Search Results (3,345)

Conversational agents are transforming digital interactions across various domains, including healthcare, education, and customer service, thanks to advances in large language models (LLMs). As these systems become more autonomous and ubiquitous, understanding what constitutes high-quality interaction from a user perspective is increasingly critical. Despite growing empirical research, the field lacks a unified framework for defining, measuring, and designing user-perceived interaction quality in human–artificial intelligence (AI) dialogue. Here, we present an integrative review of 125 empirical studies published between 2017 and 2025, spanning text-, voice-, and LLM-powered systems. Our synthesis identifies three consistent layers of user judgment: a pragmatic core (usability, task effectiveness, and conversational competence), a social–affective layer (social presence, warmth, and synchronicity), and an accountability and inclusion layer (transparency, accessibility, and fairness). These insights are formalised into a four-layer interpretive framework—Capacity, Alignment, Levers, and Outcomes—operationalised via a Capacity × Alignment matrix that maps distinct success and failure regimes. It also identifies design levers such as anthropomorphism, role framing, and onboarding strategies. The framework consolidates constructs, positions inclusion and accountability as central to quality, and offers actionable guidance for evaluation and design. This research redefines interaction quality as a dialogic construct, shifting the focus from system performance to co-orchestrated, user-centred dialogue quality. Full article

22q11.2 deletion syndrome (22q11.2DS) is the most common recurrent microdeletion in humans and a prototypical high-risk neurogenetic copy number variant (CNV) associated with a broad spectrum of neurodevelopmental and psychiatric disorders, including intellectual disability (ID), autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), anxiety, and psychotic symptoms. This hemizygous deletion encompasses multiple genes involved in brain development and neural circuit function, contributing to marked phenotypic variability and multisystem involvement. In pediatric populations, deficits in adaptive functioning are frequently reported and may occur independently of global intellectual impairment, reflecting broader behavioral vulnerabilities within this genetic risk architecture. Background/Objectives: This study aimed to characterize the sociodemographic, clinical, and intellectual profiles of children and adolescents with 22q11.2DS and to examine adaptive functioning and its associations with behavioral difficulties. Methods: Thirty-four patients aged 1–17 years with a confirmed molecular diagnosis of 22q11.2DS were assessed. Standardized instruments were used to evaluate cognitive performance, adaptive functioning, and behavioral outcomes. Results: Intellectual disability was highly prevalent, with most participants showing combined cognitive and adaptive impairments. Adaptive functioning was compromised across domains, with relatively higher socialization scores compared to other areas, such as daily living skills. Multivariate analyses indicated associations between sociodemographic factors and behavioral difficulties, as well as between social problems and lower global adaptive functioning. Conclusions: Together, these findings contribute to the characterization of the adaptive and behavioral phenotype associated with a high-risk neurogenetic CNV and highlight the relevance of adaptive functioning as a key outcome for early evaluation and intervention in pediatric 22q11.2DS. Full article

Residential barbecuing is becoming increasingly popular worldwide, especially in cities, where it is not only a leisure activity but also an important social and cultural practice. Consequently, the number of grills and smokers in use continues to grow. This study evaluated the environmental performance of a household wood-pellet barbecue dual-function smoker/grill using a life cycle assessment (LCA) approach. The functional units selected were per cooking time (1 h) and per unit of energy delivered (1 kWh) at different cooking settings on the smoker. The results show that most of the impacts, including global warming potential (GWP) and resource use, originate from the production of the smoker itself, whereas emissions released during combustion, especially NO_x, are the main contributors to impacts such as acidification and smog formation. The GWP per hour of operation ranged from 0.44 to 0.63 kg CO₂ eq. From an operational perspective, cooking at intermediate temperatures (between 110 and 175 °C) generally leads to lower impacts per hour than very low-temperature smoking. When considering entire meals, meat typically accounts for most of the total impact, with the smoker’s contribution comparatively small. Overall, the study provides a useful reference and shows that both equipment design and food choices play a role in barbecue sustainability. Full article

