Search Results (26,116)

Background: Food bank users experience food insecurity, a social determinant of health linked to poorer physical and mental health. However, evidence on the health-related quality of life (HRQoL) of food bank users in Spain is scarce. Objectives: This study sought to assess HRQoL among users of the Navarra Food Bank and identify associated sociodemographic factors. Methods: We performed a cross-sectional study of heads of household using the Navarra Food Bank. A simple random sample of 350 participants was selected from a population of 2749 families. HRQoL was assessed by telephone using the EQ-5D-5L. We described the prevalence of problems in the five EQ-5D-5L dimensions, calculated the EQ-5D-5L utility index using the Spanish value set, and analyzed EuroQol Visual Analogue Scale (EQ-VAS) scores. Associations with sociodemographic characteristics were examined using multivariable general linear models. Results: Mean EQ-VAS was 73.56 (95% CI: 71.62–75.50), and mean EQ-5D-5L utility index was 0.815 (95% CI: 0.800–0.831). The most frequently reported problems were anxiety/depression (62.9%) and pain/discomfort (55.7%), while mobility (25.5%), usual activities (19.7%), and self-care (8.7%) were less commonly affected. Older age was significantly associated with both EQ-VAS and EQ-5D-5L utility index. Employment status and nationality were significantly associated with EQ-VAS, whereas sex was significantly associated with the EQ-5D-5L utility index. Conclusions: HRQoL was impaired among users of the Navarra Food Bank, with the greatest burden observed in the anxiety/depression and pain/discomfort dimensions. Older age and selected sociodemographic characteristics were associated with poorer HRQoL. Given the cross-sectional design, the findings should be interpreted as associative rather than causal. Full article

Filipino Sign Language (FSL) serves as a vital means of communication for the Deaf and hard-of-hearing in the Philippines. However, its societal use remains limited due to the scarcity of qualified interpreters and the general lack of FSL literacy among the population. Therefore, this study aims to address the gap between FSL development and automated FSL translation by employing machine learning and computer vision techniques. A model was trained using the FSL-105 dataset, which comprises video clips of gestures related to greetings and colors, and utilized MediaPipe for real-time detection of hand, face, and body landmarks. Through iterative training with transfer learning, the model’s performance improved from an initial accuracy of 80% to a final accuracy of 98.75%. The results demonstrate that the MediaPipe-based model can reliably interpret FSL gestures, positioning it as a potentially accessible assistive tool for the Deaf and hard of hearing community. This technology holds promise for applications in education, healthcare, and public service, offering new opportunities to promote the social inclusion of Filipino Deaf communities through more inclusive communication. Full article

As modern society grows increasingly complex, access to essential services such as healthcare, legal aid, tailored education, and psychological support remains heavily gated by socio-economic, neurological, and systemic barriers. This paper explores the transformative potential of Large Language Models (LLMs) and Generative Artificial Intelligence not merely as industrial productivity enhancers, but as vital “social scaffolds” capable of fostering a more inclusive society. Crucially, we propose a paradigm shift in the concept of Ethical Computing—moving from a passive defensive framework of non-maleficence (“do no harm”) to an active mandate of beneficence, where AI systems are explicitly developed to serve marginalized and un(der)served populations. Through this expanded ethical lens, we systematically analyze the democratizing impact of AI across four primary axes of inclusivity: socio-economic (providing zero-cost medical triage and legal translation for undocumented populations), neurospicy (acting as a non-judgmental communicative bridge for individuals with Autism Spectrum Disorder), pedagogical (delivering hyper-personalized executive function support for Special Educational Needs), and psychological (serving as an accessible, first-level triage system for mental health crises). By framing LLMs as a modern social safety net, we outline a clear trajectory for future research, advocating for an “ethical-by-design” development paradigm that explicitly prioritizes equity, accessibility, and the active dismantling of historical barriers for the digitally and socially disenfranchised. Full article

Business-to-consumer (B2C) e-commerce firms operate in fast-changing digital markets, where timely interpretation of external signals may strengthen organisational agility. This study examines how four dimensions of competitive intelligence—market, technological, social, and competitor intelligence—relate to organisational agility in Croatian B2C e-commerce firms. The study adopted a pragmatic explanatory sequential mixed-methods design. Quantitative data were collected through an online survey, and 208 valid responses were analysed using reliability testing, construct-validity assessment, correlation analysis, and multiple regression. Qualitative follow-up evidence was used to support the interpretation of the quantitative results. The findings show that the effects of competitive intelligence dimensions on organisational agility are not uniform. In the final validated model, social intelligence emerged as the only significant positive predictor of organisational agility, while market intelligence, technological intelligence, and competitor intelligence did not show statistically significant effects. The study therefore suggests that, in this context, systematic attention to customer conversations, online feedback, and socially visible market signals may play a more decisive role in supporting agile organisational responses than other intelligence domains. The study contributes to the competitive intelligence and agility literature by showing that intelligence dimensions should be examined separately rather than treated as a single undifferentiated capability in digital commerce settings. Full article

