Search Results (234)

Background: The COVID-19 pandemic significantly disrupted patterns of physical activity and participation in mass sporting events, with recreational runners in Latin America among the most affected. In Colombia, pre-existing inequalities in access to sport further exacerbated these impacts. Nevertheless, evidence on post-COVID-19 impact and recovery experiences among regional runners remains limited. Objective: We examined the sociodemographic profiles, athletic experience, and perceptions of COVID-19-related impact and recovery among participants in the 2023 Medellín Marathon, and to assess differences by educational attainment, employment status, age group, and geographic origin. Methods: A cross-sectional descriptive study was undertaken involving 2486 registered marathon runners. An ad hoc questionnaire assessed COVID-19 symptoms and sequelae, perceived respiratory and physical limitations, fears associated with group exercise, and self-reported recovery. Analyses included descriptive statistics, bivariate comparisons and one-way ANOVA tests. Results: Older participants, retirees and those with lower educational levels reported significantly greater COVID-19 impact, longer recovery periods and higher perceived physical and respiratory limitations. In contrast, younger runners and those with a college education showed more complete physical recovery and attributed protective benefits, such as improved cardiorespiratory function and a lower incidence of respiratory symptoms, to their training. Additionally, runners originating from smaller municipalities and other Latin American countries reported higher levels of impact and lower perceptions of recovery. Conclusions: Post-COVID-19 effects among marathon runners are not uniform but vary according to sociodemographic and contextual factors. These findings underscore the importance of tailored support and readaptation strategies—particularly for vulnerable subgroups—to ensure their safe and equitable return to mass endurance events. Full article

Background: Scientific evidence plays a critical role in informing public health decision-making processes. However, the extent, nature, and effectiveness of its use remain uneven across contexts. Despite the increasing volume of literature on the subject, previous syntheses have often suffered from narrow thematic, temporal, or geographic scopes. Objectives: This study undertook a comprehensive systematic literature review spanning 50 years to (i) synthesise current knowledge on the use of scientific evidence in public health decisions, (ii) identify key determinants, barriers, and enablers, (iii) evaluate implementation patterns, and (iv) propose future directions for research and practice. Methods: We adopted the PRISMA model (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Moreover, we researched three large databases (Web of Science, Embase, and PubMed), and this study focused on articles published in the English and French languages between January 1974 and December 2024. Studies were analysed thematically and descriptively to identify trends, patterns, and knowledge gaps. Results: This review reveals a growing corpus of scholarship with a predominance of qualitative studies mainly published in public health journals. Evidence use is most frequently analysed at the national policy level. Analyses of the evolution of scientific production over time revealed significant shifts beginning as early as 2005. Critical impediments included limited access to reliable and timely data, a lack of institutional capacity, and insufficient training among policy-makers. In contrast, enablers encompass cross-sector collaboration, data transparency, and alignment between researchers and decision-makers. Conclusions: Addressing persistent gaps necessitates a more nuanced appreciation of interdisciplinary and contextual factors. Our findings call for proactive policies aimed at promoting the use of scientific evidence by improving the accessibility of health data (addressing the absence or lack of data, as well as its reliability, timeliness, and accessibility), and by training decision-makers in the use of scientific evidence for decision making. Furthermore, our findings advocate for better alignment between the agendas of healthcare professionals (e.g., data collection), researchers (e.g., the selection of research topics), and decision-makers (e.g., expectations and needs) in order to develop and implement public health policies that are grounded in and informed by scientific evidence. Full article

