Search Results (6,849)

Objective: This study examined the relationships between the developmental stages of children aged 6–72 months and their parents’ psychological resilience and psychological well-being. Method: The study was designed as a descriptive and correlational survey. The sample included a total of 184 children aged 6–72 months, as well as their parents, who visited Sinop Atatürk State Hospital. Data were collected face-to-face using the Personal Information Form, the Early Developmental Stages Inventory (EGE), the Psychological Well-being Scale (PWBS), and the Psychological Resilience Scale for Adults (PRS). The data were analyzed using the independent samples t-test, Pearson correlation coefficient, and simple and multiple linear regression analyses. Results: According to the study’s results, most children (92.4%) were found to be at a normal level in terms of overall development; importantly, personal-social skills had the highest rate of developmental delay (19.0%). Comparative analyses showed that the psychological resilience and psychological well-being scores of parents of children with typical development were higher than those of parents of children with developmental delays. Correlation analysis revealed a moderate positive relationship (r = 0.330, p < 0.001) between the Early Developmental Stages Inventory score and the Psychological Well-being Scale, and a weak positive relationship (r = 0.154, p < 0.05) between the Psychological Resilience Scale and the Early Developmental Stages Inventory score. Regression analyses suggest that psychological well-being and resilience are associated with child development outcomes. Discussion and Conclusions: The findings of this study indicate that there are meaningful associations between parents’ psychological well-being and resilience levels and children’s early developmental outcomes. Children whose parents reported higher psychological well-being and resilience tended to demonstrate more favorable developmental profiles in several developmental domains. These results suggest that parental psychological characteristics may be relevant factors associated with early childhood developmental outcomes and should be interpreted within broader ecological and contextual frameworks. Full article

Background: Artificial Intelligence (AI) and Machine Learning (ML) technologies, such as conversational agents, are becoming increasingly essential tools across multiple industries, particularly in healthcare. This paper presents a scoping review (PRISMA-ScR) of conversational agents (CAs) in mobile health coaching systems (MHCS). It examines existing applications of MHCS, focusing on development strategies, usage contexts, impacts on users, benefits, and research gaps, emphasizing the ability of explainable artificial intelligence (XAI) in making health guidance and decision-support recommendations transparent, trustworthy, and interpretable, if properly integrated. This scoping review identifies opportunities to maximize the use of conversational agents, explainable AI, and mobile technologies to make mobile health coaching systems more accessible and trustworthy, as well as further research gaps worth exploring. Objective: This scoping review maps the evidence on CAs and XAI-enabled technologies in MHCS, identifies trust-related design criteria, categorizes reported outcomes, and highlights opportunities for explainable conversational agents (XCA) in a mobile health context, especially in tackling general medical conditions pertinent in underserved settings. Eligibility criteria: Reported eligible resources evaluated, designed, or conceptually analyzed existing CAs, XAI techniques, and MHCS, AI-supported medical dialogue systems, e-coaching systems, and mobile health applications. We considered sources only relevant to healthcare, health coaching, trust, explainability, or patient engagement that were published between 2006 and 2025. Sources of Evidence: Searches were conducted in IEEE Xplore, Google Scholar, Springer, ScienceDirect/Elsevier, ProQuest, and ACM Digital Library, supplemented by targeted web searches and backward citation checks. Charting methods: Data were charted by system type, communication mode, health context, operational mode, technology used, XAI/trust features, degree of automation, study designs and outcome classification. We applied a revised outcome classification: generated desired outcome (GDO) and partially generated desired outcome (P-GDO), and did not generate desired outcome (DN-GDO). Results: A total of 201 resources were collected. Charted studies clustered around CAs in health, MHCS for chronic diseases and stress management, XAI methods such as LIME, SHAP, Prospector, and counterfactual explanations, and trust-related elements such as voice quality, communication style, appearance, social intelligence, privacy, and performance quality. Most health CAs and MHCS addressed chronic diseases, mental health, or behavior change; fewer addressed general medical diagnosis or autonomous mobile-based primary care support. Conclusions: Existing evidence suggests that CAs and MHCSs can support engagement, coaching, education, and selected decision-support tasks, but evidence for safe, autonomous, explainable general practice functionality remains limited. Future work should prioritize clinically supervised XCA designs, core safety assessment, interfaces with transparent explanation, data protection, culturally and linguistically responsive implementation, and future-oriented review in underserved mobile health settings. Full article

