Gözde Bozkurt

As in many parts of the world, demographic indicators in Türkiye (e.g., increasing life expectancy and a growing proportion of the older population) are driving important social implications. One consequence is a growing tendency to remain in the workforce at older ages. Although older individuals are increasingly participating in the labour force, the use of information and communication technologies affects them in multidimensional ways. This chapter examines the health and social inequalities faced by Türkiye’s ageing population in the context of digital transformation. Drawing on findings from national research, it analyses how digital technology use affects the health of older workers during extended working lives. It also presents examples of good practices in Türkiye’s health and social sectors and assesses the opportunities they offer to older adults. The chapter concludes with structural-level policy recommendations aimed at enhancing digital inclusion for older people in Türkiye.

Each financial market carries a unique “fractal signature” with its own distinct risk and return pattern. This study comparatively deciphers these fractal signatures of the leading stock market indices of the Emerging Seven (E7) countries (Turkey, India, Brazil, Mexico, Russia, China, Indonesia), using Multifractal Detrended Fluctuation Analysis (MFDFA) with data covering the 2021–2025 period. The findings reveal that all examined markets deviate from the classical random walk model and exhibit distinct multifractal characteristics. However, significant differences were observed among these signatures: in contrast to Russia’s chaotic structure, which showed extreme fragility to geopolitical shocks, the Chinese and Mexican markets presented a more stable and homogeneous risk profile. In all indices, it was found that small-scale fluctuations carry a strong long-memory effect (stable trends), while large-scale fluctuations assume a more random character (sudden shocks). This asymmetric behavior confirms the heterogeneous nature of investor expectations. For example, the generalized Hurst exponents H(q) ranged from 0.22 (RTS, Russia) to 0.73 (BIST100, Turkey), and the spectrum width Δα varied between 0.10 (Mexico) and 0.45 (Russia), confirming significant heterogeneity in market complexity. Turkey’s BIST100 index, with its structure encompassing both predictable and sudden-shock-prone dynamics, occupies a balanced position within this spectrum. Consequently, the study confirms that understanding these unique fractal signatures of emerging markets is a fundamental prerequisite for formulating effective risk management strategies and achieving global portfolio diversification.

The growing visibility of social media influencers has increased interest in their role in shaping health beliefs and behaviors. While prior research has largely focused on message characteristics or direct behavioral outcomes, less attention has been given to the conditions under which influencer-based health messages are interpreted and translated into action. This study conceptualizes influencer-based health communication not as a direct persuasive force, but as a conditional communication process. Drawing on Uses and Gratifications Theory and the Health Belief Model as interpretive frameworks, it examines how individuals engage with health-related influencer content, how such engagement relates to health perceptions, and how digital health literacy shapes message interpretation.Survey data from social media users were analyzed using Firth's penalized logistic regression to address the rarity of influencer-driven health behavior. Findings indicate that, despite high levels of exposure to influencer-based health content, the translation of such exposure into health-related action remains limited. Exposure to health content significantly increases the likelihood of influencer-driven behavior, whereas higher digital health literacy reduces this likelihood, suggesting a protective effect. Additionally, perceived commercial intent decreases the probability that influencer recommendations lead to action.By distinguishing between engagement and behavioral change, this study reframes influencer effects as conditional outcomes shaped by motivations, perceptions, and interpretive competencies. It contributes to health communication literature by moving beyond linear persuasion models and highlighting the critical role of digital health literacy. The findings also offer practical implications for strengthening individuals' ability to critically evaluate health information in digital environments.

This study investigates the existence and characteristics of financial contagion between Türkiye and Indonesia,-two emerging economies with similar macroeconomic profiles—through an econometric approach. Using daily USD/TRY and USD/IDR exchange rate return data from January 2, 2008, to April 17, 2025, the research applies Constant Conditional Correlation GARCH (CCC-GARCH) and Dynamic Conditional Correlation GARCH (DCC-GARCH) models to capture volatility dynamics and correlation structures. Logarithmic returns were tested for normality, and volatility clustering was confirmed. The findings reveal a unidirectional and statistically significant short-term influence from Türkiye to Indonesia, indicating asymmetric contagion. Although the conditional correlations are positive and significant, their low levels point to limited financial integration. Furthermore, the dynamic correlation parameters from the DCC model are statistically insignificant, suggesting that correlation remains stable over time rather than reacting sharply to shocks. The results imply a low but persistent interdependence, shaped more by structural economic linkages than by temporary crises. As one of the few empirical studies comparing exchange rate contagion in developing countries, this research contributes to the literature by highlighting contagion asymmetry and evaluating the relative performance of CCC and DCC models in emerging market settings.

