Search Results (2,981)

Amidst the accelerating trend of population aging, addressing regional disparities in basic elderly care services (BECS for short) and identifying the key obstacles to their development have become crucial prerequisites for development. Taking urgent transformation measures is indispensable for enhancing the quality of fundamental senior care provisions and advancing the attainment of the United Nations Sustainable Development Goals (SDGs for short) by 2030. However, the extant literature does not have a sufficient understanding of the evolution of differences, spatial correlations, and sources of obstacles. Therefore, this paper takes the period from 2021 to 2023 as the investigation period and comprehensively applies the entropy weight method, Dagum Gini coefficient, kernel density estimation, Moran Index, and obstacle degree model to conduct a systematic analysis of BECS in China. Quantitative results obtained from the research demonstrate that the level of BECS in China follows the pattern of eastern > western > central > northeastern regions. The overall difference slightly increases, and the differences within and between regions vary. The kernel density estimation results are highly consistent with the current landscape of the level of BECS in China, and the spatial correlation and aggregation characteristics are obvious. It was also found that the main obstacles in the quasi-measurement layer (including the indicator layer) were concentrated in the dimension of welfare subsidies. Based on this, a policy combination proposal is put forward in terms of strengthening the construction of a multi-subject supply network, promoting the cross-regional coordinated development of human, financial, and material factors, and enhancing the government’s governance capacity, with the aim of increasing Chinese contributions to improving the level of BECS and achieving the United Nations 2030 Sustainability Goals on schedule. Full article

Cancer is one of the biggest health burdens for women in the Middle East and North Africa (MENA), with the incidence of breast, cervical and colorectal cancer on the rise. Although preventive measures such as the HPV vaccination and population-based screening are available, access to them remains very unequal. Women in rural, low-income and refugee communities face additional barriers, cultural stigmatisation, low health literacy, gender norms and fragile health systems, leading to delayed diagnoses and poorer outcomes. This review summarises the results of 724 peer-reviewed publications to assess the current situation of cancer screening in MENA and Mediterranean countries. The studies were classified into four dimensions: cancer type (breast, cervical, colorectal), behavioural constructs (awareness, uptake, education), vulnerability factors (e.g., migrants, refugees, low-literacy groups), and geography (indigenous MENA populations versus diaspora and Mediterranean immigrant communities). The results show large inequalities in access and participation due to fragmented policies, socio-cultural resistance and infrastructure gaps. Nevertheless, promising approaches are emerging: community-led outreach, mobile screening programmes, AI-assisted triage and culturally appropriate digital health interventions. Comparisons between the local and diaspora populations make it clear that systemic and cultural barriers persist even in well-equipped facilities. Closing the screening gap requires a culturally sensitive, digitally enabled and policy aligned approach. Key priorities include engaging religious and community leaders, promoting men’s engagement in women’s health and securing sustainable funding. With coordinated action across all sectors, MENA countries can build inclusive screening programmes that reach vulnerable women and reduce preventable cancer mortality. Full article

Context: Paediatric palliative care in Romania is underdeveloped and unevenly distributed, which creates major difficulties in accessing services for children with life-limiting illnesses and their families. The lack of a dedicated national strategy, the shortage of specialised staff, and socio-economic barriers exacerbate the vulnerability of these groups. Objectives: This study aimed to explore parents’ and caregivers’ experiences, to analyse the perspectives of public institutions and NGOs involved in supporting these children, and to identify the main barriers and facilitators in accessing paediatric palliative care. Material and Method: Given that all data were collected exclusively through focus group discussions, this study employed a qualitative design based on three focus groups guided by a semi-structured interview guide. The analysis was conducted using MAXQDA software, which enabled the coding and synthesis of emerging themes. Participants were parents/caregivers of children with life-limiting illnesses, representatives of public institutions, and members of relevant NGOs in Bacău County, Romania. Purposive sampling was used to capture diverse and experience-based perspectives, resulting in a total of 24 participants across three focus groups—parents and caregivers (n = 11), public institution representatives (n = 7), and NGO representatives (n = 6). No individual semi-structured interviews were conducted. Results: The analysis highlighted a complex typology of medical, emotional, social, educational, and spiritual needs of children and their families. Parents reported experiences of abandonment in the curative system, emphasising the importance of pain control, safety, and community support. Public institutions acknowledged the lack of skills and inter-sectoral coordination, while NGOs pointed to structural barriers and the low visibility of these children. Major needs include access to specialised care, psychological support, respite services for carers, financial and administrative assistance, education, and spiritual counselling. A significant obstacle is the lack of up-to-date statistical data needed to inform public policy. Conclusions: Paediatric palliative care should be considered a national priority through the development of a dedicated strategy, the expansion of specialised services, and the strengthening of partnerships between the public and non-governmental sectors. An integrated, child- and family-centred approach addressing the medical, social, emotional, and spiritual dimensions of care is essential. The results highlight the need for continuous staff training, information campaigns, and community support mechanisms to reduce inequalities and improve the quality of life of children with life-limiting illnesses. Full article

