Search Results (12,900)

Background/Objectives: This study aimed to assess public stigma toward people with mental health problems and to examine the association between stigma and socioeconomic characteristics, personal mental health history, and contact with individuals with mental health problems. Methods: This observational, descriptive, and cross-sectional study was conducted among the general population in Spain using a sample of 404 participants, the majority of whom were women (71%), with a median age of 38 years (IQR = 26–49); most participants (86.4%) lived in urban areas. The participants completed a self-administered online questionnaire that explored socioeconomic variables and the Community Attitudes towards Mental Illness Scale (CAMI-S, Spanish version). Non-parametric tests (Mann–Whitney U, Kruskal–Wallis, and Spearman correlation), multiple linear regression, and statistical power analyses were performed. Results: The mean CAMI-S total score was 84.89 (SD = 11.122) out of 100, indicating relatively favourable attitudes toward people with mental health problems. Statistically significant associations (p-value ≤ 0.05) were found between CAMI-S scores and variables such as gender, age, place of residence, educational level, mental health disorder, and close contact with someone with mental health disorders. The regression model revealed four significant predictors of lower stigma: identifying as female (β = 2.523; p = 0.037), having a medium or higher educational level (β = 5.061; p = 0.002), experiencing a mental health diagnosis (β = 4.535; p = 0.014), and close contact (β = 4.183; p < 0.001). Conclusions: Social stigma toward people with mental health problems in Spain appears to be generally low, reflecting positive attitudes toward community integration. Being female, having higher education, and personal or close contact with mental health problems are associated with lower stigma. Full article

The global landscape of sustainability challenges has become increasingly complex, characterized by varying regulatory frameworks and market maturity across different nations. The financial significance of environmental, social, and governance (ESG) factors is influenced by industry and firm-specific attributes. Therefore, this study employs an integrated decision support framework that combines grey relational analysis (GRA) models including Deng’s GRA, absolute GRA, and a second synthetic grey relational analysis (SSGRA) with firm-level panel regressions to compare ESG and financial performance linkages across 11 Middle East and Africa (MEA) countries and industrial sectors. Furthermore, the study utilized a sensitivity analysis to check the robustness of SSGRG. Results indicate considerable variability in the relationships between ESG and financial performance across the region. The economies of the Gulf Cooperation Council (GCC) showed the most robust positive relationship between ESG factors and financial performance based on SSGRG, with Kuwait (0.82), Qatar (0.81), and Saudi Arabia (0.80) predominantly influenced by the social and governance dimensions. Conversely, a weak correlation was demonstrated in Egypt (0.54), Nigeria (0.53), and Kenya (0.56). Moreover, financials, communication services, and materials sectors exhibit the greatest integration of ESG factors into financial performance, with composite SSGRG values ranging from 0.75 to 0.78. In contrast, the information technology and energy sectors demonstrate weak association, with composite SSGRG values falling below 0.60. Furthermore, a conservative maximin analysis reveals that corporate governance in Kenya and environmental performance in Oman are identified as the weakest relationship at the country level, while governance in the information technology and energy sectors, environmental management in real estate, and social performance in consumer discretionary sectors are highlighted as weak connections. This study addresses a gap in the literature by developing a novel decision-support framework, providing fresh empirical evidence from emerging markets, and offering theoretical insights into the into influence of stakeholder and institutional factors on ESG value creation. This study provides implications for investors, corporate managers, and policymakers on sustainable finance in emerging markets and presents a decision-making framework that emphasizes ESG initiatives to enhance financial performance. Full article