Background: Diabetes is a growing public health crisis across the Arab region, where rapid urbanization, dietary transitions, and physical inactivity have contributed to some of the highest diabetes rates globally. Despite a growing recognition of the problem, most diabetes prevention efforts in the region remain small-scale or insufficiently adapted to the sociocultural realities of adults living in the UAE. Evidence-based diabetes prevention strategies, such as the United States’ Centers for Disease Control Diabetes Prevention Program (DPP), reduce the risk of developing diabetes but remain underutilized. Methods: The objectives of this study were to (1) describe the systematic cultural adaptation of the Evidence-based Intervention for Diabetes Prevention (EID) using the Framework for Reporting Adaptations and Modifications–Expanded (FRAME), and (2) assess the preliminary acceptability of the adapted materials through formative focus groups. Results: Materials were culturally tailored to address both deep and surface structures. Deep structure adaptations incorporated Arab cultural values, social norms, and religious practices, including Ramadan-specific content. The original 26-session curriculum was condensed to 12 weekly sessions based on prior research and stakeholder input. Surface-level adaptations included translation into Arabic and development of culturally relevant educational videos. Three formative focus groups (n = 7 total participants) provided preliminary findings of strong acceptability of simplified, culturally relevant, and digitally supported materials. Conclusions: This work will inform the adaptation of an evidence-based lifestyle change program aimed at preventing type 2 diabetes in high-risk individuals to better meet the needs of adults living in the UAE. While some countries have created their own national diabetes prevention efforts, like the United Kingdom, there is notably no similar program in the Arab world. Full article

The Mediterranean diet is widely recognized as one of the most robust dietary patterns for the prevention of chronic diseases, yet its health effects cannot be fully understood without considering the culinary practices and cultural contexts that shape food preparation and consumption. In this context, we propose the concept of Mediterranean Culinary Medicine, defined as the application of culinary medicine principles within the Mediterranean dietary model, integrating evidence-based nutrition with traditional ingredients, cooking techniques, and meal patterns. This narrative review synthesizes evidence from epidemiological, experimental, and clinical studies to examine how culinary practices may influence the nutritional quality, bioavailability of bioactive compounds, and overall health effects of the Mediterranean diet, although the strength of evidence varies across domains, with particular attention to home cooking, traditional cooking techniques, and extra virgin olive oil. We also explore the biological pathways, suggested by a combination of experimental findings and observational evidence, through which culinary practices may modulate metabolic health, including inflammation, glycemic response, and gut microbiota, as well as their potential application in addressing disease-related eating limitations such as sensory alterations, dysphagia, malnutrition, and food allergies, for example, through texture modification or flavor enhancement strategies. Finally, we highlight the social, cultural, and environmental dimensions of Mediterranean Culinary Medicine, emphasizing its role as a holistic and culturally grounded approach that facilitates the translation of Mediterranean dietary principles into sustainable and practical dietary behaviors. Overall, available evidence suggests that culinary practices are a relevant but still underexplored component of the Mediterranean diet, with the potential to improve dietary adherence and nutritional quality. However, current evidence remains heterogeneous and largely based on experimental and observational studies, highlighting the need for longitudinal and intervention studies to clarify their long-term health impact. Full article

This Perspective is dedicated to the memory of Professor Joseph Mark (Joe) Gani (1924–2016) and Professor Christopher Charles (Chris) Heyde (1939–2008), two scholars whose intellectual leadership profoundly shaped applied probability, mathematical statistics, and their interface with finance, insurance, and risk management. Their contributions extend beyond specific technical results to the development of research cultures grounded in probabilistic rigor, empirical relevance, and methodological transparency. We emphasize three enduring themes central to modern quantitative risk analysis. First, the systematic incorporation of heavy-tailed and non-Gaussian features in stochastic modeling, reflecting persistent empirical deviations from classical Gaussian assumptions in financial data. Second, the development of stochastic and time-series methodologies capable of handling dependence structures, including conditional heteroskedasticity and long-range dependence. Third, the principled integration of probabilistic modeling with data-driven and machine learning approaches, ensuring predictive performance is accompanied by interpretability and robustness. We situate these contributions within contemporary challenges in financial risk management, including systemic risk, environmental, social and governance (ESG) considerations, and climate finance. In particular, climate-related financial risks arise from both physical impacts (such as extreme weather events and long-term environmental change) and transition dynamics associated with the shift toward a low-carbon economy (including policy, technological, and market adjustments). These sources of risk introduce additional forms of dependence, nonlinearity, and model uncertainty, particularly in high-dimensional, data-rich settings. This Perspective highlights a forward-looking research agenda that preserves the foundational principles of applied probability while adapting them to modern financial systems characterized by real-time information flows and evolving risk structures. This legacy continues to shape how financial risk is modeled, measured, and understood in increasingly complex and interconnected environments. Full article