Selecting a sustainable healthcare waste treatment method is a complex multi-criteria problem influenced by environmental, economic, social and technological factors. This study addresses key gaps in the literature by proposing an intuitionistic fuzzy AHP–TOPSIS framework that explicitly models cognitive uncertainty and expert hesitation, while demonstrating its application through a real-world case study in Adana, Türkiye. In contrast to prior studies utilizing fewer criteria, our framework evaluates four treatment alternatives—incineration, steam sterilization, microwave, and landfill—across 17 comprehensive criteria that directly integrate circular economy principles such as resource recovery and energy efficiency. The results indicate that steam sterilization is the most sustainable option, demonstrating superior performance across environmental, economic, social, and technological dimensions. A 15-scenario sensitivity analysis ensures ranking resilience across varying decision contexts. Furthermore, a systematic comparative analysis highlights the methodological advantages of the proposed framework in terms of analytical granularity and robustness compared to existing models. The study also offers step-by-step operational guidance, creating a transparent and policy-responsive decision-support tool for healthcare waste management authorities to advance sustainable practices. Full article

Understanding the economic performance of heritage-rich towns requires a systematic evaluation of how heritage-related components collectively contribute to revenue generation. Existing studies often examine heritage assets, socio-cultural factors, physical infrastructure, and local economic conditions independently, resulting in fragmented insights that limit comprehensive planning for local economic development. This study develops and validates an integrated Cultural Heritage Economy Model that quantifies the influence of heritage resources, social, physical, and economic aspects on revenue generation in heritage contexts. The model is conceptualized through a structured synthesis of theoretical literature and domain-specific indicators, followed by construct operationalization, expert validation, and pilot-level assessment. Using Structural Equation Modelling (SEM-PLS), the study demonstrates strong reliability, convergent validity, discriminant validity, and significant structural relationships. The predictive relevance of the final model is further evaluated through PLSpredict, confirming its suitability for future estimation. The findings confirm that revenue generation is a product of the combined and mutually reinforcing effects of heritage, socio-cultural, physical, and economic dimensions, rather than just by the influence of heritage resources. By offering this novel, empirically grounded, multidimensional framework to estimate heritage-driven economic outcomes, this research establishes a foundational model that can guide evidence-based resource allocation, policy formulation, and long-term sustainable urban development planning. Full article

Artificial intelligence (AI) promises large productivity gains, yet growing concern surrounds its implications for social sustainability. This paper develops and empirically evaluates a simple behavioral framework in which unequal access to AI generates mutually reinforcing gaps in economic performance and social visibility, potentially undermining the long-run stability of social systems. Individuals fall into two groups—AI adopters and non-adopters—and differences in productivity and social recognition give rise to two exchange rates: an Economic Exchange Rate (EER), capturing relative economic advantage, and a Social Exchange Rate (SER), capturing relative social visibility and recognition. AI strengthens the feedback between economic success and social standing, and the joint evolution of EER and SER is stable only when the product of two feedback parameters lies below unity. When this threshold is approached, the system enters a regime of systemic disequilibrium, in which economic and social disparities expand endogenously. Using panel data for 30 economies over the period 2012–2025, we provide empirical evidence of strong mutual reinforcement between economic and social advantage, with feedback strength rising as AI diffusion accelerates. The findings suggest that unequal AI access poses risks not only to equality but to social sustainability itself. The paper contributes a diagnostic framework for socially sustainable AI diffusion, highlighting the need for policies that dampen amplification mechanisms and strengthen inclusive pathways from economic performance to social recognition. Full article