Background: The Mobility and Quality of Life-7 Dimension (MobQoL-7D) is a new patient-reported outcome measure for mobility-related quality of life. Our aim was to translate and test a Dutch-language version. Methods: A cross-sectional psychometric evaluation study was undertaken. The sampling frame was community-dwelling adults living in the Netherlands who had a long-term (>6 months) mobility impairment. Participants were recruited through a Dutch research agency, and data were collected via online survey. Statistical and psychometric analyses were undertaken to assess the interpretability, validity and reliability of the MobQoL-7D Dutch, including assessment of missing data, floor/ceiling effects, test–retest reliability, structural validity, known-group validity and convergent validity. Results: n = 308 respondents completed the survey; sub-group sample sizes ranged from n = 29 to n = 87. No issues with missing data were found. Despite ceiling effects per item (ranging from 23.1% to 56.5%), there were no floor/ceiling effects for overall index values (12.3% and 0%, respectively). The findings show excellent test–retest reliability of the index value over a two-week period (n = 37; ICC = 0.95), and potential discriminative ability to detect differences between known groups. Factor analyses confirmed unidimensionality. Conclusions: The results provide promising evidence of the validity and reliability of the MobQoL-7D Dutch; further research is needed to confirm these findings. Full article

Research on information and communication technologies (ICTs) in sustainable agriculture has largely been technocentric, focusing on effectiveness, efficiency, and adoption, with limited consideration of end-user perceptions in practice. This study addresses this gap by examining perceptions of mobile gardening apps as accessible ICT tools that may support sustainable behaviours. Based on over 180,000 user reviews from Google Play and the Apple App Store, Contextualized Topic Modeling (CTM) was used to identify key themes and interpret them within the Theory of Consumption Value (TCV) framework. This approach allows for the analysis of functional, emotional, and epistemic dimensions of user experiences based on large-scale, real-world data. The results indicate that functional aspects, such as reliability and usability, dominate app evaluation, but emotional engagement and knowledge acquisition also play a significant role. By combining a data-driven approach with a well-established behavioural framework, this study bridges the gap between technological and user perspectives. It simultaneously extends the application of the TCV to the field of ICT solutions supporting sustainable development and provides practical guidance for designing more effective gardening apps. Full article

This short communication synthesizes evidence on how the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) altimetry data are used by private sector actors and the implications for economic value creation. Using secondary research that collected and summarized information from existing data from reports, journals, websites, and databases, the work identifies 54 companies across 9 sectors leveraging ICESat-2-derived elevation, canopy height, bathymetry, and surface measurements to inform decision-making, risk assessment, and new business models. The analysis situates ICESat-2 within a broader context where freely available Earth observation data can generate substantial private- and public-sector value, potentially exceeding hundreds of billions in aggregate when scaled across industries such as geospatial services, climate management, real estate, and insurance. The paper uses a four-pillar conceptual model to guide valuation of data-driven impacts: Data Utility (intrinsic information value of altimetry and related metrics), Decision Impact (tangible economic benefits from improved models and operations), Strategic Integration (emergence of new business models and market opportunities), and Data Ecosystem Exclusivity (development of proprietary datasets and workflows that enable competitive differentiation). Empirical findings illustrate how these pillars manifest in practice. The paper seeks to connect private-sector uptake to NASA’s Earth Science to Action framework and related capacity-building efforts, highlighting pathways for broader utilization through training, tutorials, and accessible interfaces. Limitations of the study include partial sector coverage and reliance on publicly reported use cases. Future work should quantify economic returns with standardized metrics and extend the dataset to capture dynamic shifts in data products, governance, and IP development within the evolving data ecosystem. Full article

Coffee label information impacts consumer choice by communicating key product attributes. This study investigated whether label information on fermentation-related post-harvest processing techniques influence specialty coffee consumers’ expectations and perception of brewed coffee. A total of 180 specialty coffee consumers participated in a within-subject tasting experiment, evaluating the same coffee paired with three labels: no processing information, ‘fermentation’, and ‘carbonic maceration’. Participants first rated their expectations of aroma, flavour, acidity, sweetness, and subsequently, their experience of those attributes on tasting the coffees, as well as rating their liking and purchase intent. Additionally, they also assessed the usual-to-exotic flavour expectation and perceived price of coffees processed with traditional and innovative post-harvest methods. Results showed that the coffee paired with the label ‘fermentation’ was expected to be the most acidic and the least liked, which was confirmed during tasting, whereas the label ‘carbonic maceration’ increased curiosity and perceived novelty towards the coffee without negatively affecting the sensory acceptance. Innovative fermentation-related terms were also perceived as more exotic and expensive compared to traditional methods. These findings demonstrate that descriptive post-harvest terms on coffee labels significantly influence consumer expectations, sensory perception, and perceived value. They also highlight the importance of carefully selecting labelling terms to balance consumer curiosity, sensory expectations, and product acceptance. Full article