This study examines two proximate yet theologically and spatially disparate religious spaces in Seoul: the Jeoldusan Martyrs’ Shrine (Korean: 절두산 순교 성지; hereafter “Jeoldusan Martyrs’ Shrine”) and the Yanghwajin Protestant Cemetery (Korean: 양화진 묘원; hereafter “Yanghwajin Cemetery”). We propose the concept of isomorphic heterotopias and discuss the logic of intersecting memories. Drawing on Foucault’s concept of heterotopia and cultural memory theory, the study finds that the Jeoldusan Martyrs’ Shrine, through architectural enclosure, the exhibition of relics, and pilgrimage rituals, foregrounds the vertical redemption of martyrs’ flesh and faith, reinforcing ecclesiastical discourse and collective salvation narratives. In contrast, at Yanghwajin Cemetery, through dispersed tombstone layouts, egalitarian epitaph inscriptions, and public commemorative activities, the study finds that the site presents the dialectic of the martyr spirit within a secular spiritual space and individual testimonies. Despite their spatial heterogeneity, their geographic proximity generates a dialogical memory field: the vertical sacrality of the shrine is refracted through the cemetery’s horizontality, while the cemetery’s public spirit resonates with the shrine’s liturgical framework. This dialogical memory field, shaped by shared physical environments and common public narrative platforms—generates a long-term coexistence without convergence, producing a spatial relationship of “non-integrative entanglement” born of antagonism. At the same time, these sites are not isolated spatial fragments; rather, through urban governance, they are woven into the same memory politics network, forming an “isomorphic heterotopia.” Through politically inflected discursive narratives, both sites facilitate multidirectional flows of memory, preserving their respective “canons” while re-contextualizing each other within the same urban memory network. In doing so, they engage in an ongoing process of mutual rereading and co-construction, producing a re-contextualization of spatial memory and shaping a “composite historical sensibility” that, in turn, contributes to the city’s character. Full article

Canine distemper virus (CDV) is a multi-host morbillivirus whose evolution and host-switching capacity are largely determined by its hemagglutinin (H) gene. To reconsider the molecular evolution of this critical gene, we performed comprehensive phylogenetic, selection, and structural analyses on a curated dataset of 68 representative global H gene sequences. Our phylogenetic reconstruction confirmed the segregation of sequences into distinct, geographically associated lineages. To provide stronger evidence for viral adaptation, we performed a site-specific selection analysis, which identified 15 amino acid sites in the H protein undergoing significant episodic positive selection. Crucially, the majority of the known SLAM and Nectin-4 receptor-binding residues were found to be among these positively selected sites. We further contextualized these findings by mapping the sites onto a 3D homology model of the H protein, which confirmed their location on the exposed surfaces of the receptor-binding domain. This compilation provides quantitative evidence that the key functional regions of the H protein are direct targets for adaptive evolution, which has significant implications for understanding host tropism and the ongoing challenge of vaccine mismatch. Full article

Introduction: Polio supplementary immunisation activities (SIA) are implemented to rapidly increase vaccination coverage and interrupt the transmission of poliovirus in a specified geographical area. Polio SIA complements routine immunisation and is crucial for the eradication of the disease by increasing population immunity. However, several contextual factors (i.e., implementation determinants) can influence the success or failure of polio SIA implementation; as such, understanding their dynamics can enhance proactive planning for practice improvement. This study aimed to explore and map the contextual factors of polio SIA implementation in the African region using a critical systems thinking approach. Methods: A rapid review of published and grey literature was conducted. The search included the Global Polio Eradication Initiative library for programmatic reports and two databases (PubMed and Google Scholar). Data extraction was performed using a structured tool. Thematic analysis was performed to categorise the identified contextual factors according to the domains and constructs of the Consolidated Framework for Implementation Research (CFIR). Then, a causal loop diagram (CLD) was used to map the linkages between the identified factors. Results: A total of seventy-eight contextual factors across the five CFIR domains were identified: three for innovation, twenty for outer setting, sixteen for inner setting, twenty-six for individuals, and thirteen for the implementation process. A system map of all the factors using CLD revealed multiple contingent connections, with eleven reinforcing loops and four balancing loops. Conclusions: This study identified the multilevel nature of the contextual factors that influence polio SIA, including their dynamics. The integration of CLD and CFIR in this study offers critical insights into the potential feedback loops that exists between the contextual factors which can be used as leverage points for policy and practice improvements, including tailoring strategies to enhance polio campaign implementation effectiveness, especially with the expanded use of the novel Oral Polio Vaccine type 2 (nOPV2) across countries in the region. Full article