Accurate electricity carbon emission factors are crucial for assessing overall social carbon emissions and achieving China’s “dual carbon” goals. This paper proposes a dynamic correction model that integrates lifecycle extension, power exchange networks, and multi-time-scale decomposition to address the limitations of static carbon emission factors. The model considers factors such as power generation structure, cross-regional transmission, clean energy proportion, line losses, and non-CO₂ greenhouse gas emissions, and achieves dynamic correction at quarterly and monthly scales, enhancing timeliness and regional adaptability. Results show that transmission losses, energy structure, and inter-provincial electricity exchange significantly impact carbon emission factors. For instance, in 2022, line losses in Xinjiang and Gansu raised the electricity carbon emission factor by over 0.06 kgCO₂/kWh. Monthly factors exhibit significant seasonal fluctuations, with some regions showing variations of up to 105% of the annual average. Areas rich in hydropower, such as Yunnan, Sichuan, and Qinghai, experience pronounced fluctuations, highly sensitive to changes in water volume, offering more accurate reflections of carbon emission changes during electricity consumption. This study presents a refined dynamic correction method for electricity carbon emission accounting, providing theoretical support for carbon emission policy development and performance evaluation. Full article

Obesity is associated with multiple comorbidities and therefore requires a multidisciplinary approach. Particular attention is given to the role of visceral adiposity and its impact on quality of life. Childhood obesity, in particular, is a major global public health challenge with physical, psychological, and social consequences extending into adulthood. Within the framework of personalized medicine, assessing physical fitness and health-related quality of life (HRQoL) offers valuable insight for defining individualized therapeutic goals. Objective: To evaluate the relationship between physical fitness and HRQoL in children with simple obesity and to highlight the potential value of personalized approaches in pediatric obesity management. Methods: This study included 123 patients aged 8–16 years with simple obesity who were hospitalized at the Children’s Memorial Health Institute in Warsaw. Obesity was diagnosed according to CDC growth charts (OLAF study). Physical fitness was assessed using the EUROFIT test battery (8 trials), and HRQoL was measured with the Kidscreen-52 questionnaire (10 domains). Results: The overall EUROFIT test performance in the study group was significantly lower compared with population norms (p < 0.001). Similarly, HRQoL scores reported by both children and their parents were significantly below reference values (p < 0.001). Conclusions: Reduced physical fitness is strongly associated with impaired quality of life in children with obesity. Personalized interventions aimed at improving motor performance may represent an effective strategy in the prevention and treatment of pediatric obesity. Full article

This study evaluates the agri-environmental performance of the EU-27 Member States using the PROMETHEE multiple-criteria decision analysis method, based on three Eurostat indicators linked to the sustainability pillars: Harmonized Risk Indicator 1 (HRI1, social pillar), pesticide sales intensity (kg/ha UAA, environmental pillar), and environmental protection investments (% GDP, economic pillar). The analysis uses the most recent available Eurostat data (primarily from 2023) and examines three weighting scenarios: (i) equal weights, (ii) higher emphasis on the economic pillar, and (iii) higher emphasis on the environmental and social pillars. Across all scenarios, Slovenia ranked first (net flow, φ = 0.4173 to 0.4734), followed by Czechia (φ = 0.2796 to 0.3260) and France (φ = 0.1886 to 0.2240), while Malta (φ = −0.3356 to −0.3691), Cyprus (φ = −0.2916 to −0.3027), and Estonia (φ = −0.2641 to −0.2903) consistently occupied the lowest positions. The stability of rankings across alternative weighting schemes indicates robust performance patterns, with minimal shifts for most Member States. Overall, the results highlight persistent cross-country differences in agri-environmental performance despite common EU regulatory frameworks, underlining the relevance of national implementation capacity and investment strategies. The proposed PROMETHEE-based ranking provides a transparent and policy-aligned benchmarking tool that can support monitoring and prioritization of interventions related to pesticide risk reduction and environmental investment across EU Member States. Full article