Distance learners in higher education are often assumed to face limited peer interaction, potentially weakening their sense of belonging. This study examines peer relationships and belonging among students in distance and blended university programs, with attention to the role of virtual reality (VR) within digitally mediated learning environments. Immersive VR teaching is included in the curriculum for distance learning students in the studied programs. Using a mixed-methods design, survey data and open-ended responses were collected from 17 students in Information Studies and Information Service Design. An adapted Classroom Community Scale was supplemented with items addressing the perceived contribution of different communication technologies. Contrary to expectations, fully distance learners did not report weaker agreement with statements reflecting belonging than blended students; on several items, they expressed stronger agreement, particularly regarding perceived peer support and learning opportunities. Results indicate that conventional 2D communication tools, particularly chats and video calls, are central to sustaining peer relationships. VR was not perceived as essential but described by some students as an added value supporting shared experience and group cohesion. Overall, belonging emerges as a socio-technical achievement shaped by communication practices rather than physical proximity. Full article

Demand for camel milk products is growing in Morocco and worldwide, creating opportunities to strengthen the livelihoods of populations living in arid regions through the development of camel-based dairy value chains. In addition to their economic potential, such value chains may contribute to sustainability by supporting food systems adapted to arid environments, promoting the use of locally resilient livestock species, and enhancing the socio-economic viability of vulnerable rural communities. This exploratory qualitative study investigates urban consumer behavior related to dairy consumption with a specific focus on the potential integration of camel milk products into local dietary habits. To capture nuanced consumer perspectives, gender-segregated focus-group discussions were conducted in three Moroccan cities using a semi-structured questionnaire on dairy consumption habits. Key factors examined included milk types, product preferences, purchasing locations, consumption frequency and willingness to include camel products in the household diet. The results indicate that camel milk is rarely consumed outside areas where camels are raised. Nevertheless, participants expressed interest in several camel milk-based products, particularly fermented milk and spreadable cheeses. This interest was primarily driven by perceptions of camel milk as a healthy product and by its association with traditional food practices. These findings suggest that expanding camel milk consumption in urban markets could support more sustainable and territorially rooted dairy systems by linking consumer demand with production models suited to dryland conditions. This study indicates promising market opportunities for the development of camel milk products in urban areas, particularly if challenges related to pricing strategies, distribution network, and region-specific supply chains are strategically managed. Full article

Residential college (RC) activities represent a creative form of engagement beyond formal classroom teaching, integrating experiential, social, and community-based learning. China is promoting holistic education through the RC activities. Student motivation directly influences their engagement in practice-based learning. Yet, the motivation profile of Chinese students’ participation in RC activities remains largely unexplored. To address this gap, the exploratory cross-sectional study involved 403 undergraduates from an RC-based university in the Guangdong–Hong Kong–Macao Greater Bay Area. Based on a standardized questionnaire, we explored descriptive patterns of three forms of motivation, namely intrinsic motivation, extrinsic motivation, and amotivation, as well as four influencing factors: activity logistics, experiential value, outcome expectations, and social context. We then conducted hierarchical linear regression analyses with the three motivation types as outcomes. The primary results indicated that intrinsic motivation was the dominant motivation type among RC students. Experiential value emerged as a key influencing factor, positively associated with intrinsic and extrinsic motivation, and negatively associated with amotivation. Additionally, activity hosting experience was identified as another important correlate, positively linked to both intrinsic and extrinsic motivation. Motivational patterns further varied across gender, academic year, ID place, weekly RC stay duration, and part-time employment. The findings provide empirical support for more targeted RC activity planning aimed at boosting student motivation in the Chinese context. Full article