Bu araştırma, BRICS (Brezilya, Rusya, Hindistan, Çin ve Güney Afrika) ülkelerinde yeşil büyüme, enerji kullanımı, yenilenebilir enerji arzı, sağlık göstergeleri ve kişi başına düşen gayrisafi yurtiçi hasıla (GSYİH) arasındaki ilişkileri incelemektedir. Araştırmada, zaman serisi verilerinde uzun dönem ilişkileri analiz eden Bootstrap Otoregresif Dağıtılmış Gecikme Modeli (ARDL) kullanılmıştır. 1990-2021 yılları arasını kapsayan araştırma verileri, Ekonomik İşbirliği ve Kalkınma Örgütü (OECD) veri havuzunda yer alan yeşil büyüme göstergelerinden elde edilmiştir. Bulgular, belirtilen yıllar arasında BRICS ülkelerinde farklı eşbütünleşme süreçleri bulunduğunu, ayrıca yenilenebilir enerji arzı ve kişi başına reel GSYİH ile doğumda beklenen yaşam süresi arasında eşbütünleşik bir ilişkinin var olduğunu göstermektedir. Granger nedensellik testi sonuçları, yenilenebilir enerji kullanımının doğumda beklenen yaşam süresini olumlu etkilediğini, enerji yoğunluğunun ise ekonomik büyüme üzerinde belirleyici bir faktör olduğunu ortaya koymuştur. Ancak, ekonomik büyüme bağımlı değişken olarak ele alındığında uzun dönemli eşbütünleşme tespit edilmemiştir. Sonuçlar, enerji tüketimi ve CO2 emisyonlarının kısa vadede ekonomik büyümenin önemli belirleyicileri olduğunu göstermektedir. Araştırma, sürdürülebilir ekonomik ve çevresel kalkınma stratejilerinin sağlık politikaları ile entegrasyonunun önemini vurgulamakta ve politika yapıcılara yenilenebilir enerji yatırımlarını artırmaya yönelik öneriler sunmaktadır.

Grounded in the Health Belief Model (HBM) and Media System Dependency Theory (MSDT), this study examines the relationship between media literacy and health literacy in the Turkish context, where digital media plays an increasingly dominant role in disseminating health-related information. It focuses on how individuals access, evaluate, and utilize health information, analyzing the effects of media literacy sub-dimensions-access, analysis, evaluation, and communication-on health literacy levels. The study aims to determine how media-based health information influences individuals' decision-making processes and their ability to make informed health choices. A survey-based quantitative research approach was employed with 485 participants from Turkey, of which 477 valid responses were analyzed. The Turkish Health Literacy Scale (TSOY-32) measured health literacy, while the Media Literacy Skills Scale assessed media literacy. The Generalized Ordered Logit Model (GOLM) was applied to examine the effects of media literacy on health literacy. Descriptive statistics, correlation analysis, and hypothesis testing were conducted. Media literacy levels significantly influence health literacy levels (p < 0.05). The access sub-dimension increased the likelihood of improving health literacy by 1.90 times (p < 0.05). The analysis sub-dimension significantly enhanced health literacy by 2.23 times (p < 0.05). The evaluation sub-dimension had a statistically significant effect on health literacy (p < 0.05). The communication sub-dimension supports individuals in sharing health information and making informed decisions (p < 0.05). Health recommendations disseminated through media significantly impact health literacy levels (p < 0.05). Trust in media-based health information had a weak but positive correlation with health literacy (r = 0.2097, p < 0.05). Education level was positively correlated with health literacy, while income level showed no significant effect. These findings suggest that enhancing media literacy skills, particularly in access and analysis, can meaningfully improve individuals' capacity to navigate complex health information landscapes and foster more informed health behaviors. The study highlights the crucial role of media literacy in improving health literacy and preventing misinformation. Access and analysis skills are particularly vital in enabling individuals to obtain accurate health information and avoid misleading content. Conducted within the Turkish sociocultural context, where digital media usage is high and misinformation about health is prevalent, the findings offer valuable insights for national health promotion strategies. Policymakers and educators should integrate media literacy into educational curricula, launch public awareness campaigns to combat misinformation, and develop strategies to enhance individuals' critical thinking skills regarding health information. This study is limited by its cross-sectional design and reliance on self-reported data. Future research should employ longitudinal methods and explore the long-term impact of media and health literacy across different demographic groups and contexts.

Slovenská akadémia vied vykonáva špičkový základný výskum, dlhodobý strategický a aplikovaný výskum a vývoj a poskytuje prístup k vedeckej infraštruktúre.

Demographic change is a critical factor affecting countries' economic and socio-cultural structure. The change between generations deeply affects economic systems and shapes production capacity. This research examines the impact of the generational transition in the youth labor market on total factor productivity (TFP) in G20 countries. Between 1980 and 2019, the labor force participation rates and TFP data of young people aged 15-24 were evaluated with a panel regression model. The findings reveal the impact of this transition between generations on economic systems; they emphasize the role of different generations in economic dynamics. This study aims to contribute to the literature and guide the policy-making processes of G20 countries. It is expected to shed light on future policy developments by emphasizing the importance of intergenerational interaction in the labor market on the economic performance of countries.

Green growth integrates economic progress with environmental sustainability by reducing the ecological costs of development. It promotes green technologies and renewable energy to limit the negative impacts of industrialization and fossil fuel reliance. This study examines the long-term link between green investments, energy structure, and sustainable growth in Eurasian Economic Union countries (Russia, Belarus, Kazakhstan, Kyrgyzstan, Armenia) and Turkey from 2000 to 2021. The dependent variable, Green GDP, adjusts per capita GDP for environmental damages such as carbon emissions, air pollution, resource depletion, and deforestation. Explanatory variables include renewable energy’s share in final energy consumption, foreign direct investment (FDI), trade deficit, fossil-fuel-based electricity, R&D spending, and climate finance received. To address cross-country dependence, the analysis uses second-generation panel unit root and cointegration tests. Long-run coefficients are estimated via the Fully Modified Ordinary Least Squares (FMOLS) method. Results show renewable energy use and R&D spending significantly boost green growth, while trade deficits and fossil fuel dependence hinder it. Surprisingly, FDI negatively affects green growth, suggesting that capital inflows often target environmentally harmful sectors rather than sustainable ones. The study highlights the importance of transforming energy systems, enhancing regional cooperation in environmental innovation, and aligning policies to attract green investments. These findings provide empirical evidence for policymakers aiming to balance economic growth with environmental protection and advance the Sustainable Development Goals (SDGs) through environmentally conscious strategies.