Search Results (605)

Background/Objectives: Hidradenitis Suppurativa (HS) is a chronic inflammatory skin disease associated with a significant impairment in patients’ quality of life (QoL). However, evidence on QoL assessment in HS remains fragmented, with heterogeneous instruments and domains reported. This scoping review aimed to map the assessment of QoL in individuals with HS, identify the instruments used, and describe the domains explored. Methods: This scoping review was conducted in accordance with the Arksey and O’Malley framework, as refined by Levac et al. and the Joanna Briggs Institute. A systematic search of six databases was performed between November 2025 and March 2026 to identify studies reporting QoL or patient-reported outcomes (PROs) in individuals with HS. Data were extracted and analyzed using a narrative synthesis approach. Results: A total of 21 studies met the inclusion criteria. HS was consistently associated with substantial QoL impairment across multiple domains, including physical, psychological, social, sexual, and occupational aspects. Symptom burden was a major determinant of reduced QoL, particularly pain, pruritus, malodor, and discharge. A wide range of instruments was used, with the Dermatology Life Quality Index (DLQI) being the most frequently applied. However, most tools did not adequately capture the multidimensional impact of HS. The use of HS-specific instruments was limited, and most studies adopted cross-sectional designs. Conclusions: QoL in HS is markedly compromised, but current assessment approaches are inconsistent and incomplete. Further research using comprehensive, disease-specific instruments and longitudinal designs is needed to better capture disease burden and support patient-centered care. Full article

This study analyzes educational migration patterns in small towns across Dambovita County, Romania, focusing on spatial accessibility and gender disparities. Officially designated as Rank III urban settlements under national legislation, these small towns face structural regional imbalances. The research is based on a comprehensive structured questionnaire administered to a target sample of 143 graduates from 15 high schools across the surveyed municipalities. Given that the data collection depended on institutional access granted by school administrations, a non-probability purposive sampling approach was employed. The survey incorporated open-ended and closed-ended items capturing students’ institutional choices, secondary education profiles, intentions to pursue matching higher education fields, and underlying motivations. Survey data were integrated with spatial analysis methods using QGIS 3.34 version isochrones modeling and the OpenRouteService (ORS) Matrix to evaluate travel times and distances to competing regional university centers. The results reveal gender-based patterns differences in student mobility: female high school students concentrate on a single metropolitan destination, whereas male high school students are more broadly distributed secondary vocational nodes. Ultimately, this research contributes to understanding how gender intersects with educational migration and highlights the influence of transport infrastructure and spatial friction in students’ decision-making processes. Full article

Generative AI (GenAI) adoption in higher education (HE) raises significant ethical concerns. The focus is shifting from rules- or outcomes-based learning environments towards the development of moral character, personality traits, integrity, and practical wisdom (phronesis). However, most existing AI ethics validation instruments are predominantly shaped by Global North paradigms. In Global South HE contexts, in particular, open distance e-learning (ODEL) HE institutions (HEIs) characterised by limited direct supervision and a digital divide, validation remains scant. Ethical risks are intensified by the adoption and integration of GenAI tools, such as large language models (LLMs), to enhance teaching, learning, research, and student support, thus recognising the need to develop and validate virtue ethics scales. The current paper attempts to address this gap by validating the Virtue Ethics Measurement Scale (VEMS) within South Africa’s largest comprehensive ODEL institution. Guided by the positivist paradigm, a 36-item cross-sectional survey of 503 undergraduate and postgraduate students measured six virtue dimensions (justice, honesty, responsibility, care, prudence, and fortitude). Confirmatory factor analysis (CFA) compared four competing models. The single-factor model showed poor fit, rejecting unidimensionality. A second-order hierarchical model demonstrated an acceptable fit (χ²/df = 2.992, CFI = 0.933, RMSEA (Root Mean Square Error of Approximation) = 0.063, SRMR (Standardized Root Mean Squared Residual) = 0.043) with subscale reliabilities ranging from Cronbach’s α = 0.84 to 0.90, supporting a multidimensional yet hierarchical virtue structure. The VEMS offers a psychometrically sound instrument for evaluating ethical AI use in ODEL institutions. This aligns with virtue ethics theory, which emphasises that moral character is a constellation of dispositions (e.g., honesty, care, prudence) rather than a single trait. The VEMS thus enables HEIs to assess students’ virtues, design targeted ethics capacity-development programmes, and inform policy reform for responsible GenAI adoption in under-researched Global South HE settings. Full article