In the context of high-quality urbanization, a key challenge for urban agglomerations is the structural mismatch between economic linkages and rapidly expanding information interactions, which may constrain the performance of coupled systems under shocks. Taking the Beijing–Tianjin–Hebei (BTH) urban agglomeration as a case, we construct an inter-city economic network from cross-city corporate investment ties and an information network from online attention flows, and further derive an economic–information coupled network using a coupling-coordination framework. Using social network analysis and resilience assessment (hierarchy, assortativity, clustering, and disruption simulations), we compare network structures in 2013 and 2023 and evaluate how the structural gap shapes coupled resilience. Results show that (i) economic ties strengthen steadily but moderately, whereas the information network expands faster and becomes more inclusive, widening the structural gap between “virtual” and “material” flows; (ii) despite a persistently high correlation between the two layers, coordination declines, indicating increasing local divergence in link organization; and (iii) resilience improves overall, but differentiation remains: the information network gains robustness through decentralization and redundancy, while the economic network is more sensitive to targeted removals of core nodes, and the coupled network exhibits intermediate performance. These findings suggest that enhancing BTH resilience requires strengthening cross-jurisdictional redundant links and reducing excessive dependence on core corridors to better translate information interactions into balanced economic connectivity. Full article

Background/Objectives: Patient-level factors strongly influence antimicrobial resistance (AMR) through the pressure applied to healthcare professionals to prescribe antibiotics even for self-limiting viral infections, enhanced by knowledge and attitude concerns. This includes Africa, with high levels of AMR. However, validated measurement tools for African primary healthcare (PHC) are scarce. This study evaluated the reliability, structural validity, and interpretability of the Community Antimicrobial Use Scale (CAMUS) in South Africa. Methods: A cross-sectional survey was conducted with 1283 adults across 25 diverse public PHC facilities across two provinces. The 30-item theory-based tool underwent exploratory and confirmatory factor analysis (EFA/CFA), reliability, and validity testing. Results: EFA identified a coherent five-factor structure: (F1) Understanding antibiotics; (F2) Social and behavioural norms; (F3) Non-prescribed use; (F4) Understanding of AMR; and (F5) Attitudes. Internal consistency was strongest for knowledge and misuse domains (alpha approximation 0.80). Test–retest reliability was good-to-excellent (ICC: 0.72–0.89). CFA confirmed acceptable composite reliability (CR ≥ 0.63). Although average variance extracted (AVE) was low for broader behavioural constructs, indicating conceptual breadth, it was high for AMR knowledge (0.737). Construct validity was supported by positive correlations with health literacy (r = 0.48) and appropriate use intentions (r = 0.42). Measurement error metrics (SEM = 1.59; SDC = 4.40) indicated good precision for group-level comparisons. Conclusions: CAMUS demonstrated a theoretically grounded structure with robust performance in knowledge and misuse domains. While social and attitudinal domains require refinement, we believe the tool is psychometrically suitable for group-level antimicrobial use surveillance and programme evaluation in South African PHC settings and wider to help with targeting future educational programmes among patients. Full article

The increasing need to regenerate public housing stock highlights the importance of adopting integrated evaluation tools capable of supporting transparent, sustainable, and public value-oriented investment decisions. This study compares two alternative intervention strategies—renovation with extension and demolition followed by reconstruction—by applying a Cost–Benefit Analysis (CBA) model developed in two phases. In the first phase, the analysis focuses on social benefits, with the aim of assessing their contribution to collective well-being. The second phase incorporates potential energy-related benefits, estimated on the basis of performance improvements associated with the two design scenarios. The results demonstrate that the integrated consideration of economic, social, and energy–environmental dimensions affects the relative performance differences between the examined strategies, offering a more comprehensive evaluation framework than conventional approaches based solely on monetary costs. The proposed model, which is replicable in Mediterranean contexts, contributes to the ongoing international debate on ex ante evaluation tools and provides operational insights to support urban regeneration policies oriented towards more effective, equitable, and policy-consistent solutions, in line with the objectives of the European Green Deal and the 2030 Agenda. The two-phase structure allows decision-makers to distinguish between short-term social effects and long-term energy-related benefits, offering a transparent support tool for public investment choices under fiscal constraints. Full article