The concept of governance has gained increasing attention across various fields of study. However, its application within the specific context of educational policies, particularly within compulsory public education, remains fragmented and underexplored. To answer the questions “How is governance conceptualized in the context of the compulsory public education system?” and “What contributions to future research emerge from this review?”, 32 peer-reviewed articles published in open-access journals between 2019 and 2023 were extracted from the Web of Science, Scopus, and ERIC databases and selected following PRISMA guidelines. Results from this systematic literature review analysis suggest a sustained yet moderate interest in the field, as evidenced by the reviewed publications, different theoretical and conceptual approaches, and research themes that illustrate different aspects of educational systems. Research gaps include the lack of a consolidated and integrated theoretical–conceptual framework on educational governance; the under-representation of specific actors, contexts, and points of view about how educational policies intentions are interpreted and enacted; insufficient critical analyses of, among others, educational leadership, digital transformation, and non-state actors’ influence in educational governance; and limited discussion of governance’s effects on educational justice, equity and quality. The main limitations relate to geographic, linguistic, and cultural biases of the analyzed studies, the exclusion of non-open-access articles, and the predominance of qualitative methodological approaches, which restrict generalizability. To address these challenges, future research should follow the adoption of interdisciplinary approaches, longitudinal and context-sensitive studies, and the use of mixed methodologies. These findings could contribute to a more informed discussion, avoiding reductionist interpretations and more open and critical perspectives on how educational governance transcends organizational and technical structures by incorporating political, ethical, and contextual dimensions that challenge the quality of educational systems. Full article

Mangrove forests are among the world’s most vital coastal ecosystems. Mapping mangrove cover from local to global scales using spectral data and machine learning models is a well-established method. While non-spectral contextual datasets (spatial features) have also been incorporated into such models, the contribution of these additional features to improving mangrove mapping remains underexplored. Using the Mesoamerican Reef Region as a case study, we evaluate the effectiveness of incorporating spatial features in binary mangrove classification to enhance mapping accuracy. We compared an aspatial model that includes only spectral data with three spatial models: two included features such as geographic coordinates, elevation, and proximity to coastlines and streams, while the third integrated a geostatistical approach using Inverse Distance Weighted (IDW) interpolation. Spectral inputs included bands and indices derived from Sentinel-1 and Sentinel-2, and all models were implemented using the Random Forest algorithm in Google Earth Engine. Results show that spatial features reduced omission errors without increasing commission errors, enhancing the model’s ability to capture spatial variability. Models using geographic coordinates and elevation performed comparably to those with additional environmental variables, with storm frequency and distance to streams emerging as important predictors in the Mesoamerican Reef region. In contrast, the IDW-based model underperformed, likely due to overfitting and limited representation of local spectral variation. Spatial analyses show that models incorporating spatial features produced more continuous mangrove patches and removed some false positives in non-mangrove areas. These findings highlight the value of spatial features in improving classification accuracy, especially in regions with ecologically diverse mangroves across varied environments. By integrating spatial context, these models support more accurate, locally relevant mangrove maps that are essential for effective conservation and management. Full article

The spatial attention mechanism has been widely employed in the semantic segmentation of remote sensing images due to its exceptional capacity for modeling long-range dependencies. However, the analysis performance of remote sensing images can be reduced owing to their large intra-class variance and complex spatial structures. The vanilla spatial attention mechanism relies on the dense affine operations and a fixed scanning mechanism, which often introduces a large amount of redundant contextual semantic information and lacks consideration of cross-directional semantic connections. This paper proposes a new Cross-scan Semantic Cluster Network (CSCN) with integrated Semantic Filtering Contextual Cluster (SFCC) and Cross-scan Scene Coupling Attention (CSCA) modules to address these limitations. Specifically, the SFCC is designed to filter redundant information; feature tokens are clustered into semantically related regions, effectively identifying local features and reducing the impact of intra-class variance. CSCA effectively addresses the challenges of complex spatial geographic backgrounds by decomposing scene information into object distributions and global representations, using scene coupling and cross-scanning mechanisms and computing attention from different directions. Combining SFCC and CSCA, CSCN not only effectively segments various geographic spatial objects in complex scenes but also has low model complexity. The experimental results on three benchmark datasets demonstrate the outstanding performance of the attention model generated using this approach. Full article