Background: Sustainable leadership has emerged as a critical approach for promoting long-term organizational effectiveness and workforce well-being in healthcare settings. However, empirical evidence linking sustainable leadership to workplace integration and resilience among nurses remains limited. Objective: This study aimed to examine the association between sustainable leadership and both workplace integration and resilience among staff nurses. Methods: A descriptive cross-sectional correlational design was used. Data were collected from 200 staff nurses working in intensive and intermediate care units at a tertiary healthcare institution. Standardized instruments were used to measure sustainable leadership, workplace integration, and resilience. Data were analyzed using descriptive statistics, Pearson correlation, and linear regression analysis. Results: Sustainable leadership was positively associated with workplace integration (r = 0.43, p < 0.001) and resilience (r = 0.24, p < 0.001). Regression analysis indicated that sustainable leadership was associated with workplace integration (β = 0.43, R² = 0.18, p < 0.001) and resilience (β = 0.24, R² = 0.10, p < 0.001), explaining a modest proportion of variance in both outcomes. Conclusions: Sustainable leadership is significantly associated with improved workplace integration and resilience among nurses. Healthcare organizations should adopt sustainable leadership practices such as providing consistent mentorship and professional development chances to improve workplace integration, and implementing supportive supervision and wellness initiatives to improve nurse resilience. However, the relatively low explained variance suggests that additional individual and organizational factors contribute to these outcomes. Therefore, sustainable leadership should be integrated with complementary strategies, including peer support programs and workload management interventions, to comprehensively strengthen workforce integration and resilience. Full article

This study assesses the multi-dimensional impacts of large-scale urban mass transit infrastructure on network sustainability and individual mobility behavior, using the newly operational Riyadh Metro as a case study. Adopting a qualitative interpretive synthesis method, the research integrates peer-reviewed literature, institutional policy reports, and early operational datasets to evaluate transit outcomes across network accessibility, spatial equity, and localized environmental constraints. The study shows the interactions between infrastructure provision, urban form, and climatic conditions. The results reveal that while the infrastructure significantly enhances raw corridor accessibility, its systemic impact is heavily constrained by extreme climatic conditions, institutional fragmentation, and critical first- and last-mile gaps. Extreme heat significantly reduces effective walking. Additionally, continued reliance on private vehicles, resulting in a hybrid mobility regime rather than a full modal transition. The analysis also further reveals uneven spatial distribution of the metro for easy accessibility. To overcome these barriers, this paper introduces the Climate-Constrained Sustainable Transit Transition Framework (CSTTF) as an analytical tool. The study concludes that infrastructure-led urban transformation in hyper-arid megacities requires a comprehensive policy shift that integrates land-use reform, behavioral incentives, and climate-adaptive urban design. The proposed Climate-Constrained Sustainable Transit Transition Framework (CSTTF) provides a transferable decision-support framework that can assist policymakers, urban planners, and transit agencies in designing climate-resilient metro systems, optimizing first- and last-mile connectivity, and informing sustainable transport planning in Riyadh and other hot-arid metropolitan regions facing similar environmental and urbanization challenges. Full article

The National Big Data Comprehensive Pilot Zone (NBDCPZ) constitutes a landmark institutional initiative designed to advance and deploy data elements while strengthening governance capacity for environmental sustainability and low-carbon transition. Drawing on a panel dataset covering 285 Chinese cities at or above the prefectural level over the 2005–2023 period, this study capitalizes on the sequential rollout of the NBDCPZ to establish a quasi-natural experimental design. It employs a staggered difference-in-differences (DID) design to examine the policy’s causal effects on urban environmental quality—specifically, its effectiveness in curbing air pollution and carbon emissions—and further identifies the underlying mechanisms driving these effects and sources of contextual heterogeneity. The results demonstrate that the policy yields substantial benefits in curbing urban pollution and advancing carbon reduction; this conclusion remains robust across multiple sensitivity checks. Mechanism analysis reveals that the policy achieves synergistic gains in pollution reduction and carbon mitigation by promoting green innovation and reducing energy consumption, as well as by fostering digital industry agglomeration and accelerating digital innovation. Heterogeneity analysis shows significant structural variation in policy effects: non-resource-based cities exhibit more pronounced carbon mitigation effects, whereas resource-based cities, large cities, and old industrial bases demonstrate stronger pollution control effects. Full article