The professional development of English as a Foreign Language (EFL) education has been converted from rigid hierarchical models to more flexible and context-sensitive frameworks. This study introduces ego-centred network card analysis as a new methodology to investigate how Indonesian university EFL teachers create and negotiate their professional identities. The data were collected from 11 experienced EFL teachers. The network cards were analysed to find the nodes and sectors of professional identity and development. Drawing on constructivist and sociocultural perspectives, the study findings indicated that the formation is influenced by relational, emotional and institutional influences, and that family support, mentoring, and career goals alleviate pressures such as workload, publication demands, and financial instability. The findings highlight identity as both a product and a driving force for professional development, extending sociocultural theories by visualizing hidden dimensions of teachers’ networks. Methodologically, this study demonstrates the value of visual-relational tools in capturing complexity beyond interviews or surveys. The results suggest that, in practice, teacher education and policy must integrate structured mentorship, peer reflection, and recognition of emotional work in order to maintain professional growth. Full article

Traditional villages are integral to the broader context of global socio-economic transition. This study developed a resilience evaluation model centred on built-environment indicators. This model integrates the community, economy, ecology, and culture dimensions. Clarifying the typology and key driving factors of traditional village built environment resilience can effectively activate the inherent potential of villages. The study provides a holistic approach to identifying traditional village built environment resilience types and analysing the key influencing factors. Utilising a method combining the SOM-K-means clustering model and the interpretable XGBoost-SHAP model, the study provides a holistic analytical framework for identifying traditional village built environment resilience types and quantifying the nonlinear action characteristics of various indicators across different types. Taking the Yangtze River Delta (YRD) region as an example, the study demonstrates that traditional villages can be categorised into six potential resilience types, with differentiated key indicator combinations across these types. Furthermore, the nonlinear action characteristics and operational thresholds of the same key indicator differ significantly across various traditional village types. For instance, at medium-to-high threshold levels, the accessibility of cultural buildings contributes significantly to the sustainability of culture–service-driven villages but, conversely, becomes a detriment in ecology-cultural composite archetypes. Similarly, in industry–creative driven villages, once the density of cultural and creative spaces reaches a specific threshold, it exerts a significant positive effect on traditional village development and stabilises into a sustained positive state. However, in ecology–agriculture–organisation-driven villages, exceeding a certain threshold in the density of cultural and creative spaces has a significant negative influence. The results provide an analytical framework for the resilience typology and influencing factors of traditional village built environments, consequently offering a scientific basis for formulating refined, differentiated policies for traditional villages. Full article

In this study, we examine the impact of government green subsidies on corporate ESG performance. We employ the method of double machine learning for causal inference. We use all A-share listed companies in China from 2013 to 2023 as the research sample. After excluding financial and insurance companies, those in ST/*ST/PT status, and those with missing key indicators, we ultimately obtain 2337 sample observations. Our baseline results based on double machine learning reveal government green subsidies significantly enhance corporate ESG performance. The findings suggest that this enhancement occurs notably through the mediating variables of digital technology innovation and technology conversion efficiency. We also introduce heterogeneous dimensions such as the level of digital inclusive finance, the intensity of environmental regulations, and the scale of enterprises. Meanwhile, we adopt multiple robustness test methods, including changing the dependent variable, excluding data from special years, controlling for exogenous policy shocks, using instrumental variable methods, and resetting the double machine learning model—adjusting the sample partition ratio from the original 1:4 to 1:9 and replacing the prediction algorithm from random forest to gradient boosting, lasso regression, and ensemble machine learning methods—to ensure the reliability and scientific nature of the research conclusions. Additional tests indicate that the regression coefficient remains positive and is significant, indicating the robustness of our conclusions. This research offers implications for further optimizing the design of government green subsidy policies, and to promote the improvement of enterprises’ ESG performance and economic green transformation. Full article