The growing environmental and economic impacts of agri-food waste have intensified interest in digital and circular strategies for more sustainable resource management. This study investigates how digital technologies are being applied to enhance the circular management of agri-food waste. A systematic literature review was conducted following PRISMA guidelines, using Scopus as the primary database. The bibliometric analysis included 373 publications from 2015 to 2025 and was complemented by a thematic review of the 20 most cited articles. Results revealed six major research clusters, ranging from predictive waste analytics and smart traceability systems to circular bioeconomy applications such as anaerobic digestion and pyrolysis. In addition, the study examined structural indicators such as food waste per capita and hunger indices to contextualize geographic disparities in research output. The findings underscore the dual role of digital technologies as both operational tools and mechanisms for reducing systemic inequalities. Overall, the integration of intelligent systems and circular models offers promising pathways to support the Sustainable Development Goals and foster a more inclusive and resilient agri-food sector. Full article

In recent years, geographic knowledge graphs (GeoKGs) have shown great promise in representing spatio-temporal and event-driven knowledge. However, existing knowledge graph embedding approaches mainly focus on structural patterns and often overlook the dynamic evolution of entities in both time and space, which limits their effectiveness in downstream reasoning tasks. To address this, we propose a spatio-temporal evolutionary knowledge embedding approach (ST-EKA) that enhances entity representations by modeling their evolution through type-aware encoding, temporal and spatial decay mechanisms, and context aggregation. ST-EKA integrates four core components, including an entity encoder constrained by relational type consistency, a temporal encoder capable of handling both time points and intervals through unified sampling and feedforward encoding, a multi-scale spatial encoder that combines geometric coordinates with semantic attributes, and an evolutionary knowledge encoder that employs attention-based spatio-temporal weighting to capture contextual dynamics. We evaluate ST-EKA on three representative GeoKG datasets—GDELT, ICEWS, and HAD. The results demonstrate that ST-EKA achieves an average improvement of 6.5774% in AUC and 5.0992% in APR on representation learning tasks. In question answering tasks, it yields a maximum average increase of 1.7907% in AUC and 0.5843% in APR. Notably, it exhibits superior performance in chain queries and complex spatio-temporal reasoning, validating its strong robustness, good interpretability, and practical application value. Full article

For high-growth firms, designing and implementing strategies to ensure the long-term sustainability of business models is a key priority. Although these strategies are carefully planned to achieve specific outcomes, these firms also encounter contextual factors inherent to entrepreneurship, as well as the potential negative consequences of operating as small- and medium-sized enterprises (SMEs). Consequently, they adapt emergent outcomes to secure positive scaling-up processes. A comprehensive analysis of 69 studies from 1978 to 2023 revealed that 34.8% used sales as the main indicator of high-growth outcomes, 18.8% considered employment to be the most important outcome, and 37.7% incorporated both. The assessment period for these studies spanned three to seven consecutive years. A subsequent review of the existing literature yielded 56 potential new outcomes, emphasising the existence of a diverse array of concepts and metrics with which to assess high-growth performance. The study confirmed sales and positive profits arising during the planning process as strategic outcomes. However, it was also demonstrated that geographical expansion and innovation become emergent outcomes in critical situations. The research also identified that external factors, including an adverse public environment, business context difficulties, and a favourable business environment, may influence the effect of the firm’s high growth. Full article