Systematic frameworks for describing podcast design remain scarce. Previous research on listening motives often treats podcasts as a monolithic category or focuses on specific genres, leaving open how motives vary across different design types. This dual-perspective investigation examines two questions: Which primary design types characterize German-language podcasts, and how are listening motives related to these design types? Using a multi-method qualitative approach, 30 podcasts were analyzed through iterative listening and 16 expert interviews to develop a typology of design. Additionally, 29 semi-structured listener interviews were examined via qualitative content analysis to identify usage motives and their associations with design types. The analysis identified three podcast design types—story, talk, and factual (STF)—each characterized by distinct structural and aesthetic features. The analysis further suggested that factual design types were primarily associated with cognitive motives, talk design types with social motives, and story design types with affective motives. The resulting STF model is a relevant framework for both academic research and practical applications in podcast production. The results further suggest that usage motives may be linked to these design types and thus indicates how podcast form and audience needs and gratifications may be interdependent. Full article

The primary aim of this study is to validate the utility of Social Media Data (SMD) as a scientifically grounded tool for quantifying the spatial mismatch between objective ecological supply and subjective social demand. Assessing the spatial coupling and mismatch between Habitat Quality (HQ)—representing objective ecological supply—and Ecological Perception (EP)—representing subjective social demand—is essential for developing targeted urban management and development strategies. Focusing on the core urban area of Hangzhou, this study quantified ecological supply using the InVEST HQ model. To reflect social demand, 4958 geolocated Weibo posts were processed using contextual sentiment analysis. A Coupling Coordination Degree model served as a diagnostic tool to evaluate the synergy between these two dimensions. Additionally, a Geodetector model was employed to investigate the factors driving spatial differentiation in this coupling. The findings indicate that: (1) The regional average HQ is 0.56, reflecting a moderate overall level of degradation, while EP shows a preference for natural environments and exhibits a distinct “strip-like” spatial distribution. (2) The overall CCD value is 0.384; high-coupling areas are primarily concentrated in regions with superior natural conditions and dense vegetation, whereas low-coupling areas correspond to zones with intensive urban functions. (3) Driving factor analysis reveals that land-use type exerts the most significant influence on the overall degree of coupling. This study demonstrates that the HQ-EP coupling framework provides a reliable spatial diagnostic tool for urban planners to identify socio-ecological vulnerabilities. The results suggest that an appropriate integration of natural elements enhances coupling outcomes, with the highest synergy observed in environments characterized by high HQ and minimal anthropogenic disturbance. Full article

This study investigates the determinants of borrower repayment intentions in Marketplace Lending (MPL) platforms, focusing on the interplay between behavioural factors and Environmental, Social, and Governance (ESG) awareness in the Hungarian context. A Partial Least Squares Structural Equation Modelling (PLS-SEM) approach was employed to analyze survey responses from 477 participants familiar with MPL platforms. The study integrates constructs from behavioural finance (Perceived Usefulness, Perceived Ease of Borrowing, Theory of Planned Behaviour) and ESG-related factors (Socially Responsible Investment Theory, Reciprocity Theory) to assess their influence on repayment intentions. Perceived Usefulness (PU) emerged as the strongest predictor of Repayment Intention (RI) (β = 0.554, p < 0.001), highlighting the importance of platform functionality. Socially Responsible Investment Theory (SRIT) also had a significant positive impact (β = 0.194, p < 0.01), suggesting that ethical lending practices enhance borrower accountability through reciprocity mechanisms. Conversely, Continuance Intention to Borrow (CIB) and Credit Risk Theory (CRT) showed no significant effects. This study contributes to the literature by bridging behavioural finance, credit risk theory, and ESG principles in FinTech lending, offering a novel framework for sustainable lending practices. Full article

