Search Results (1,762)

This study examines how socioeconomic conditions shape learning outcomes in rural schooling contexts through a narrative review of the recent empirical literature. Studies published between 2020 and 2026 were identified through thorough systematic searches of EBSCOhost, Scopus, Web of Science, and Google Scholar. Following screening and eligibility assessment, 50 empirical studies were included in the final synthesis. The review explores how household economic resources, parental education and involvement, and community and institutional conditions interact to influence literacy, numeracy, attendance, grade progression, and educational persistence in rural schools. The findings reveal strong convergence across the literature that structural socioeconomic disadvantage contributes to unequal learning outcomes by limiting access to educational resources, constraining school and institutional capacity, and weakening formal and informal support systems. At the same time, the evidence points to substantial contextual variation and conditionality. The effects of household and parental characteristics are mediated by school quality, governance coherence, and community support structures, while institutional improvements generate uneven outcomes across different rural settings. Building on these patterns, the study develops a multi-level conceptual framework that illustrates how convergence, divergence, and conditionality interact within rural education systems. The review argues that rural educational inequality emerges from the dynamic interaction of socioeconomic and institutional mechanisms rather than from isolated determinants, underscoring the importance of integrated, context-sensitive policy interventions that advance social sustainability objectives. Full article

Understanding academic achievement requires moving beyond the identification of influential factors toward explaining how these factors are organized into functional learning and cognitive mechanisms. Although prior research has extensively documented the roles of socioeconomic status, student attitudes, and learning behaviors, less attention has been paid to how these elements interact within structured pathways that reflect underlying learning intelligence across educational systems. This study adopts a mechanism-oriented perspective to examine mathematics achievement using data from PISA 2018. Focusing on high-performing regions in East Asia and Western countries, it integrates interpretable artificial intelligence methods with structural modeling to investigate how contextual, psychological, and learning-process factors jointly shape achievement outcomes. The findings show that high achievement is not governed by a single set of dominant predictors, but by distinct organizational mechanisms of learning intelligence. In East Asian systems, achievement follows a chain-like convergent structure, in which socioeconomic background is systematically translated into academic outcomes through sequential psychological and self-regulatory processes. Psychological factors, particularly educational expectations and self-beliefs, function as key mediating mechanisms that organize learning engagement and strategy use. By contrast, high-performing systems in Europe and North America exhibit a parallel configuration, in which multiple cognitive and behavioral factors independently contribute to achievement through more decentralized pathways, reflecting a distributed structure of learning intelligence. Across regions, learning processes such as reading engagement and digital literacy show consistently positive associations with achievement. However, their roles vary depending on how they are embedded within broader system-level structures. These results suggest that self-regulation operates not merely as an associated factor, but as an organizing mechanism of learning intelligence that structures the translation of background resources into performance. By reconceptualizing prediction as a means of revealing the organization of learning intelligence, this study proposes a unified analytical framework that links interpretable artificial intelligence with theory-driven explanation. The findings contribute to a deeper understanding of how achievement systems function and highlight that high performance can emerge through multiple, structurally distinct pathways, with important implications for educational research, cognitive theory, and policy design. Full article

