development goals. We described the calculation model of external quality assessment indicators through the algorithms of independent education quality assurance agencies' activity and rating indicators shown in the modified Mauboussin's equation. The model considers the economic component (the consequence of achievement) of skill, which is expressed in raising funds from external sources to implement educational and scientific activities. The proposed algorithm for assessing the educational program quality can be applied to benchmark educational program components, complete educational programs within the subject area, and the educational institution for different areas. We propose a "financial" model for educational program quality based on the analysis results. The model makes it possible to determine the need for additional focused funding of the educational program based on the individual analysis of the external evaluation criteria of the achievement level. This study analyzes the accreditation results of more than 110 educational programs in 2020 and 8 months of 2021 within the direction 22 "Medicine" (according to the national classification of fields of knowledge) (state and private Ukrainian medical universities).
- MeSH
- studium lékařství * MeSH
- výuka - hodnocení * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVE: The aim of this study was to evaluate the perception of the respondents in selected areas of testing for COVID-19 during the first waves of this disease with an emphasis on the age categories. METHODS: The research sample consisted of 806 Slovak respondents and the collection of data took place in February 2021. The study examined six areas, of which five focused on the perception of testing and one area focused on examining the risk of population behaviour. All areas were examined in the first as well as in the last testing for COVID-19. In terms of age, we focused on 4 age categories: up to 24 years, 25-44 years, 45-59 years, and over 60 years. Data were obtained by online survey, using descriptive analysis and nonparametric analysis of differences. RESULTS: The results of the analysis show that age is a socioeconomic characteristic that is of great importance for the creation and implementation of epidemiological processes and programmes and therefore epidemiologists should pay increased attention to it when creating prevention programmes. Younger people perceived testing more positively than older ones, even though the course of the disease caused by COVID-19 is much more severe in older people. The difference in the perception of testing between age categories was confirmed in the first as well as in the last test study. Respondents perceived the last test more negatively and thus they showed slightly riskier behaviour compared to the first test. CONCLUSIONS: We perceive testing as an efficient way in the fight against pandemics generally, but we point out that testing should be well accomplished in a managerial way, otherwise testing can have a negative impact on society's confidence.
- MeSH
- COVID-19 * diagnóza epidemiologie MeSH
- lidé MeSH
- pandemie * MeSH
- percepce MeSH
- SARS-CoV-2 MeSH
- senioři MeSH
- testování na COVID-19 MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Slovenská republika MeSH
Internet addiction is a serious problem among young adults that requires increased attention, especially at a time of distance learning during the coronavirus disease 2019 (COVID-19) pandemic. The aim of the study was to assess the relationships between internet addiction and selected socio-demographic, study-related, and psychological characteristics of college students. Internet addiction was measured using the Internet Addiction Test both overall and in its individual subscales (Salience, Excessive Use, Neglect Work, Anticipation, Lack of Control, and Neglect Social Life). The selected characteristics represented (1) socio-demographic profile (gender, age, residence, family), (2) academic profile (housing during the semester, form of study), and (3) psychological profile (depressive symptoms-the Patient Health Questionnaire, stress-the Perceived Stress Scale, anxiety symptoms-the Generalized Anxiety Disorder). Data collection took place during the first wave of the COVID-19 pandemic in 2020 at Czech and Slovak colleges, with 1,422 students from the Czech Republic and 1,677 students from Slovakia participating in the research. The analytical processes were carried out through descriptive analysis, non-parametric difference analysis, and multiple negative binomial regression. Mild internet addiction was found in 387 (27.2%) Czech and 452 (27.0%) Slovak students. Moderate internet addiction was identified in 49 (3.4%) students from the Czech Republic and in 100 (6.0%) students from Slovakia. Two (0.1%) Czech and three (0.2%) Slovak students reported severe internet addiction. Increased likelihood of internet addiction overall, as well as in most individual subscales, was found particularly among male students and students who lived away from home during the semester. Depressive symptoms and stress could also be considered significant predictors in both countries. These results are important for the development of effective strategies and prevention programs, as Internet addiction may be a serious problem in the future, given the current times. When assessing internet addiction among college students, it would also be appropriate to evaluate the individual internet addiction subscales and their specifics.
