This study examines the determinants of inflation in Tunisia from 1998 to 2023, with a particular focus on the role of fiscal policy. The study analyzes the long-run and short-run relationships between inflation and key macroeconomic variables, including government expenditure, government revenue, money supply, balance of trade, and budget deficits using ARDL model. The empirical findings reveal that budget deficits have a significant and positive impact on inflation, underscoring the critical role of fiscal imbalances in driving price instability. In contrast, government expenditure, government revenue, money supply, and balance of trade do not exhibit statistically significant long-term effects on inflation. The results highlight the importance of fiscal discipline and effective coordination between fiscal and monetary policies to achieve price stability. These findings provide valuable insights for policymakers in Tunisia and other developing economies facing similar inflationary pressures, emphasizing the need for prudent fiscal management and structural reforms to mitigate inflation volatility and ensure macroeconomic stability.

This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.

This study examines the determinants of stunting prevention among toddlers in fishing families residing in the coastal areas of Bengkulu City. Utilizing a mixed-method approach, the research combined survey data from 70 respondents and in-depth interviews with 11 informants. Findings indicate that health behavior and genetic factors from health status, alongside education level and occupation from socioeconomic status, play pivotal roles in stunting prevention. Consumption patterns, particularly the consistent provision of animal protein and vegetables in daily meals, significantly contribute to the absence of stunting cases in the studied population. However, limited fruit intake persists due to economic barriers. The study underscores the necessity of integrated strategies, including nutrition education, enhanced access to nutritious foods, and economic support for fishing families, to sustain stunting prevention in coastal communities.

The consumption of dietary supplements among the elderly is on the rise. Despite the potential benefits, a comprehensive understanding of the decision-making processes leading to the consumption is lacking. This study explores the conditions influencing the decision-making and behavioral patterns of older adults related to dietary supplement consumption. Using a qualitative approach, in-depth interviews were conducted with 21 elderly participants from a seniors’ club in Bangkok, Thailand, who had consistently consumed dietary supplements for at least one year. The behavior was classified into five primary categories: enduring use of identical dietary supplements, insufficient regard for health compatibility, replacing medications with supplements, not verifying before consumption, and opting for supplements over medical treatments. These patterns are aligned with the core constructs of the Theory of Planned Behavior (attitude, subjective norm, and perceived behavioral control). Many individuals perceive supplements as pivotal health investments, while others view them as a direct route to robust health. Trusted advice from friends and television significantly influence their choices, with a prevailing sentiment that dietary supplements are generally safe. The high price tag on supplements is often associated with superior quality. The findings highlight the multifaceted nature of dietary supplement consumption decisions among the Thai elderly, suggesting the need for interventions to promote safer and more informed choices.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.