Background and Objectives: The COVID-19 pandemic caused unprecedented mortality shocks worldwide, but its differential impact across European regions and the mediating mechanisms remain inadequately quantified. Materials and Methods: We conducted a longitudinal multilevel analysis using data from 29 European countries (2015–2023; N = 261 country-years). Linear mixed models estimated the impact of the pandemic on life expectancy, controlling for regional differences, vaccination rates, healthcare expenditures, gross domestic product, and excess mortality. The primary outcome was national life expectancy at birth. Results: The pandemic period was associated with an average reduction of 1.12 years in life expectancy (95% CI: 0.95 to 1.49, p < 0.001) after adjusting for pre-existing trends. Eastern Europe experienced 56% greater impact than Western Europe (interaction β = −0.623, p = 0.002). Excess mortality emerged as the primary mediator, explaining 79% of the pandemic effect. Each 1% increase in excess mortality reduced life expectancy by 0.091 years (p < 0.001). Healthcare expenditures showed protective effects (β = 0.000327 per purchasing power standards (PPS), p = 0.049), while vaccination rates, as a direct predictor, were not significantly associated with life expectancy in multivariate models. This critical finding on vaccination rates does not imply biological inefficacy but rather suggests a misspecification of its role. Conclusions: Excess mortality, rather than its direct component, COVID-19-specific mortality, appears to mediate most of the pandemic’s impact on life expectancy. Regional disparities reflect structural differences in healthcare systems and socioeconomic conditions more than differential vaccination uptake. The protective effect of vaccination on life expectancy operates entirely through the reduction in excess mortality. Consequently, health policies should prioritize strengthening resilient health systems as well as disease-specific interventions. Full article

Background and Objectives: New Caledonia, an archipelago in the South Pacific, experienced an unprecedented conjunction of prolonged border closure during the COVID-19 pandemic (2020 to 2022) and marked influence of the El Niño/Southern Oscillation (ENSO). This context provided a unique opportunity to explore how environmental drivers, island isolation, and socio-demographic factors interact to shape infectious disease dynamics. This study aimed to assess the respective and combined effects of climatic variability, travel restrictions, and socio-demographic factors on the dynamics of four priority infectious diseases. Materials and Methods: We retrospectively analysed data from 2017 to 2023 on four infectious diseases: leptospirosis, dengue, influenza, and hepatitis A (HAV). Satellite precipitation data and the Multivariate El Niño/Southern Oscillation Index (MEI) were used. Socio-demographic and economic variables were gathered. Statistical analyses employed descriptive analysis and Generalized Additive Mixed Models to evaluate the associations between climatic events, travel restrictions, and disease circulation using the communal level as a random effect and time (daily) as a spline effect. Results: We analysed 878 cases of leptospirosis, 165 of HAV, 6607 of influenza, and 7377 dengue cases. Influenza was associated with rainfall before lockdown (Odds Ratio (OR) 0.7, Confidence interval 95%, (CI95%), (0.6–0.8)) and disappeared during lockdown but resurged post-reopening losing its meteorological association. Dengue epidemics declined, coinciding with the Wolbachia program and border closure, and were associated with lower MEI (OR 0.78, CI95% (0.6–1) during the 2017 to 2020 period. HAV cases were correlated with the MEI (OR: 1.8, CI95% (1–3.3)). Leptospirosis cases were associated with cumulative rainfall (OR 1.12 (1.1–1.2)) and lower education (OR 1.04, CI95% (1–1.1)) and decreased with water supply (OR 0.7, CI95% (0.5–0.8)). Conclusions: Our findings highlight how climatic conditions, mobility restrictions, and socio-environmental inequities differentially shape infectious disease risks in island ecosystems. These results reinforce the need for integrated One Health surveillance that jointly addresses environmental change, social vulnerability, and infectious disease prevention. Full article

Chronic pain is a complex and widespread pathological state that severely impairs the quality of life of millions worldwide and imposes a heavy socioeconomic burden. Current therapeutic regimens often fail to provide adequate relief, frequently accompanied by dose-limiting side effects. Emerging evidence suggests that the bidirectional crosstalk between microglia and neurons plays a fundamental role in the development and maintenance of chronic pain. This interaction contributes to central sensitization and enhanced neuronal excitability. This review elucidates the molecular mechanisms underlying microglia–neuron communication. with particular emphasis on its modulation of neuronal excitability. We also discuss innovative translational strategies such as gene therapy, cell therapy, and nanomedicine. Modulating these neuroimmune interfaces represents a promising frontier for developing more precise and efficacious analgesic interventions. Full article