- MeSH
- COVID-19 * epidemiologie MeSH
- demografie MeSH
- lidé MeSH
- mladý dospělý MeSH
- návykové chování * epidemiologie psychologie MeSH
- netholismus epidemiologie MeSH
- pandemie MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- studenti psychologie MeSH
- Check Tag
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
- Slovenská republika MeSH
Poor mental health is a growing concern among young people during the coronavirus disease 2019 (COVID-19) pandemic. The aim of this study was to assess the associations of Internet addiction with depressive symptoms, anxiety symptoms, and stress in higher education students during the COVID-19 pandemic, as well as to examine these mental health problems in the context of study-related characteristics. The research sample consisted of 3,099 participants from the Czech Republic (CZ: 1,422) and Slovak Republic (SK: 1,677). The Internet Addiction Test (IAT), the Generalized Anxiety Disorder (GAD-7) scale, the Patient Health Questionnaire for depressive symptoms (PHQ-9), and the Perceived Stress Scale (PSS) were used to measure mental health problems. The analyses also included demographic data (gender and age) and study-related characteristics (form of study, degree of study, field of study, distance between college and home, and housing during the semester). Based on the results of frequency and descriptive analyses, the prevalence of mental health problems was high. The most serious levels of Internet addiction (IAT cut-off point ≥ 50), to which attention should be paid, were found in 3.5% of Czech and 6.2% of Slovak students. Using the standard cut-off point of GAD-7 ≥ 10, 14.1% of Czech and 11.6% of Slovak students were identified with anxiety symptoms. Regarding the PHQ-9 with the cut-off point ≥ 10, 23.4% of Czech and 19.1% of Slovak students had depressive symptoms, which should be addressed. Using the PSS cut-off point ≥ 27, 12.9% of Czech students and 9.1% of Slovak students perceived high stress. The quantile regression analysis showed that Internet addiction was positively associated with anxiety symptoms, depressive symptoms, and stress in all of the analyzed cases (p-value < 0.001). In terms of study-related characteristics, the binomial logistic regression analysis revealed that risk factors for mental health problems in Czech and Slovak students were mainly full-time form of study and living away from home during the semester. Internet addiction, anxiety symptoms, depressive symptoms, and stress are issues that require increased attention, and professionals and policy-makers should implement interventions to effectively prevent and help students with psychological problems.
- MeSH
- COVID-19 * epidemiologie MeSH
- deprese epidemiologie MeSH
- lidé MeSH
- mladiství MeSH
- netholismus epidemiologie MeSH
- pandemie * MeSH
- psychický stres epidemiologie MeSH
- studenti psychologie MeSH
- úzkost epidemiologie MeSH
- úzkostné poruchy epidemiologie MeSH
- Check Tag
- lidé MeSH
- mladiství MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Objectives: The objective was to explore whether a sick leave length related to mental morbidity differs across different occupational categories. Methods: In the analysis, registry of sick leaves was analyzed. Provided analysis is focused on the length of sick leaves related to mental diseases caused by substance use or other factors. Dependent variable is the sick leave length, and the independent variables are the categories of disease and occupation. Kruskal-Wallis test, Shapiro-Wilk test, and Brown-Forsythe (B-F) are used. Results: There are differences in mental sick leave lengths caused by substance use or other factors. In the case of mental illnesses attributable to drugs, differences in the sick leave duration among different working groups were not found. Considering mental disorders caused by other factors, there are differences in the sick leave duration among different working groups. Conclusions: There is no evidence of longer sick leave in people diagnosed with mental disorder related to substance use. Differences in occupational categories do not relate to sick leave length.
- MeSH
- duševní poruchy * epidemiologie MeSH
- lidé MeSH
- mladý dospělý MeSH
- pracovní neschopnost * MeSH
- zaměstnanost MeSH
- Check Tag
- lidé MeSH
- mladý dospělý MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Studying in college can be a challenging time for many students, which can affect their mental health. In addition to academic pressure and stressful tasks, another aggravating factor in student life is the ongoing coronavirus disease 2019 (COVID-19) pandemic. The aim of the study was to examine the prevalence of anxiety, depression, and somatic symptoms in Czech and Slovak college students during the COVID-19 pandemic and to evaluate possible socio-demographic determinants of mental health problems. A total of 3,099 respondents participated in this cross-sectional study (Czech Republic: 1,422, Slovakia: 1,677). The analyzes included the Patient Health Questionnaire for somatic symptoms (PHQ-15), the Generalized Anxiety Disorder instrument (GAD-7), and the Patient Health Questionnaire for depression (PHQ-9). Socio-demographic factors were gender, age, family structure, marital status, form of study, degree of study, year of study, field of study, distance between home and college, residence, and housing during the semester. Among Czech students, prevalence of somatic complaints, anxiety and depression was 72.2, 40.3, and 52%, respectively. Among Slovak students, prevalence of somatic complaints, anxiety and depression was 69.5, 34.6, and 47%, respectively. During the COVID-19 pandemic, the most severe mental health problems were identified in a non-negligible part of the sample (Czech Republic: PHQ-15 = 10.1%, GAD-7 = 4.9%, PHQ-9 = 3.4%; Slovakia: PHQ-15 = 7.4%, GAD-7 = 3.5%, PHQ-9 = 2.7%). Regarding the differences between the analyzed countries, a significantly higher score in somatic symptoms, anxiety, and depression was identified in the Czech Republic. Significant differences in mental disorders were found in most socio-demographic characteristics. The main results of the logistic regression analysis revealed that risk factors for mental health disorders in Czech and Slovak students were female gender, younger age, third degree of study, and study of Informatics, Mathematics, Information and Communication Technologies (ICT). Especially in the case of these high-risk groups of students, public policies should consider a response to impending problems. The findings are an appeal for a proactive approach to improving the mental health of students and for the implementation of effective prevention programs, which are more than necessary in the Czech and Slovak college environment.
- MeSH
- COVID-19 * epidemiologie MeSH
- deprese epidemiologie psychologie MeSH
- lidé MeSH
- pacienti bez organického nálezu * MeSH
- pandemie MeSH
- průřezové studie MeSH
- studenti psychologie MeSH
- úzkost epidemiologie psychologie MeSH
- úzkostné poruchy epidemiologie MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
- Slovenská republika MeSH