Purpose: This study conducts a systematic literature review on the intersection of real estate exposure and geotechnical hazards, focusing specifically on seismic and subsurface risks. The objective is to synthesize key thematic trends, methodologies, and governance frameworks that inform risk-informed planning in seismically vulnerable urban areas. Design/methodology/approach: A Boolean search query was implemented on Lens.org, identifying 55 peer-reviewed articles published between January 2020 and May 2025. Inclusion criteria required explicit focus on property exposure to seismic or ground instability risks. Thematic analysis was conducted based on title and abstract data, supported by a Python (version 3.11)-generated word cloud to inductively identify five core clusters: (1) seismic assessment and earthquake risk, (2) building vulnerability and structural performance, (3) subsurface hazards and ground instability, (4) urban areas, heritage, and social vulnerability, and (5) risk mitigation, planning, and resilience frameworks. Findings: The review reveals a shift from hazard-centric, engineering-based models toward integrated, multi-scalar frameworks that embed risk within socio-economic, spatial, and institutional contexts. While consensus exists on the importance of probabilistic modeling, retrofitting, and GIS-based tools, divergences persist around behavioral valuation, policy uptake, and equity in implementation. Heritage cities and informal settlements emerge as under-addressed but critically vulnerable domains. Originality/value: This study systematically maps interdisciplinary research on real estate exposure to seismic and subsurface risks post-2020. By bridging engineering, planning, behavioral economics, and disaster governance, the review provides a unique synthesis relevant for academics, urban planners, and policymakers seeking to design equitable and resilient urban futures. The five-cluster thematic taxonomy introduced in this review represents an original synthesis that bridges engineering vulnerability assessment, behavioral economics, heritage preservation, and resilience governance. Unlike previous reviews that have typically focused on single disciplinary perspectives, this taxonomy integrates multi-scalar approaches spanning asset-level diagnostics to national exposure modeling, providing a comprehensive framework for understanding real estate exposure to seismic and subsurface risks. Full article

Recent developments in cognitive neuroscience, neuroimaging, and embodied cognition have stimulated growing interest in neuroscience-informed architecture. However, despite the rapid expansion of the field, neuroarchitectural scholarship remains conceptually fragmented and methodologically diverse, and its institutional evolution, thematic structure, and translational implications have not been comprehensively synthesised. Using a narrative critical synthesis supported by translational qualitative structuring and conceptual synthesis, this study examines foundational publications, institutional documents, conference outputs, and applied studies that have shaped neuroscience-informed architecture since the early 2000s. The review identifies recurring thematic domains, including sensory perception, spatial cognition, emotion, empathy, embodied cognition, environmental behaviour, healthcare design, and evidence-based architectural practice. It indicates that ANFA-related scholarship has played a significant role in legitimising neuroscience as a relevant framework for understanding architectural experience and informing design practices in therapeutic, educational, and behavioural contexts. The review also highlights persistent methodological challenges in translating neuroscientific findings into architectural research, particularly given that architectural experience is multisensory, embodied, socially situated, and temporally dynamic. The study concludes that neuroscience-informed architecture should be understood not as a deterministic explanatory model but as a translational framework that connects neuroscientific knowledge with architectural theory and practice. This expanding evidence base calls for more ecologically valid, interdisciplinary, and methodologically rigorous research, while encouraging architects and practitioners to adopt evidence-based, human-centred design strategies that enhance health, well-being, and user experience across diverse built environments. Full article