This study examines the association between digital payments adoption and reliance on cash in Latin America and the Caribbean (LAC), as well as its potential implications for financial inclusion. Using microdata from the 2021 Global Findex Survey for 17,498 adults, logit models and average marginal effects are estimated to assess this relationship according to income, gender, age, education, rural-urban location, and internet access. The results show that the use of digital payments is associated with a lower probability (9.7 percentage points) of using cash, a statistically significant and robust effect among different population groups. People with less education, older age, and limited access to the internet are more dependent on cash, while income differences are less pronounced than expected. Counterfactual simulations consistently show lower reliance on cash among digital payment users, regardless of socioeconomic status. The study provides new microeconomic evidence for the LAC by quantifying the association between digital payments and cash use and analyzing its heterogeneity between socioeconomic groups. Sustainable financial inclusion is not measured by a composite indicator or as an independent variable; it is used as an interpretative framework to analyze whether the adoption of digital payments is associated with less dependence on cash and greater interaction with formal financial channels. Policy implications suggest strengthening payment interoperability, digital trust, financial education, and consumer protection to expand integration into formal financial channels. Full article

Wild fruit species are key components of natural and semi-natural ecosystems, playing an important role in maintaining ecological balance and supporting biodiversity. This review aims to analyze these species from the perspective of their ecological functions, contribution to biodiversity conservation, and the ecosystem services they provide. Ecologically, wild fruit species contribute to soil stabilization, nutrient cycling, and carbon sequestration, while also serving as essential food sources and habitats for a wide range of organisms, including mammals, birds, insects, and microorganisms. Through these interactions, they support ecosystem functioning and resilience. Beyond their ecological role, these species provide significant socio-economic benefits, particularly in rural areas. They contribute to cultural ecosystem services and represent valuable resources for traditional medicine, while also offering opportunities for income generation through harvesting, processing, commercialization, and rural tourism. In the context of climate change, biodiversity loss, and increasing ecosystem degradation, wild fruit species represent multifunctional natural resources. Their conservation and sustainable use are essential for maintaining ecosystem functionality and promoting sustainable rural development. Full article

Against the backdrop of intensifying global climate change and water eutrophication, the increasing occurrence of Harmful Algal Blooms (HABs) poses a significant threat to aquatic ecosystems, human health, and socio-economic activities. The occurrence and development of HABs are complex processes governed by the interaction of physical, chemical, and biological factors. Therefore, timely and accurate monitoring is essential for early warning and scientific research. This paper comprehensively reviews recent advances in HAB monitoring technologies, with a focus on two core components: sensors and monitoring platforms. First, organized around key environmental parameters, it summarizes the principles, applications, and limitations of in situ sensors, such as multi-parameter water quality sondes, Imaging Flow Cyto-bots (IFCB), and Environmental Sample Processors (ESP), as well as laboratory-based analytical techniques such as HPLC-MS for measuring physical, chemical, and biological indicators. Second, it compares the technical characteristics of three major monitoring platforms (including field surveys, remote sensing, and autonomous systems) and discusses their potential for synergistic application. Finally, this review proposes a future framework for an integrated “Space–Air–Ground–Sea” intelligent monitoring network and explores possible pathways to address current challenges through cross-platform data fusion, sensor miniaturization, intelligentization, and artificial intelligence-driven decision support. This review aims to provide a comprehensive reference for the optimization and innovation of HAB monitoring technologies and to promote the development of the field toward greater integration, intelligence, and real-time monitoring capability. Full article