Against the backdrop of increasing challenges posed by ongoing climate change, pollution and its associated implications and environmental and climate protection measures have become the focus of politics and society in recent years. But adaptation and mitigation require changes in behavior among the population. This means that a process of social transformation must take place. Based on the thesis that people working in healthcare facilities can make a relevant contribution to the social transformation of environmental awareness, this study examines the general and workplace-related environmental awareness of hospital employees. Risk awareness, measure effectiveness, transformation costs and the subjective social norm factors were included, which eventually influence this awareness. Therefore, a mixed study design consisting of an original study and a systematic replication study was used. Data were analyzed using structural equation modeling (path analysis) to identify key predictors of environmental awareness and behavior. The results show that hospital employees generally have a high level of environmental awareness compared to the general population in Germany. This is also evident in their awareness of workplace-related measures. However, influencing factors such as transformation costs in particular mean that measures, even if they are considered effective, are only implemented to a limited extent by hospital employees. With regard to the question of whether hospital employees can play a key role in the social transformation process, this study does not provide sufficient evidence to answer this question. Full article

Media coverage of disasters frequently frames self-interested behavior in contrast to collective responsibility and coordinated response. This study aims to explore how such behavior is emotionally constructed in disaster-related media, using a carefully selected corpus of 12 text-centered news articles focusing on selfish behavior. The analysis combines transformer-based sentence-level emotion classification using the tweetnlp RoBERTa model, which predicts 11 emotion categories, with Latent Dirichlet Allocation topic modeling across single-sentence and three-sentence windows in a small purposively selected corpus. Emotion–topic relationships are quantified by weighting emotion probabilities by topic distributions and visualized using bar charts, network graphs, and heatmaps. The findings suggest that fear and disgust dominate portrayals of self-interested behavior, while anticipation appears in projections of harm and anger is linked to inequality and institutional accountability. Two discursive configurations emerge: Responsibility Across Individuals and Institutions, emphasizing public accountability and authority, and Collective Fear and Self-Protective Practices, reflecting affect-driven responses under uncertainty. Although negative emotions predominate, optimism appears conditionally, signaling coordination and recovery. Overall, disaster reporting constructs selfishness through integrated emotional–semantic patterns that position individual actions within broader social risk and collective responsibility. Full article

Employee happiness has become a central concern for the social dimension of sustainability, particularly within small and medium-sized enterprises (SMEs) operating in emerging economies. However, empirical evidence remains limited regarding how advanced organizational self-management practices—especially when integrating holacracy-inspired practices and broader self-management mechanisms that show a positive and significant association with employee happiness in SME contexts, particularly in Latin America. Addressing this gap, this study examines the relationship between organizational self-management practices and employee happiness in Peruvian SMEs, adopting a predictive approach based on Partial Least Squares Structural Equation Modeling (PLS-SEM). Organizational Self-Management Practices (OSMPs) are modeled as a higher-order construct integrating holacracy-inspired and broader self-management practices. Data were collected from 383 SME employees through a structured questionnaire. The findings indicate that organizational self-management practices exert a positive and significant association with employee happiness, operating through an underlying mechanism in which self-management-oriented practices foster greater employee autonomy, participatory decision-making, role clarity, and shared responsibility, thereby supporting fundamental psychological needs and enhancing employees affective and cognitive well-being at work. By promoting these autonomy-supportive organizational conditions, Organizational Self-Management Practices (OSMPs) strengthen employee happiness in resource-constrained SME contexts, highlighting how Organizational Self-Management Practices function as internal governance mechanisms that enhance employee well-being and contribute to social sustainability by strengthening psychologically supportive, autonomy-enhancing, and socially sustainable work environments in emerging economy SMEs. These findings demonstrate that employee happiness represents a micro-level manifestation of social sustainability, linking internal organizational governance mechanisms with broader sustainable development outcomes in emerging economy contexts. Full article

This study examines the applicability of coding-theoretic tools to the digital monitoring of information space. The proposed approach treats response patterns to socially significant stimuli as binary sequences and interprets their analysis as a classification problem analogous to error correction in coding theory. To verify the feasibility of this framework, a model psychological test consisting of seven binary questions was analyzed using a procedure derived from the Hamming code (7,4). The method makes it possible to map the full space of observed answer combinations onto a smaller set of reference codewords and thereby identify stable response configurations. The obtained results show that the distributions produced after coding-based transformation are markedly non-uniform and contain recurrent maxima, indicating the presence of structured patterns in collective responses. It is also shown that permutations of question order substantially affect the resulting distributions and correlation indicators, which highlights both the sensitivity and the analytical potential of the proposed encoding scheme. The main contribution of the study is methodological: it demonstrates that error-correcting coding can be operationalized as a formal tool for detecting latent regularities in simplified monitoring data. At the same time, the present results should be regarded as proof of concept, since further work is required to validate the approach on larger datasets, compare it with baseline classification methods, and extend it to longer and multivalued response sequences. Full article

