The Behavioral and Social Dimension of the Public Health System of European Countries: Descriptive, Canonical, and Factor Analysis

Abstract

Background: The state and prospects of the healthcare industry of a country are among its top priorities because the quality of life and health of its citizens are indicators of its success and competitiveness. The aim of this study is to conduct a theoretical analysis and qualitative and quantitative assessments of indicators by developing an integral indicator in the context of behavioral, social, demographic, and economic factors that characterize the level of healthcare system development in European countries using multivariate statistical modeling methods. Methods: The study was implemented using Statistica 10 and Statistica Portable statistical packages. The statistical base of the study was formed using descriptive analysis; a group of 10 European countries was identified using a cluster analysis based on the application of an iterative divisive k-means method. The degree and significance of the interrelations between the components characterizing the studied groups of indicators were determined using canonical correlations by conducting a canonical analysis. Factor modeling is conducted by applying the analysis of the main components to determine the relevant indicators for assessing the level of healthcare system development to build integral indicators of the level of healthcare system development in European countries. Results: The need to improve the level of healthcare system development in European countries was confirmed. Shortcomings and possible reserves for potential improvement of the healthcare system were identified. Conclusions: The results can help public authorities, officials and employees of the healthcare sector organize and conduct effective, timely, high-quality regulation and adjustment of the regulatory and legislative framework to improve healthcare system development.

Effect of minimum wages on labor, welfare and economic growth: Evidence from East Java province

“…The data analysis technique used in this study is canonical correlation analysis (CCA). Canonical correlation is a statistical model used to test the correlation between one set of variables or more than one set of dependent variables with one set of variables or more than one set of independent variables (Vasylieva et al, 2023). The results of the canonical analysis will form the two dependent variables into a composite set of the dependent and two independent canonical variables.…”

“…This research has a complex relationship between the minimum wage in the City/Regency of East Java and the number of labor, welfare, and economic growth. The equation of CCA based on Vasylieva et al (2023) as follows:…”

External assessment of medical education quality: indicative model development considering paradox of skill

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