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The study aims to explore the discrepancy between the subjective and objective debt burdens across various household socio-demographic and debt characteristics. Additionally, it seeks to establish an optimal debt service-to-income ratio (DSTI) threshold for identifying over-indebtedness.

This study utilized a sample of 1,004 respondents from a nationwide survey conducted among Polish indebted households. A discrepancy ratio (DR) measure was proposed to evaluate the divergence between subjective and objective over-indebtedness. Binary logistic regression was employed to estimate the probability of being subjectively and objectively over-indebted, as well as the discrepancy between the two measures of over-indebtedness. The study also employed numerical simulations to determine the optimal DSTI threshold for identifying over-indebted households in general and based on their socio-economic characteristics.

The study established a debt service-to-income ratio (DSTI) threshold of 20% to minimize the discrepancy between subjective and objective debt burden, which is lower than thresholds found in other studies aimed at identifying over-indebted households. Age, number of loans, self-perceived needs satisfaction and type of debt were identified as significant socio-economic and debt-related determinants of over-indebtedness. Household socio-economic and debt-related characteristics significantly influence the threshold for identifying over-indebtedness using DSTI. It can vary widely, ranging from as low as 11% for well-educated women with multiple loan commitments to 43.7% for young males with vocational education, high incomes and originating from households with four or more members.

The paper proposes a more comprehensive approach to debt burden analysis by introducing a new methodology for determining a debt service-to-income (DSTI) threshold that could serve as a measure of over-indebtedness based on the discrepancy between subjective and objective over-indebtedness. It also emphasizes the significance of socio-economic and debt-related factors in evaluating subjective and objective over-indebtedness.

The investigation goal is the analysis of the relation between healthcare expenditures and other resources, and COVID-19 fatality rates among European countries to design effective health policies for crisis management.

Research methodology is based on descriptive statistics and various parametric methods, also including a linear model of regression to analyze basic relationships of variables under study.

Results show that a lower COVID-19 fatality rate is associated with higher levels of health expenditure (% GDP), of healthcare expenditure per capita, health expenditure in preventive care (% GDP), hospitals per million inhabitants, physicians, nurses, hospital beds and curative acute care beds per 1,000 inhabitants. Regression analysis shows that a 1% increase in healthcare expenditures per capita of countries, it reduces the level of COVID-19 fatality rate by 0.74%. In fact, many countries in Eastern Europe with low healthcare expenditures per capita in 2019 (e.g., Bulgaria, Romania, Hungary, Poland, Latvia, Slovakia, Lithuania, etc.), they have experienced high COVID-19 fatality rates. Instead, a lot of countries in Western Europe, with high healthcare expenditures per capita, such as Germany, Denmark, Austria, and the Netherlands, they had resilient health systems to face pandemic crisis and lower COVID-19 fatality rates.

These findings suggest strategies of systematic and continuous investments in healthcare, medical technologies, and ICT infrastructures to support effective health policy of crisis management in countries to face future pandemic crisis and other emergencies in society.

The explanation of critical role of high health expenditure (% GDP) and healthcare expenditure per capita to support robust health systems that bolster the resilience in nations to face health emergencies and worldwide crises.

In this viewpoint article, the authors recognize the increased focus in health systems on co-design for innovation and change. This article explores the role of leaders and mangers in developing and enhancing a culture of trust in their organizations to enable co-design, with the potential to drive innovation and change in healthcare.

Using social science analyses, the authors argue that current co-design literature has limited focus on interactions between senior leaders and managers, and healthcare staff and service users in supporting co-designed innovation and change. The authors draw on social and health science studies of trust to highlight how the value-based co-design process needs to be supported and enhanced. We outline what co-design innovation and change involve in a health system, conceptualize trust and reflect on its importance within the health system, and finally note the role of senior leaders and managers in supporting trust and responsiveness for co-designed innovation and change.

Healthcare needs leaders and managers to embrace co-design that drives innovation now and in the future through people – leading to better healthcare for society at large. As authors we argue that it is now the time to shift our focus on the role of senior managers and leaders to embed co-design into health and social care structures, through creating and nurturing a culture of trust.

Building public trust in the health system and interpersonal trust within the health system is an ongoing process that relies upon personal behavior of managers and senior leaders, organizational practices within the system, as well as political processes that underpin these practices. By implementing managerial, leadership and individual practices on all levels, senior managers and leaders provide a mechanism to increase both trust and responsiveness for co-design that supports innovation and change in the health system.