Inflation, recognized as a social determinant of health (SDOH), significantly affects the daily lives of individuals through the rising costs of food, housing, and other basic needs, all of which are public health concerns. Since the COVID-19 pandemic, inflation has become a prominent concern in the U.S. and has been linked to increased stress and poor mental health among adults. While data on inflation is tracked routinely, how it is discussed publicly is understudied. Social media platforms provide insights into how inflation is framed and experienced by the public, and these assessments may be used to determine public health needs and policy advocacy. In this study, we conducted a time-bound, platform-specific case study of inflation-related discourse on X (formerly Twitter). Analysis revealed a predominance of negative sentiments (68.5%) including frustration and distrust. Posts primarily concerned monetary policy/government spending (31.6%), Federal Reserve interest rates/financial markets (24.5%), and U.S. presidential politics (12.9%). The users did not explicitly discuss personal-level hardships, and the discussions largely focused on macro-level issues framed in polarized political perspectives. These patterns matter for public health because institutional trust shapes support for social and health policies. Our study findings suggest a fragmented social environment that may exacerbate community-wide anxiety and challenge health promotion efforts and the need for public health surveillance through surveys or personal interviews to identify and address the psychological burden of inflation. Full article

The increasing number of end-of-life (EOL) products has raised new challenges for sustainable manufacturing, especially when recycling efficiency, structural modularity and worker well-being must be considered simultaneously. From the perspective of symmetry and asymmetry in mechanical product design, this study proposes a Design for human-centric Modular Recycling (DFHMR) approach to improve EOL product recycling while reducing ergonomic risks in disassembly operations. In the proposed framework, functional similarity, structural correspondence and spatial association among components are used to characterize symmetry-oriented modular relationships, whereas asymmetric factors such as disassembly difficulty, carbon emissions, recycling profit and worker-related ergonomic risks are incorporated to describe the heterogeneity of practical recycling processes. A multi-objective optimization model is developed to maximize green disassembly performance and intra-module relevance while minimizing inter-module coupling and human-factor risks. To solve the constrained modular design problem, an enhanced social engineering optimizer (SEO) is introduced to balance global exploration and local exploitation. A turbo reducer case study is conducted to validate the proposed model, and comparative experiments with several multi-objective optimization algorithms demonstrate the effectiveness and robustness of the enhanced SEO. The results indicate that the DFHMR framework can provide decision-makers with a set of balanced modular recycling schemes, offering a practical reference for symmetry-oriented, sustainable and human-centered mechanical design under Industry 5.0. Full article

The third United Nations Sustainable Development Goal promotes health and well-being. Despite the existence of academic literature examining the relationship between health and income inequality, evidence on the role of healthcare systems in this inequality remains limited. This article aims to analyse the extent to which healthcare systems are associated with differences in economic inequality. To this end, a balanced panel of 27 European Union countries for the period 2005–2022 is used, applying t-tests for differences in means and linear regression models using S80/S20, Gini and Palma inequality measures. The main results show that countries with a Social Health Insurance System (SHIS) exhibit, on average, lower levels of income inequality, despite not being the highest spenders on healthcare. On the other hand, healthcare expenditure has a negative and statistically significant relationship with inequality, whereas in countries with a Mixed Healthcare System (MHS), this association is not statistically significant. A disaggregated analysis of public and private spending indicates that public expenditure is particularly relevant in SHIS countries being negatively associated with income inequality, whereas this relationship differs in countries with a National Health System (NHS). Thus, it is concluded that healthcare systems display significant differences in the relationship under study. Full article