Against the backdrop of China’s transition from the eradication of absolute poverty toward the pursuit of common prosperity, equitable access to energy has become an increasingly important policy concern. This study develops a multidimensional framework to assess energy poverty from three interrelated dimensions: energy use level, energy structure, and energy capability. Using panel data for 30 provincial-level regions from 2005 to 2020, a provincial energy poverty index (EPI) is constructed based on the entropy-weighting approach. The spatial and temporal dynamics of energy poverty are examined using Moran’s I, the Dagum Gini decomposition, kernel density estimation, and spatial Markov chain analysis. The results reveal several key patterns. (1) Although energy poverty has declined nationwide, it remains pronounced in parts of western, central, and northeastern China. (2) Energy poverty exhibits significant spatial clustering, with high-poverty clusters concentrated in resource-dependent regions such as Shanxi and Inner Mongolia, while low-poverty clusters are mainly located along the eastern coast. (3) Regional disparities follow an inverted U-shaped trajectory over time, with east–west differences constituting the primary source of overall inequality. (4) Moreover, the evolution of energy poverty displays strong path dependence and club convergence. These findings highlight the need to strengthen dynamic monitoring and governance mechanisms, promote region-specific clean energy development, and enhance cross-regional coordination to support energy security and green transformation under China’s “dual-carbon” objectives. Full article

Contemporary cities constitute both the primary site where the climate crisis manifests its most evident impacts and the privileged laboratory for testing strategies of adaptation and resilience. However, the growing emphasis on “climate neutrality” policies risks obscuring the social dimension of urban regeneration processes, thus generating new imbalances and forms of exclusion. This paper offers a critical reflection on the role of urban planning beyond climate neutrality, reorienting it towards a perspective of climate justice capable of integrating ecological transition goals with those of social and territorial cohesion. The research adopts a mixed-method approach, combining theoretical and documentary analysis with empirical case comparison, to investigate the relationship among urban regeneration, urban welfare, and spatial inequalities. The study aims to identify strategies for preventing climate gentrification, a phenomenon in which adaptation and mitigation measures—if not accompanied by adequate redistributive mechanisms—produce socio-spatial displacement effects that exclude the most vulnerable communities from the environmental benefits generated. The comparative analysis of two international case studies—Little Haiti (Miami) and the Green Corridors of Medellín (Colombia)—reveals two contrasting trajectories of the ecological transition: a regressive one, driven by market logics and real-estate valorization, and a progressive one, grounded in principles of equity, participation, and inclusive distribution of environmental benefits. Full article

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome prediction. It does so by leveraging deep learning and computer vision, as well as AI-driven platforms such as ERICA, iDAScore, and IVY where the goal is to address the limitations of traditional embryo assessment. Key amongst them are the issues of subjectivity, labor intensity, and limited predictive power. Despite rapid technological progress, the integration of AI into routine IVF practice faces key challenges. These are issues related to clinical validation, ethical dilemmas, and workflow adaptation. Rationale/Objectives: This review synthesizes current evidence to evaluate the role of AI in IVF, focusing on six critical dimensions: (1) the evolution of AI from traditional embryology to algorithmic assessment, (2) clinical validation and regulatory considerations, (3) limitations and ethical challenges, (4) pathways for clinical integration, (5) real-world applications and outcomes, and (6) future directions and policy recommendations. The objective is to provide a comprehensive roadmap for the responsible adoption of AI in reproductive medicine. Outcomes: AI demonstrates significant potential to improve the precision and efficiency of IVF. Studies report that AI models can achieve 10 to 25% higher accuracy in predicting embryo viability and implantation potential compared to traditional morphological assessment by embryologists. This enhanced predictive power supports more consistent embryo ranking, facilitates elective single-embryo transfer (eSET) strategies, and is associated with 30 to 50% reductions in embryologist workload per embryo cohort. Early adopters report promising trends. However, large-scale randomized controlled trials have yet to conclusively demonstrate a statistically significant increase in live birth rates per transfer compared to expert embryologist selection. The most immediate and evidenced value of AI lies in hybrid decision-making models. This is where it augments embryologists by providing data-driven, objective support, thereby standardizing workflows and reducing subjectivity. Wider Implications: The sustainable integration of AI into IVF banks on three key aspects: robust evidence generation, interdisciplinary collaboration, and global standardization. To foster these, policymakers ought to establish regulatory frameworks for transparency and bias mitigation. On their part, clinicians need training to interpret AI outputs critically. Ethically, safeguarding patient trust and equity is non-negotiable. Future innovations, mainly AI-enhanced genomics and real-time monitoring, could further personalize care. However, their success depends on addressing current limitations. By balancing innovation with ethical vigilance, AI holds the potential to revolutionize IVF while upholding the highest standards of patient care. Full article