Background: Indoor Environmental Quality (IEQ) in housing plays a critical role in supporting health, comfort, and daily well-being, yet research and practice often address thermal, visual, acoustic, and air quality conditions in isolation. Objective: This systematic review synthesizes findings from peer-reviewed studies to examine how residential IEQ is experienced and shaped through interactions among physical building factors, environmental conditions, occupant behaviors, and socio-economic contexts. Methods: A systematic literature review was conducted following PRISMA guidelines, including 110 peer-reviewed studies published between 2015 and 2025. Data were extracted and coded from 10,838 quotations and corresponding measured environmental parameters, enabling cross-domain thematic synthesis across eight IEQ domains and four analytical themes. Results: The results show persistent perception-to-measurement gaps, particularly in ventilation usability, low-frequency noise, nighttime thermal conditions, and moisture control. Demographic factors, including age, life stage, health sensitivity, and housing tenure, influence how IEQ conditions are perceived. Integrated IEQ assessments indicate that sleep-critical spaces, moisture robustness, and simple, quiet control systems exert disproportionate influence on overall environmental satisfaction. Conclusions: The findings highlight the need to prioritize preventive design strategies addressing moisture, thermal comfort, acoustics, and lighting, while improving usability of environmental controls. Future research should expand longitudinal and cross-context studies, particularly in low-income communities, and strengthen links between IEQ performance and health outcomes. Healthy residential environments require understanding IEQ not only as a technical performance metric but as a spatial and social condition. Full article

International research and policy frameworks underscore the value of mandatory energy regulations in reducing energy demand and greenhouse gas (GHG) emissions in the built environment. However, Global South (GS) countries experience several challenges in effectively implementing building energy efficiency codes (BEECs), as codes are either absent, unevenly adopted or inconsistently enforced. A poor alignment with the specific climatic, socio-economic and construction realities further limits the potential of BEECs to support GS climate resilience. This research aims to identify opportunities to enhance building energy regulatory practices by exploring recent progress in the field. It also systematically evaluates existing mandatory BEECs in the GS to identify models and principles that could guide the development of more effective codes, specifically for GS countries without BEECs. It is hypothesised that the mandatory BEECs currently implemented in GS countries can be analysed using contextually relevant criteria to reveal common regulatory patterns, strengths, and shortcomings, thereby informing a climate-responsive framework suited to GS realities. This research implemented a two-tiered literature review. After determining the broad regulatory context, an exploratory review of the current state of the art in BEEC research was conducted. These publications (primarily 2016–2025) were obtained via a systematic query in Scopus. Following the exploratory review, this study performed a Systematic Quantitative Literature Review (SQLR) to assess mandatory BEECs from 18 GS countries. The findings reveal that BEECs are useful for delivering energy-efficient buildings in the real world. However, ample opportunities exist to improve their comprehensiveness in context and coverage. Improving regulatory implementation systems and structures, along with robust stakeholder engagement, can support better BEEC design and enforcement. To address the need for contextualised BEECs, the SQLR helped develop a taxonomy by comparing the mandatory codes. This research also introduces the Sustainable Level Indicator Model, Matrix, and Map (SLIM³) prototype, proposed as a decision-support tool, and hosted on an interactive online platform, thereby potentially contributing to real-world building energy regulatory practices. The SLIM³ tool organises the mandatory BEECs into a coherent, accessible framework that could assist GS decision-makers in benchmarking existing and new codes, identifying gaps and prioritising contextually appropriate improvements, thus contributing to a more resource-efficient built environment. Full article