Research traditionally examines the spatial distribution of urban parks through the lens of spatial equity, overlooking the intricate interaction between the physical foundation of park construction and historical processes. Grounded in the theory of material geography, we investigate the mechanisms underlying the spatio-temporal evolution of urban parks in Shenzhen. We conduct topographical analysis and examine relevant historical policy texts to explore the ‘production of nature’ in China’s post-Mao urbanisation. We find that the distribution of urban parks in Shenzhen is not merely a result of social choice but a product of the interplay between material natural endowments—centred on topography—and urban spatial policies across historical stages. During rapid urbanisation, government-led spatial policies functionally reorganised and assigned symbolic meanings to diverse topographical features, such as plains, hills, and coastal areas, transforming them into urban parks that support capital accumulation and urban upgrading. The proposed ‘topography–policy’ synergistic framework transcends neutral spatial descriptions, revealing the nexus between the commodification of nature and urban governance. We clarify the rationale for the creation of contemporary urban green spaces in China and offer novel theoretical and empirical insights into sustainable urban transformation worldwide. Full article

Background: Puberty is a period of visible bodily change, heightened self-consciousness, and increased sensitivity to social evaluation. While prior studies have linked pubertal development to broad psychological outcomes, less attention has been given to adolescents’ social evaluative distress, defined here as discomfort when feeling looked at or talked about by others. Parenting style may also be relevant to this outcome. Methods: Using secondary survey data from 3591 secondary-school students in Shenzhen, China, this study employed Bayesian analysis to examine whether puberty stress, authoritarian parenting, and permissive parenting were associated with adolescents’ social evaluative distress, and whether authoritarian and permissive parenting moderated the association between puberty stress and social evaluative distress. Results: Puberty stress was positively associated with social evaluative distress, and authoritarian parenting was also positively associated with this outcome. Permissive parenting did not show a clear direct association. Neither authoritarian nor permissive parenting showed clear evidence of moderating the association between puberty stress and social evaluative distress. Conclusions: Social evaluative distress during adolescence appears to be associated more clearly with puberty stress and authoritarian parenting as direct correlates than with interaction effects between puberty stress and parenting style. The study extends existing literature by focusing on a narrower, socially focused form of adolescent distress in the Chinese context. Full article

Mobile payment services are increasingly embedded in everyday digital consumption, yet their sustainability relevance should not be assumed solely from technological adoption. This study conceptualizes sustainable mobile payment consumption as a relational and digital sustainability issue, reflected in the continuity, trust, diffusion, and resilience of mobile payment ecosystems rather than as a direct measure of environmental sustainability. Drawing on perceived value theory, relationship marketing, social exchange theory, and trust-based consumption logic, this study examines how mobile payment perceived value (MPPV) is associated with customer advocacy through customer experience and customer loyalty, while considering customer trust as a boundary condition. Survey data collected from 382 mobile payment users in Lebanon were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings suggest that MPPV is positively associated with customer experience, customer loyalty, and customer advocacy. Customer experience is positively associated with loyalty while loyalty is positively associated with advocacy. The sequential mediation results are consistent with the proposed relational pathway in which holistic perceived value is linked to advocacy through experience and loyalty rather than through transactional evaluations alone. Customer trust strengthens the associations between MPPV and both loyalty and advocacy, suggesting that trust amplifies value-based relational outcomes in high-uncertainty financial environments. The central finding is that holistic perceived value becomes sustainability-relevant when channeled through accumulated experience and loyalty into advocacy, and that this relational pathway is contingent on trust, a mechanism particularly consequential in Lebanon’s high-uncertainty financial environment. By positioning advocacy as a sustainability-relevant relational outcome, this study clarifies how perceived value, experience, loyalty, and trust jointly contribute to sustainable digital consumption in an emerging economy. Full article