The adoption of e-government services in Small Island Developing Nations (SIDNs) aims to enhance public service efficiency, inclusiveness, and quality. However, e-government service development in SIDNs faces some significant constraints, including limited resources, geographical isolation, low digital literacy levels, and inadequate technological infrastructure. This study investigates value co-creation approaches in e-government service, aiming to identify specific value co-creation processes and methods to support sustainable e-government initiatives in SIDN settings. The study applies a qualitative approach; based on the thematic analysis of interviews with government stakeholders, it identifies contextual factors and conditions that influence e-government value co-creation processes in SIDNs and strategies for sustainable e-government service value co-creation. This study contributes a value co-creation framework that applies participatory design, agile development, collaborative governance, socio-technical thinking, and technology adaptation as methods for the design and implementation of flexible and inclusive e-government services that are responsive to local needs, resilient to challenges, and sustainable over time. The framework can be used by policymakers and practitioners to facilitate sustainable digital transformation in SIDNs through collaborative governance, active participation, and civic engagement with innovative technologies. Full article

Teacher mental health is a growing concern in educational and public health systems worldwide. This meta-analysis systematically examines the relationship between teacher self-efficacy—a core construct in social cognitive theory—and job satisfaction, both considered crucial indicators of occupational well-being. A total of 39 studies involving teachers across 18 countries were analyzed, yielding a significant positive correlation between self-efficacy and job satisfaction (r = 0.41, p < 0.001), with notable heterogeneity (I² = 97%). Subgroup analyses revealed that the relationship was significantly stronger among teachers in high school and post-secondary contexts, and in studies conducted in Southern Hemisphere countries, highlighting the role of contextual and systemic moderators such as educational level and geographic inequality. The findings underscore the need for school- and policy-level interventions that bolster teachers’ self-efficacy through professional development, emotional support, and improved working conditions. Such interventions are essential not only for enhancing job satisfaction and reducing attrition but also for promoting the psychological resilience and well-being of the global teaching workforce. The study provides evidence-based insights into education and health policymakers aiming to support teacher retention and mental health through scalable, targeted initiatives. Full article

Turkey, a country with a unique blend of traditional and modern lifestyles, has made significant progress in promoting gender equality and is recognized as a pioneer in advancing women’s rights in the region. However, despite these advances, gender inequalities persist in various respects. This study aims to examine gender perception in a Turkish sample. Employing a cross-sectional and descriptive research design, the study was conducted with 1053 literate participants aged 18 and above who volunteered. Data were collected using a Demographic Information Form and the gender perception scale. The findings suggest that gender perception in Turkey is shifting toward a more egalitarian perspective, reflecting a departure from traditional norms. Several key factors were identified as contributors to this transformation, including education level, employment status, urbanization, socio-economic background, and geographical region of residence. These variables play a critical role in shaping gender perceptions and fostering societal change. By analyzing and contextualizing the results, this study offers valuable insights into the ongoing evolution of gender norms in Turkey. It underscores the importance of continued efforts to promote gender equality and serves as a foundation for future research on the sociocultural dynamics influencing gender perceptions. Full article

In social networks like community Question-Answering (cQA) services, members interact with each other by asking and answering each other’s questions. This way they find counsel and solutions to very specific real-life situations. Thus, it is safe to say that community fellows log into this kind of social network with the goal of satisfying information needs that cannot be readily resolved via traditional web searches. And in order to expedite this process, these platforms also allow registered, and many times unregistered, internauts to browse their archives. As a means of encouraging fruitful interactions, these websites need to be efficient when displaying contextualized/personalized material and when connecting unresolved questions to people willing to help. Here, demographic factors (i.e., gender) together with frontier deep neural networks have proved to be instrumental in adequately overcoming these challenges. In fact, current approaches have demonstrated that it is perfectly plausible to achieve high gender classification rates by inspecting profile images or textual interactions. This work advances this body of knowledge by leveraging lexicalized dependency paths to control the level of abstraction across texts. Our qualitative results suggest that cost-efficient approaches exploit distilled frontier deep architectures (i.e., DistillRoBERTa) and coarse-grained semantic information embodied in the first three levels of the respective dependency tree. Our outcomes also indicate that relative/prepositional clauses conveying geographical locations, relationships, and finance yield a marginal contribution when they show up deep in dependency trees. Full article