As a strategic node of the Silk Road Economic Belt and a prototypical valley-type city, Lanzhou is subject to the dual constraints of rapid urbanization and an inherently fragile ecological foundation, making the coordination between urban expansion and ecosystem services a critical issue for regional sustainability. Drawing upon multi-temporal land use remote sensing datasets provided by the Chinese Academy of Sciences Resource and Environment Science Data Center, in conjunction with soil, meteorological, and socio-economic data, this study integrates a land use transition matrix, the InVEST model, a modified coupling coordination degree model, and the geographic detector to comprehensively examine land use dynamics, the spatiotemporal evolution of urban expansion, and the spatial heterogeneity of ecosystem services (i.e., carbon storage, water yield, habitat quality, and soil conservation) in Lanzhou. In addition, the coupling coordination relationship and its underlying driving mechanisms are systematically explored. The results demonstrate the following: (1) Between 1980 and 2020, urban land area in Lanzhou increased from 103.87 km² to 286.83 km², accounting for 2.17% of the total area, with cropland constituting the dominant source of expansion and exhibiting a fluctuating “high–low–high” conversion trajectory. (2) Ecosystem services exhibit pronounced spatial heterogeneity, with carbon storage and habitat quality displaying a pattern of “low in the southeast and high in the northwest”, water yield showing an increasing gradient from southeast to northwest, and soil conservation characterized by “lower values in central areas and higher values in peripheral regions”; (3) Urban expansion has accelerated significantly, with Yongdeng County and Gaolan County emerging as principal expansion hotspots during 2010–2020. (4) The dominant driving mechanism gradually shifted from natural factors to the synergistic interaction between natural and socioeconomic factors, and the interaction among driving factors markedly enhanced the explanatory power for ecosystem service evolution. (5) The coupling coordination degree has transitioned from widespread imbalance to a spatially differentiated pattern, characterized by relatively coordinated conditions in peripheral areas and persistent imbalance within the central urban core. These findings provide a robust scientific basis for territorial spatial optimization and the synergistic development of ecological and economic systems in valley-type cities, and offer important implications for sustainable development in arid and semi-arid regions. Full article

Urban community parks are important public open spaces (POSs) that support residents’ quality of life (QoL) by aiding recreation, social interaction, and physical activity. However, evidence on how to design and assess sustainable POS in Saudi Arabia remains limited, particularly in relation to the country’s hot–arid climate, socio-cultural context, and emerging urban development priorities. This study aims to develop a context-sensitive framework for the design and assessment of sustainable POSs (a scope of urban community parks) in Saudi Arabia using a mixed-methods approach. The study combined: (i) a structured review of the literature on POSs’ sustainability and QoL/subjective well-being (SWB); (ii) naturalistic field observations in two community parks in Al-Khobar (Shells Park and Prince Ibn-Jalawy Park); (iii) an on-site questionnaire survey of park users assessing satisfaction and self-reported well-being (n = 89); and (iv) structured expert interviews to refine and prioritize the framework elements (n = 15). The quantitative analysis included descriptive statistics, Pearson correlation analysis, and reliability testing using Cronbach’s alpha, the Mann–Whitney U test, and the Kruskal–Wallis test to explore the associations between perceived park attributes, user satisfaction, and self-reported well-being. The framework was iteratively refined through triangulation via the literature, field evidence, user feedback, and expert judgement, while expert responses were synthesized using weighted mean scores, simple ranking system, and the Relative Importance Index (RII). The findings indicate that shading and thermal comfort, safety, accessibility, maintenance, and cultural alignment are the most important design priorities in the Saudi Arabian context. The empirical assessment also highlights recurrent shortcomings in the selected parks, particularly inadequate heat mitigation measures, inconsistent maintenance, limited recreational infrastructure, and the weak integration of smart support features. Based on this triangulated evidence, the study proposes a framework comprising nine categories, 43 sub-categories, with 137 indicators organized across environmental, socio-cultural, economic, and smart-enabler considerations. The framework provides a practical and context-sensitive tool for evaluating existing parks, prioritizing interventions, and guiding future community park development in support the Quality-of-Life Programme of Saudi Vision 2030. Full article