Climate change education (CCE) is increasingly recognized as a key lever for responding to the climate crisis, yet its implementation in schools often remains fragmented and weakly transformative. This review synthesizes international research on CCE in secondary education, focusing on four interconnected domains: students’ social representations of climate change (SRCC), curricular frameworks, teaching practices and teacher professional development, and emerging pathways towards transformative, justice-oriented CCE. A narrative review of empirical and theoretical studies reveals that students’ SRCC are generally superficial, fragmented and marked by persistent misconceptions, psychological distance and low perceived agency. Curricular frameworks tend to locate climate change mainly within natural sciences, reproduce deficit-based and behaviorist models and leave social, political and ethical dimensions underdeveloped. Teaching practices remain predominantly transmissive and science-centered, while teachers report limited training, time and institutional support, especially for addressing the affective domain and working transdisciplinarily. At the same time, the literature highlights promising directions: calls for an “emergency curriculum” and deeper curricular environmentalization, the potential of socio-scientific issues and complexity-based approaches, narrative and arts-based strategies, school gardens and community projects, and growing attention to emotions, hope and climate justice. Drawing on a narrative and integrative review of empirical and theoretical studies, the article identifies recurrent patterns and gaps in current CCE research and outlines priorities for future inquiry. The review argues that bridging the knowledge–action gap in schools requires aligning curriculum, pedagogy and teacher learning around four key principles—climate justice, collective agency, affective engagement and global perspectives—and outlines implications for policy, practice and research to support more transformative and socially just CCE. Full article

Evaluating rural households’ subjective well-being (SWB) and identifying its determinants is crucial for rural sustainable development. This study takes Diqing Prefecture in the Tibetan region of China as a case, aiming to address two key research questions: (1) How do livelihood assets affect subjective well-being (SWB)—directly or indirectly—through the mediating role of the agricultural-income proportion? (2) Do these effects vary across different livelihood strategies? A questionnaire survey was administered to 489 randomly selected rural households in mid-2022. Two index systems were constructed: one for livelihood assets based on the Sustainable Livelihood Framework and another for SWB based on the Millennium Ecosystem Assessment. A subgroup Tobit regression model was utilized to analyze the heterogeneous effects. The results revealed deficiencies in SWB regarding basic material for a good life and health. Human, financial, and social assets are positively associated with SWB. However, natural assets directly negatively impact SWB across dimensions of basic material, security, and freedom, although the negative effect is masked by the mediating effect of farming livelihood strategies. Notably, human assets’ positive influence significantly strengthens with the agricultural income proportion rising. Whether physical, financial, and social assets positively affect SWB depends on farm work participation. These evidence-based findings contribute to a better understanding of the heterogeneous role of sustainable livelihoods in affecting rural households’ subjective well-being and highlight the need for policymakers to design diverse, targeted policies to support rural development. Full article

Over the past two decades, escalating climate crises, geopolitical conflicts, and pandemics have intensified the frequency and severity of disasters, exposing severe vulnerabilities in global food systems. In this pressing context, disaster nutrition emerges as a vital domain of intervention. However, existing academic literature and field practices often address this topic through fragmented, single-axis perspectives. Nutritional physiology, food technology, humanitarian logistics, and policy–ethics frameworks tend to progress in parallel yet disconnected tracks, which results in a lack of holistic models that adequately reflect field realities. The urgency of this issue is underscored by the latest global data. In 2023 alone, disasters resulted in over 86,000 deaths, a significant increase from the preceding two-decade annual average. Furthermore, the 2025 Global Report on Food Crises reveals that 295.3 million people faced high levels of acute food insecurity in 2024, marking the sixth consecutive year this number has risen. This escalating crisis highlights the inadequacy of fragmented approaches and necessitates the development of an integrated framework for disaster nutrition. To address this fragmentation, this study redefines disaster nutrition as a multi-layered, integrated food system challenge. Based on a comprehensive literature analysis, it proposes an “Integrated Disaster Food System Model” that brings these different dimensions together within a common framework. The model is built on four main components: (i) nutritional requirements and vulnerable groups (such as infants, older adults, pregnant individuals, and populations with chronic diseases requiring special diets); (ii) product design, technology, and packaging (balancing shelf life, nutritional value, cultural acceptability, and sensory attributes, including innovative components such as microalgae and fermented foods); (iii) logistics, storage, and distribution systems (centralized storage versus localized micro-warehouses, as well as the use of drones and digital traceability technologies); and (iv) policy, regulation, ethics, and sustainability (the applicability of the Sphere Standards, fair distribution, food waste, and environmental impact). By emphasizing the bidirectional and dynamic interactions among these components, the model demonstrates how decisions in one domain affect others (for example, how more durable packaging can increase both logistics costs and carbon footprint). The study highlights the risks and cultural mismatches associated with a “one-size-fits-all high-energy food” approach for vulnerable groups and argues for the necessity of localized, context-specific, and sustainable solutions. In conclusion, the article posits that the future of disaster food systems can only be shaped through a holistic approach in which interdisciplinary collaboration, technological innovation, and ethical–environmental principles are integrated into the core of policy-making. Full article