Assessment feedback on complex written reports remains one of the most persistent and resource-intensive challenges in higher education. However, no principled framework exists for deciding which feedback tasks might appropriately involve artificial intelligence and which must remain human responsibilities. This paper addresses that gap by proposing a tripartite feedback framework that distinguishes three analytically distinct levels: low-level structural and presentational feedback, intermediate-level factual content validation, and high-level critical evaluation and synthesis. Grounded in established feedback theory, including Hattie and Timperley’s feedback model and Boud and Molloy’s sustainable feedback design principles, the framework provides pedagogically justified criteria for allocating tasks between AI systems and human assessors, rather than automating whatever technology can technically perform. Five non-negotiable boundary principles govern any AI involvement at the intermediate level, preserving human oversight, academic accountability, and assessment integrity. This paper examines current technological capabilities and limitations at each level, proposes a phased implementation pathway with explicit human-in-the-loop requirements, and addresses implications for feedback literacy, student agency, equity, and security. A comprehensive mixed-methods evaluation design specifying the evidence required for empirical validation is also presented. The framework’s contribution lies not in prescriptive solutions but in providing structured categories, explicit boundary conditions, and validation criteria to guide context-sensitive institutional decision-making about AI integration in assessment. Full article

This paper explores the role of media literacy in enhancing the educational potential of commercial off-the-shelf (COTS) video games, particularly in the context of cultural heritage education within technology-enhanced learning environments. Rather than presenting new empirical data, the study draws on existing media literacy, game studies, and cultural heritage scholarship to propose a comprehensive media literacy framework that addresses the needs and competencies of five key stakeholders: (1) players; (2) game developers; (3) educators and researchers; (4) represented communities; and (5) cultural institutions. Video game spaces are mainly designed to create entertaining products, but even COTS games have potential educational and cultural features, such as the promotion of real-life locations and tangible and intangible heritage. This paper argues that fostering media literacy among developers and players can not only support the creation of more culturally aware game worlds but also strengthen the educational use of games within technology-enhanced learning environments. In synthesising and reconfiguring existing theoretical models, the framework offers new insight into the relationship between media literacy and cultural heritage in games, and identifies directions for future empirical research. Full article

Based on survey data from 579 farmer households in major non-timber forest product (NTFP) regions of Zhejiang Province, this study comprehensively employs binary logit/ordered probit and machine learning methods for cross-validation. It systematically examines the effects of multiple factors, including perceived property rights security, technical training, village rules and regulations, ecological awareness, and economic incentives, on forest farmers’ adoption of green production technologies. The cross-validation between econometric and machine learning approaches enhances the reliability of the findings. Results show that perceived property rights security is robustly and positively associated with green production behavior, while village rules and regulations and ecological awareness emerge as the two most critical driving factors. These associations exhibit significant NTFP-type heterogeneity: the impacts of technical training and forestry subsidies vary in direction depending on the crop cultivated, rendering traditional one-size-fits-all policies ineffective. This study highlights the crucial role of informal institutions and environmental awareness in the green transition, offering empirical evidence for designing differentiated training programs, optimizing penalty gradients, and implementing targeted subsidy policies. Full article

The COVID-19 pandemic affected maternal mental health in the UK, increasing postpartum emotional distress. This scoping review identified forms of postpartum emotional distress (PPED) examined during the pandemic, the methodologies and assessment tools used, analytical approaches, reported limitations, future research directions, and overall findings. This review followed Arksey and O’Malley’s framework and the Joanna Briggs Institute scoping review guidelines. A comprehensive, keyword-based search strategy was applied across electronic databases, initially on 28 January 2023, and updated on 20 July 2023, and 3 September 2025. Strict inclusion criteria were used, and data from eligible studies were charted and synthesised. This review of 35 UK studies on postpartum emotional distress (PPED) during COVID-19 found a dominant focus on depression and anxiety, with other PPED forms largely neglected. Quantitative designs overwhelmingly outnumbered qualitative and mixed-method approaches. Common limitations included low sample diversity, reliance on online self-report surveys, cross-sectional designs, convenience sampling, and social-media-based recruitment. This review is the first to map research approaches used to explore postpartum emotional distress (PPED) during COVID-19 in the UK. The limitations and future research directions identified in this review highlight an urgent need for more diverse sampling, longitudinal study designs, qualitative research exploring women’s lived experience narratives of different forms of postpartum emotional distress, greater consideration of biopsychosocial factors, and evidence-based interventions. Full article