Historic waterfront streets are not only an important component of urban public spaces but also highlight the distinctive features and historical contexts of the city. High-quality streetscape visual perception plays a crucial role in advancing the cultural, social, environmental, and economic sustainability of the urban street space. This study was initiated to construct a multi-dimension and multi-scale comprehensive evaluation framework to assess the visual quality of waterfront streets, taking “Water City” Liaocheng as a typical case. Technical methods of semantic segmentation, sDNA (Spatial Design Network Analysis), GIS (Geographic Information System), and statistical analysis were utilized. Following the extraction and classification of street space elements, a multi-dimensional evaluation index system of natural coordination, artificial comfort, and historical culture for the visual assessment was established. Space syntax was performed on waterfront streets by sDNA to quantify macro-level scale spatial structure and meso-level scale pedestrian accessibility. The results of micro-scale visual perception, meso-scale behavioral walkability, and macro-scale spatial structure, were integrated to construct a multi-scale diagnostic framework for eight classifications. This framework provides a scientific basis to put forwards the refined and sustainable optimization strategies for historic waterfront streets. Full article

The rapid proliferation of misinformation on social media underscores the urgent need for scalable digital-literacy instruction. This study presents the design and evaluation of a Generative AI-enhanced serious game system that integrates Large Language Models (LLMs) to drive adaptive non-player characters (NPCs). Unlike traditional scripted interactions, the system employs role-based prompt engineering to align real-time AI dialogue with the Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) framework, enabling dynamic scaffolding and authentic misinformation scenarios. A mixed-method experiment with 60 undergraduate students compared this AI-driven approach to traditional instruction using a 40-item digital-literacy pre/post test, the Intrinsic Motivation Inventory (IMI), and open-ended reflections. Results indicated that while both groups improved significantly, the game-based group achieved larger gains in credibility-evaluation performance and reported higher perceived competence, interest, and effort. Qualitative analysis highlighted the HCI trade-off between the high pedagogical value of adaptive AI guidance and technical constraints such as system latency. The findings demonstrate that Generative AI can be effectively operationalized as a dynamic interface layer in serious games to strengthen critical reasoning. This study provides practical guidelines for architecting AI-NPC interactions and advances the theoretical understanding of AI-supported educational informatics. Full article

Background. Rheumatoid arthritis (RA) is a chronic autoimmune disease frequently accompanied by cardiovascular, respiratory, skeletal, psychiatric, and neoplastic comorbidities that are associated with higher morbidity and poorer health-related quality of life (HRQoL). This study evaluated the associations between comorbidities and patient-reported physical health, emotional distress, daily functioning, and social relationships in adults with RA and explored patient-reported unmet needs relevant to integrated care. Methods. We conducted a cross-sectional survey among 286 adults with physician-confirmed RA, using a structured questionnaire (ICRA-Q) administered between June and July 2025 via online platforms and in-hospital supervised completion. The survey captured demographics, patient-reported physician-diagnosed comorbidities (current and/or past), perceived disease impact, functional limitations, emotional and social consequences, access to treatment, financial burden, and support needs. Analyses included descriptive statistics, χ² tests, t-tests/ANOVA, effect sizes (Cramer’s V and standardized mean differences), and multivariable logistic regression to explore predictors of high HRQoL impact and high difficulty in disease management. An exploratory classification into high-risk phenotypes was performed using predefined clinical, psychological, and socioeconomic criteria. Results. Most participants (98.6%) reported at least one comorbidity, most commonly hypertension, osteoporosis, and cardiovascular disease. Higher comorbidity burden and depression/anxiety were strongly associated with higher pain, reduced mobility, emotional distress, and financial strain. Exploratory high-risk phenotypes (severe somatic multimorbidity, high psychological vulnerability, high socioeconomic burden, and a composite very high-risk profile) were associated with poorer HRQoL indicators. Younger age, shorter disease duration, and higher perceived social support were associated with lower perceived burden. Conclusions. In this cross-sectional, patient-reported study, comorbidity burden—particularly psychological comorbidity—was strongly associated with poorer HRQoL and greater management difficulty in RA. These findings support the need for multidisciplinary, integrated care pathways; however, subgroup phenotypes should be considered exploratory and require external validation. Full article