The cultural valorization-based territorial recognition program has established itself as an effective strategy for fostering sustainability in rural tourism destinations. However, there is limited evidence of their influence from the community’s perspective. This study analyzes the relationship between the conditions of territorial recognition promoted by the “Pueblos con Encanto” (Charming Villages) program and the sustainability of the Cruz Pampa–Yapatera tourist destination. A mixed-methods approach was employed, utilizing a non-experimental, cross-sectional, and correlational design. For the quantitative part, a structured questionnaire was administered to a sample of 336 residents from the area, using simple random sampling. Data analysis included statistics and Pearson’s correlation. For the qualitative part, 13 interviews were conducted with representative members. These people have influence over the governance of the area. The results of the triangulation showed that, according to the residents’ perception, Cruz Pampa–Yapatera meets the requirements for the “Pueblos con Encanto” program. It is evidenced in its historical heritage and Afro-Peruvian cultural heritage, such as its cumananas, local cuisine, and religious festivities. However, it has deficiencies in infrastructure and tourist facilities that require improvements to strengthen the tourist experience and preserve its cultural identity. Furthermore, the “Pueblos con Encanto” recognition program is positively and significantly related to the current sustainability of the destination. The research demonstrates, through empirical assessment, a positive perception among the local population of sustainability in their community based on the “Pueblos con Encanto” program criteria. A process that should be incorporated into the evaluation framework for the granting of such recognition. Full article

Employing a 4 (opponent type) × 2 (communication condition) between-subjects design, the study recruited 194 valid human participants to complete three rounds of game tasks. Results revealed: (1) The type of game counterpart exerted a significant main effect on participants’ remaining funds (F(3, 185) = 3.179, p = 0.025). Human participants retained significantly more funds when the counterpart was a real large model compared to other groups. (2) A significant interaction existed between the type of game counterpart and communication conditions (F(3, 185) = 3.318, p = 0.021). Specifically, when the opponent was a fake AI model (presented as human but actually an AI), human participants’ remaining funds were significantly higher under the communication condition than without communication (p = 0.012). This indicates that communication can promote rational decision-making in identity mismatch scenarios by providing additional behavioral cues. In the fake-human group (informed as human but actually AI), a numerical trend toward increased funds was also observed under communication conditions, though it did not reach statistical significance (p = 0.159); (3) The moderating effect of social value orientation did not reach significance. These findings extend the application of the theory of mind in human–machine games, revealing the complex influence mechanism of identity perception and communication dynamics on rational decision-making. Full article

This study investigates European citizens’ perspectives on farmers’ roles, highlighting gender, age, education, political orientation, community size, social class, and attitudes towards the EU. This study was developed using 21,002 interviews with European Citizens from all 27 EU countries. A quantitative data analysis methodology was used from the European Eurobarometer 97.1 survey. Seven models were formulated and tested. It is shown that men prioritise economic growth and food stability, while women emphasise environmental protection and animal welfare. Younger individuals focus on rural job creation, whereas older citizens value food security. Higher education levels correlate with environmental and animal welfare concerns. Right-leaning citizens favour economic development, whereas left-leaning individuals prioritise ecological issues. Larger communities emphasise economic growth, while smaller ones focus on environmental preservation. Social class influences priorities, with higher classes concerned about sustainability and lower classes about job creation. Pessimistic views about the EU correlate with food safety concerns, while optimistic views align with environmental and animal welfare priorities. These findings suggest that aligning agricultural and food policies with citizens’ diverse needs can foster a more sustainable and resilient European food system. Full article