Introduction: This study explores obstetric providers’ perceptions of intimate partner violence (IPV) screening in the Chinese clinical setting, guided by the social–ecological model. Methods: Purposive sampling was employed to recruit eight obstetricians and 12 obstetric nurses from a tertiary general hospital in Suzhou, Jiangsu Province, China. Individual semi-structured interviews were conducted between December 2024 and September 2025. Results: Guided by the social–ecological model, this study examines factors influencing healthcare professionals’ engagement in intimate partner violence screening across four levels. A multilevel framework was distilled; four key themes were identified, including the intrapersonal level, interpersonal level, institutional level and community and policy level. (1) The intrapersonal level—healthcare professionals’ competence (knowledge base, communication skills, role identity, screening attitudes, and diagnostic ability); (2) the interpersonal level—interdisciplinary collaboration (internal referrals and external support); (3) the institutional level—hospital screening efficacy (screening resources and management systems); and (4) the community and policy level—social environment (policy support, educational resources, and cultural context). Conclusions: Multilevel factors impact IPV screening in China. These results indicate that a multidimensional model of intervention should be designed to promote IPV screening in China, including integrating IPV curricula into mandatory medical student training, enhancing interdisciplinary collaboration, conducting public education on IPV, implementing socio-cultural adjustments, challenging authoritative attitudes, and providing comprehensive social support. Full article

Smart cities have emerged as a strategic approach to enhancing urban sustainability through the integration of digital technologies, intelligent infrastructure, and data-driven governance. However, limited research has comprehensively examined how technological, institutional, governance, and contextual factors interact to influence sustainability outcomes in industrial-city settings, particularly in Saudi Arabia. This study develops an integrated conceptual framework for sustainable smart industrial cities through a qualitative research design based on a systematic screening and synthesis of the literature, complemented by a contextual analysis of the Dammam Metropolitan Area (DMA) as an illustrative urban-industrial case under Saudi Vision 2030. A total of 86 articles, reports, and website materials were identified and screened, of which 49 sources met the inclusion criteria and were synthesized to develop the proposed framework. The analysis examined five interrelated components: smart-city applications, institutional governance, implementation conditions, contextual barriers and opportunities, and sustainability outcomes across three dimensions: environmental, social, and economic. The findings suggest that the effectiveness of smart-city applications depends not only on technological innovation but also on institutional governance, digital readiness, stakeholder participation, integrated planning, and supportive regulatory environments. The study further identifies fragmented governance, limited institutional coordination, cybersecurity risks, and high infrastructure costs as key implementation barriers, while highlighting opportunities associated with Saudi Vision 2030, digital-transformation initiatives, and circular-economy principles. The principal contribution of the study is the development of an integrated conceptual framework that explains the interactions among these five components and provides a theoretical foundation for future empirical validation, as well as conceptually informed guidance for policy development and planning in Saudi Arabia and comparable industrial-city contexts. Full article

With the accelerating global population aging process, home health care (HHC) has emerged as a promising service mode to satisfy surging elderly medical care needs and alleviate the pressure of offline medical institutions. As a core operational optimization problem in the HHC service system, the home health care routing and scheduling problem (HHCRSP) has attracted extensive research attention in recent years. Different from traditional HHCRSP research, this work proposes a bi-objective mixed-integer programming model for HHC, which integrates facility location, caregiver allocation, route planning and skill-matching rules. The model simultaneously minimizes two competing objectives: total operational cost and total penalty incurred from time window violations. To tackle the high-complexity NP-hard characteristics of this integrated optimization problem, an enhanced non-dominated sorting genetic algorithm (E-NSGA) is designed by introducing dedicated local search operators to improve solution quality. Comparative numerical experiments are carried out on 12 test instances extended from the classic Vidal benchmark, covering four patient scales of 70, 80, 90 and 100 patients. Four state-of-the-art multi-objective metaheuristics, i.e., MOEA/D, MOGWO, NSGA-II and NSGAII-MLS, are selected as baseline comparison algorithms. Experimental results reveal prominent performance advantages of E-NSGA over all comparison methods. In terms of the IGD metric, E-NSGA achieves IGD reductions of 20.19%, 86.30%, 24.98% and 37.72% against MOEA/D, MOGWO, NSGA-II and NSGAII-MLS, respectively. In terms of the Hypervolume metric, E-NSGA obtains performance improvements of 6.22%, 2019.42%, 10.36% and 18.04% relative to the four baseline algorithms. Such quantitative evidence verifies the strong comprehensive optimization capacity of the proposed E-NSGA for addressing the investigated problem. Full article