Background/Objectives: The presented study aimed to understand the relationship between knowledge, attitudes, and practices, as well as consumers’ preferences for the consumption of Spirulina-enriched fruit and vegetable juices. Methods: A survey about the consumers’ attitudes towards consumption of algae in general and especially Spirulina was conducted to better understand the target groups and marketing strategies for this novel non-alcoholic beverage product. Knowledge–Attitude–Practice (KAP) model in combination with structural equation modelling (SEM) was applied to test the hypothesised relationships between the variables. Additionally, consumers’ preference test was done using a seven-point hedonic scale and ranking of the six juice samples: plain sour cherry juice (SC1), sour cherry juice with 0.8% (SC2) and 1.6% (SC3) of blue Spirulina powder; plain tomato juice (T1), tomato juice with 0.8% (T2) and 1.6% (T3) of blue Spirulina powder. Results: The SEM results showed that there is a limited direct impact of knowledge on social motivation, while personal behaviour strongly predicts social motivation. Namely, perceived nutritional value and health benefits were shown to be the main factors for consumers’ willingness to drink Spirulina-enriched juice. Conclusions: The result of the consumer preference evaluation exposed that the juices containing sour cherry and Spirulina achieved better sensory acceptance and ranking than those containing tomato, pointing out the importance of the product matrix for achieving consumer acceptance. Full article

As image–text posts have become a dominant form of social media communication, understanding how the two modalities jointly convey meaning remains a key challenge in multimodal analysis. This study aims to examine whether image–text consistency is inherently multidimensional rather than reducible to a single similarity metric. Existing studies often reduce consistency to a single relevance score, which cannot capture semantic, emotional, and functional interactions. We construct a dataset of 28,650 multimodal posts and model image–text relationships along three dimensions: semantic consistency (CSC), emotional consistency (CEC), and informational matching consistency (IMC). Semantic and emotional alignment are measured using cross-modal representation and similarity computation, while IMC is defined through rule-based classification of informational roles. Results show that emotional consistency (CEC = 0.621) is higher than semantic consistency (CSC = 0.549, $p<0.001$), while 61.0% of posts maintain consistent informational orientation. These findings demonstrate that image–text consistency exhibits distinct cross-dimensional patterns that cannot be captured by single-metric approaches. Full article

Against the backdrop of expanding digital dissemination and experiential transformation in cultural heritage, visitors’ visual attention and symbolic choices increasingly shape heritage cognition and value transmission. Taking the Yellow Crane Tower as a case study, this research constructs a cultural symbol recognition dataset based on visitor-shared social media images and develops an enhanced ResNet-50 model for multi-label analysis. By integrating attention mechanisms and regularisation strategies, the model improves its capacity to capture complex cultural imagery, achieving a macro F1 score of 72.70% and a micro F1 score of 81.05% on the test set, indicating strong generalisation performance. The results reveal a significant imbalance in visual preferences: landmark symbols centred on the main architectural structure dominate at 32.95%, whereas culturally informative elements such as signage, cultural products, and interpretive facilities each account for less than 5%. Tag co-occurrence analysis further identifies three image production patterns: commemorative presentation, contextual documentation, and detail-oriented cultural photography reflecting different levels of heritage perception. Rather than directly proposing prescriptive strategies, the findings provide an empirical basis for informing future interventions aimed at shifting from landmark-focused viewing to deeper cultural perception. In this way, the study contributes to heritage display optimisation and research on visitor visual behaviour. Full article

Solitary living is an evolutionarily widespread yet comparatively under-theorized social system, despite its occurrence across diverse animal taxa. Shrikes (family Laniidae) are small predatory passerines that combine raptorial behavior, strong territoriality, and predominantly solitary space use, making them a powerful model for examining the ecology and evolution of solitary living. Here, I synthesize published work on shrike behavioral ecology and explicitly link these traits to the costs and benefits of a solitary lifestyle. I argue that shrikes exemplify how solitary species can offset the absence of social buffering through cognitive innovation, finetuned habitat selection, and flexible yet tightly bounded sociality. I then compare shrike ecology to solitary mammals and reptiles, highlighting convergent patterns in resource dispersion, spatial memory, risk management, and juvenile dispersal. I further examine how anthropogenic pressures, such as habitat fragmentation, climatic instability, and urbanization, interact with solitary life histories and review evidence from management interventions in both European farmland and North American systems that demographic recovery is achievable but remains contingent on addressing broader land-use conflicts and sources of adult mortality. Finally, I outline five interconnected research priorities—spanning cognitive ecology, trophic interactions, movement ecology, genomics, and formal comparative analyses—that would move shrike research from its current observational foundation toward a more experimental, mechanistic, and phylogenetically informed programme. By reframing shrikes as a model taxon for solitary living, this review aims to integrate avian behavioral ecology into broader comparative frameworks of social organization, cognition, and resilience under global change. Full article