The study investigates the interrelationship between the performance of the regional economy in Italy and the multidimensionality of wellbeing, as defined by the ISTAT Benessere Equo e Sostenibile (BES) model. Based on panel data from 19 Italian regions and 2 autonomous provinces—Trentino and Bolzano (2012–2023)—the research aims to explore whether there is a link between regional GDP and the three BES dimensions: Benessere (B), Equità (E), and Sostenibilità (S). The innovative contribution of this paper is not the creation of a novel theoretical model, but a multilayered empirical approach that combines panel data methods, machine learning, and clustering. This approach makes it possible to reveal nonlinearities, complex interactions, and regional heterogeneity in BES–GDP relationships. The analysis of the Benessere dimension based on k-Nearest Neighbors reveals nonlinear dynamics related to health, mobility, security, digital access, and socio-economic conditions. Furthermore, cluster analysis identifies territorial development regimes according to the Benessere dimension. The Equità dimension is estimated using boosting regression and clustering models that emphasize the role of income, poverty risk, healthcare pressure, labour-market participation, youth exclusion, deprivation, and access to essential services. Finally, the Sostenibilità dimension is explored using boosting regression and random forest models to estimate interactions among environmental quality, climate stress, energy transition, innovation, digital skills, service reliability, and regional economic performance. The findings demonstrate a structural connection between well-being, equity, sustainability, and the economic performance of Italian regions. The results also confirm the hypothesis that Italy has multiple development regimes that differ geographically. Full article

Digital financial inclusion (DFI) plays an increasingly important role in expanding financial participation, improving access to payment systems, and supporting inclusive economic development. Yet substantial gender gaps in DFI remain a persistent challenge in many developing economies, including Nigeria. This study examines whether these gaps mainly reflect structural inequalities, particularly unequal access to digital connectivity and economic opportunity, rather than clear evidence of gender-specific behavioral responses between men and women. Using nationally representative microdata from the 2025 Global Findex survey, we analyze three sequential dimensions of DFI: digital account ownership, the use of any digital payment, and merchant digital payments. The empirical analysis combines logit and probit models with nonlinear Fairlie decompositions and interaction analysis focusing on education, income, employment, and internet access. Descriptive results show clear raw gender gaps at the earlier stages of digital financial participation. However, once socioeconomic characteristics and digital access are taken into account, the gender coefficient becomes statistically insignificant across the main specifications. The decomposition results indicate that between 79% and 94% of the observed gaps are statistically attributable to differences in endowments, with internet connectivity and labor market participation emerging as the most important contributors. The interaction results further show that education and connectivity are positively associated with digital financial participation for both men and women, with no clear evidence that these associations differ systematically by gender. Overall, the findings suggest that gender gaps in DFI in Nigeria are mainly associated with structural inequalities rather than clear evidence of gender-specific behavioral responses. The results carry important implications for financial inclusion policy, suggesting that efforts to narrow these gaps should consider not only wider digital access but also stronger support for women’s economic participation within a broader and more inclusive digital financial transition. Full article

This study applied a syndemic framework to chikungunya virus (CHIKV) infection during the 2014–2015 Colombian epidemic, integrating biological and social determinants. Methods: A community-based cohort of 279 serologically confirmed adults from six cities was analyzed. Clinical, sociodemographic, and cytokine data were evaluated using multilevel and multivariate statistical approaches. Results: Among 279 patients, 141 (50.5%) met World Health Organization (WHO) criteria for acute CHIKV infection. The cohort was predominantly female and of lower socioeconomic status (SES). The most frequent manifestations were arthralgia (91%), fatigue (58%), fever (50.5%), myalgia (45.9%), and rash (45.2%). Multivariate models identified IL-15, IL-17A, IL-12p40, MCP-1, and MIP-1α as significant correlates of fever, rash, and myalgia. Socioeconomic and ethnic factors influenced cytokine expression; Caucasian patients showed higher proinflammatory cytokine levels than Afro-American patients. Lower SES was associated with greater symptom burden. Network analyses revealed distinct immune signatures linking biological responses with clinical and demographic variables. Conclusion: Immune responses, clinical manifestations, and social disadvantages interact significantly in CHIKV infection. These findings support a syndemic model in which socioeconomic vulnerability amplifies disease impact, highlighting the need for integrated biosociological public health strategies, particularly targeting populations with low socioeconomic status. Full article