Large Language Models (LLMs) offer opportunities for processing heterogeneous information streams relevant to energy-market decision-making, but their practical role in forecasting-oriented analytical workflows remains uncertain. This paper presents an exploratory feasibility study of LLM use across four energy-market tasks: geopolitical event monitoring for Dutch Title Transfer Facility (TTF) market context using Global Database of Events, Language, and Tone (GDELT)-based data, structured summarisation of commodity-intelligence articles, prompt-engineered solar-power and grid-load forecasting for Austria, and a short-horizon exploratory TTF price-estimation case. The study is positioned as a pilot investigation and hybrid workflow blueprint rather than as a statistically conclusive forecasting benchmark. A four-layer reference architecture was devised, including structured market data, semi-structured news intelligence, web-scraping concepts, and implemented Twitter/X and GDELT monitoring layers. The empirical cases indicate that LLMs are most useful for text-heavy reasoning, event-context integration, source triage, and structured interpretation. In the 20-article summarisation corpus, Gemini 1.5 Pro achieved higher commodity-direction accuracy than GPT-4, while GPT-4 showed stronger output-format stability. In selected solar case checks, OpenAI models produced plausible generation curves close to the Fraunhofer ISE Energy Charts reference, while Energy Charts remained more accurate for aggregate load estimation in the available benchmark comparison. The two-day TTF experiment illustrated that LLMs can incorporate qualitative geopolitical context into short-horizon reasoning, but it did not establish reliable price-forecasting capability. The Twitter/X monitoring layer is retained as a documented negative pathway, showing the limitations of informal social-media scraping for reproducible market intelligence. Full article

Children’s food choices are shaped early in life through cognitive, social, and environmental influences, yet relatively little is known about how school-based nutrition education supports these processes in routine settings. This study examined mechanisms potentially relevant to children’s food choices using a multi-source process evaluation of the municipal “I Know What I Eat” program implemented in Warsaw primary schools. A prospective observational implementation study was conducted in 81 public schools, covering 198 workshop cycles for students aged 8–9 years. Data were obtained from teacher-observers (n = 198), trained program implementers (n = 6), and implementation records. The evaluation focused on implementation quality, fidelity, acceptability, and mechanisms relevant to food-related decision-making. Quantitative data were analyzed using descriptive statistics, Kruskal–Wallis tests, and Spearman correlations; qualitative comments were examined using content analysis. The program was implemented with high quality and consistency, with mean ratings ranging from 4.88 to 4.96 on a five-point scale and no significant differences by implementer or class size. Qualitative findings indicated that experiential learning, practical food preparation, peer interaction, and active participation supported children’s engagement. These findings suggest that school-based nutrition education can create conditions relevant to food-related decision-making, although direct behavioral measures are needed. Full article

Generative artificial intelligence (GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences (HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI’s capabilities. Yet, systematic evidence on the educational impacts of GenAI on HSS students remains limited. Addressing this gap, this study draws on a large-scale survey of HSS students in China to examine its role in academic development. Guided by relevant learning theories, this study focuses on four dimensions: patterns of use, effects on learning processes and academic performance, challenges associated with GenAI use, and preferred approaches to curricular integration. We found that more than half perceived enhanced learning motivation, independent thinking and creativity, although a substantial minority reported little change or even decline. Comparatively, a notably larger majority reported academic performance gains, although these gains may partly reflect limitations in conventional assessment practices. The study identifies variations in perceived learning and performance improvements among students with differing durations of GenAI experience, along with observable disciplinary differences and modest gender differences. While an overwhelming majority valued the importance of ethical considerations, only slightly more than half were satisfied with privacy protection. Limited accuracy and overreliance emerged as the most pressing concerns reported by students. Students favored partial or optional curricular integration supported by practice-oriented training, and widely recognized GenAI’s significance for their future professional development. Grounded in student perspectives, this study offers evidence-based recommendations for the responsible and pedagogically meaningful integration of GenAI. Full article

Sexual violence against women frequently originates during adolescence, when structural inequalities and gendered power dynamics heighten vulnerability, making early identification of risk factors essential to prevent trajectories leading to sexual exploitation. This study presents the psychometric validation of the EDR-ESIA, a screening instrument designed to detect vulnerability to Child Sexual Exploitation (CSE) in healthcare, education, and social care settings, with particular relevance for prevention strategies targeting adolescent girls. The sample comprised 199 adolescents aged 11–17 years (M = 15.23; SD = 1.59) residing in Spain (58.8% female, 40.2% male, 1.0% unspecified), assessed by trained professionals using case records and reports. The 88-item instrument underwent expert review and pilot testing prior to validation, and its internal structure was examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicated that all subdimensions and higher-order constructs showed an adequate fit to the theoretical model, supporting the instrument’s validity. Female adolescents scored significantly higher than males on CSE target indicators, reflecting a medium-to-large gender difference in vulnerability levels. Overall, the EDR-ESIA constitutes an evidence-based instrument for the timely recognition of CSE vulnerability, supporting prevention, education, and intervention efforts aimed at reducing sexual violence against women from early developmental stages. Full article