WSN node energy forecasting contributes to improving network efficiency, extending network lifespan, and providing energy management strategies. In this study, a deep-learning-based wireless sensor network (WSN) node energy forecasting model based on Long Short-Term Memory (LSTM) and stacked-LSTM was developed across different wireless communication technologies in both static and dynamic WSN setups. The performance of the deep-learning-based models was compared with traditional forecasting techniques such as Exponential Smoothing and Prophet. The results showed the superiority of LSTM and stacked-LSTM in terms of root mean square error and mean absolute error, with consistently lower values compared with the traditional forecasting techniques. The results also show that the models perform best with Long Range technology. The deep learning-based model also demonstrates its ability to perform better in both static and dynamic WSN scenarios. These results demonstrate the potential of deep-learning-based models in WSN node energy management, which can result in an optimal energy efficiency and prolong the network lifetime. Future research is needed to explore hybrid approaches to further improve the prediction performance of deep learning-based models by combining their strengths with statistical or traditional forecasting techniques. Full article

Kazakhstan has aggressively pursued the internationalization of higher education, evidenced by the strategic Bolashak scholars’ program, adoption of the Bologna Process, and expanded academic mobility. In this paper, we argue that these efforts, while structurally significant, have yielded results that have prioritized institutional outputs over intercultural learning outcomes. To achieve genuine modernization, internationalization must move beyond technical compliance and be grounded in the cultivation of intercultural competence and citizenship. We review the trajectory of Kazakhstan’s educational history, development, and reforms and conclude that current efforts lack the cohesion and theoretical grounding necessary to foster globally engaged, interculturally competent citizenship. We narratively review selected international case studies of higher education institutions that have developed intercultural competence and citizenship programs to develop cross-case themes and practices. Consequently, we suggest a contextualized paradigm for developing intercultural competence within Kazakhstani higher education. We present a series of theoretical, practical, and institutional suggestions tailored for Kazakhstani higher education institutions to consider. Ultimately, intercultural competence in Kazakhstan must begin with a critical exploration of national and local values to engage the global community from a “glocalized,” culturally resonant, and decolonized standpoint. Full article

Non-convex stochastic optimization presents fundamental mathematical challenges across machine learning, wireless networks, data center resource allocation, and optical wireless communication systems, where complex loss landscapes with multiple local minima and saddle points impede classical variational inference methods. This paper introduces the Quantum-Inspired Variational Inference (QIVI) framework, which systematically integrates quantum mechanical principles (superposition, entanglement, and measurement operators) into classical variational inference through rigorous mathematical formulations grounded in Hilbert space theory and operator algebras. We develop a unified optimization framework that encodes classical parameters as quantum-inspired states within finite-dimensional complex Hilbert spaces, employing unitary evolution operators and adaptive basis selection governed by gradient covariance eigendecomposition. The core mathematical contribution establishes that QIVI achieves a convergence rate of $\mathit{O}({log}^{2}T/T^{1/2})$ for $\sigma$-strongly non-convex functions, provably improving upon the classical $\mathit{O}\left(T^{-1/4}\right)$ rate, yielding a theoretical speedup factor of $1.85$–$1.96\times$. Comprehensive experiments across synthetic benchmarks, Bayesian neural networks, and real-world applications in network optimization and financial portfolio management demonstrate 23–$47\%$ faster convergence, 15–$35\%$ superior objective values, and 28–$46\%$ improved uncertainty calibration. The principal contributions include: (i) a rigorous Hilbert space-based mathematical framework for quantum-inspired variational inference grounded in operator algebras, (ii) a novel hybrid quantum–classical algorithm (QIVI) with adaptive basis selection via gradient covariance eigendecomposition, (iii) formal convergence proofs establishing provable improvement over classical methods, (iv) comprehensive empirical validation across diverse problem domains relevant to machine learning and network optimization, and (v) demonstration of the framework’s applicability to optimization problems arising in wireless networks, data center resource allocation, and network system design. Statistical validation using the Friedman test (${\chi }^2=847.3$, $p<0.001$) and post hoc Wilcoxon signed-rank tests with Holm–Bonferroni correction confirm that QIVI’s improvements over all baseline methods are statistically significant at the $\alpha =0.05$ level across all benchmark categories. The framework discovers $18.1$ out of 20 true modes in multimodal distributions versus $9.1$ for classical methods, demonstrating the potential of quantum-inspired optimization approaches for challenging stochastic problems arising in machine learning, wireless communication, and network optimization. Full article