This study employs Gaussian kernel principal component analysis to construct a composite indicator of environmental behavior willingness from nine dimensions. Using multiple categorical ordered linear regression models and their interaction models, it examines the differential influence mechanisms of social strata (economic status, education, social prestige) and environmental perception from gender, inter-provincial, and regional perspectives. Key empirical findings are the following: (1) Environmental willingness formed within the same social stratum based on shared perception levels shows consistent characteristics, with no significant gender differences observed. (2) Higher education deepens understanding of environmental policies, promoting the shift from awareness to willingness. However, it also enhances recognition of environmental complexity, which may foster a situational sense of powerlessness, often channeled into systemic advocacy rather than the belief that individual actions are insignificant. (3) Regional disparities are evident. For example, the perception of air pollution positively correlates with willingness in Hebei and Jiangsu but negatively in Beijing and Liaoning. (4) The middle social stratum in eastern and central regions shows more stimulable environmental willingness, contributing to sustainable regional environmental engagement. Conversely, in the western region, improving the economic status of lower- and middle-stratum residents is key to significantly enhancing the sustainability of overall regional willingness. This study reveals the varied drivers of environmental willingness by integrating multidimensional indicators and a social-class perspective, highlighting the regional role of environmental perception and advancing theory on socio-cognitive interactions in environmental sociology. Practically, it provides evidence for differentiated policy design, suggesting tailored incentives across social strata and regions, including measures to address “action paralysis” among the highly educated and to combine economic support in western China for fostering sustainable public environmental participation. Full article

The transition to a low-carbon economy is profoundly reshaping European labour markets, creating both opportunities for sustainable employment and challenges for regions reliant on carbon-intensive sectors. Assessing how prepared EU Member States are for this shift remains difficult due to the lack of unified evaluation tools. This study introduces the Green Labour Market Readiness Index (GLMRI)—a composite measure assessing the adaptability of national labour markets to the energy-driven green transformation in nine EU countries: Germany, France, Sweden, Spain, Italy, Greece, Poland, Romania, and the Czech Republic. The index integrates five dimensions—education and skills, investment and infrastructure, policy and institutional quality, labour market structure, and innovation—based on harmonized data from 2010 to 2024. Panel econometric models (Fixed and Random Effects), combined with Hausman tests, are used to examine how structurally independent external energy-system characteristics, institutional capacity, and macro-structural labour-market conditions are associated with observed variation in labour-market readiness, as captured by the GLMRI composite outcome. Machine learning algorithms (Random Forest, XGBoost, LSTM) are employed to forecast readiness trajectories until 2040 under alternative policy scenarios. Results reveal persistent asymmetries between Northwestern and Southeastern Europe, showing that successful energy transition is closely associated not only with investment and innovation but also with human capital and governance quality. These associations are interpreted as diagnostic rather than causal, highlighting how external structural conditions shape the translation of energy-transition pressures into differentiated labour-market outcomes. The GLMRI provides a methodological and policy-relevant framework, helping decision-makers prioritize resources and design measures that make Europe’s energy transition sustainable, inclusive, and equitable. Full article

Despite growing technological and economic viability, the adoption of solar energy in the United States remains low. This research synthesizes 96 peer-reviewed publications from 2000 to 2024 to investigate how public perceptions, user psychology, institutional setups, and socioeconomic contexts shape solar energy adoption decisions in the United States. Drawing on a PRISMA systematic review of publications gathered from Scopus and Web of Science databases, the study reveals that solar adoption is influenced not only by environmental concern and perceived economic benefits but also by institutional trust, social norms, cognitive biases, and demographic characteristics. Key findings highlight that while higher income and education levels enable adoption, marginalized communities face persistent barriers, including institutional distrust, limited awareness, and constrained access to financing. Residential rooftop solar projects receive higher public approval than utility-scale developments, with agrivoltaics systems emerging as a promising middle ground. This review identifies critical gaps in public awareness and institutional credibility, calling for integrated policy responses that combine financial incentives with inclusive engagement strategies. By emphasizing the socio-behavioral dimensions of energy transitions, it offers actionable insights for policymakers, energy planners, and researchers aiming to broaden solar accessibility and equity. It underscores the need for future research on identity-driven adoption behavior, participatory energy planning, and depoliticized communication to bridge the intention-action gap and accelerate the just transition to solar energy. Full article