Search Results (10,224)

Vascular diseases remain a major global health burden despite remarkable technological advances in vascular surgery and endovascular therapies. Conditions such as peripheral arterial disease, abdominal aortic aneurysm, carotid stenosis, chronic venous disease, diabetic vasculopathies, and vascular chronic ulcers are not only biological entities but are deeply shaped by social structures, cultural norms, and economic inequalities. This article introduces Vascular Sociology as an interdisciplinary field that integrates vascular surgery with medical sociology to provide a more comprehensive understanding of vascular health and disease. Drawing on classical and contemporary sociological theory, including concepts such as social determinants of health, embodiment, illness narratives, and the disease–illness–sickness triad, the article argues that vascular pathology reflects cumulative social exposures across the life course. Socially patterned behaviors, work conditions, food environments, healthcare access, gender norms, and geographic inequalities profoundly influence disease onset, progression, treatment decisions, and outcomes. The paper highlights how surgical success is contingent not only on technical excellence but also on patients’ social contexts, including health literacy, trust in institutions, caregiving resources, and the capacity to adhere to long-term follow-up and rehabilitation. By outlining conceptual foundations, epidemiological evidence, and mixed-methods research strategies, the article positions Vascular Sociology as a framework capable of bridging biomedical knowledge with lived experience. This approach expands the definition of vascular outcomes to include social reintegration, identity transformation, and equity of care, ultimately aiming to improve patient-centered practice, reduce disparities, and inform more socially responsive vascular health policies. Full article

Food insecurity is not merely an outcome of individual deprivation but a place-based expression of how urban food systems operate within unequal socio-spatial contexts. Using the Drivers–Pressures–State–Impacts–Responses (DPSIR) framework as a policy-relevant analytical lens, this study examines the Metropolitan Region of Rome to show how structural inequalities and uneven food infrastructures shape exposure to food-related risks. The results show that vulnerability is amplified by food price inflation, the rising cost of a healthy diet, and spatial gaps in retail provision—captured through the combined presence of food deserts and food blackouts—disproportionately affecting peripheral municipalities. State indicators, including the Food Insecurity Experience Scale (FIES), the Food Affordability Index (FAI), and the spatial distribution of FEAD beneficiaries, reveal a markedly uneven geography of food poverty, mirroring a higher prevalence of overweight, obesity, and diabetes. These spatial configurations point to obesogenic environments in which constrained affordability and limited accessibility restrict the capacity to maintain healthy diets, generating hidden social and health costs that disproportionately burden peripheral areas. Overall, food insecurity in Rome follows a pronounced centre–periphery gradient rooted in structural and institutional arrangements rather than incidental variation. Addressing this condition requires place-based, justice-oriented interventions that strengthen food infrastructures, improve coordination across governance scales, and place food security at the core of an integrated metropolitan Food Policy. Full article

Heavy metal pollution in forest and agroforestry soils represents a persistent environmental challenge with direct implications for ecosystem functioning, food security, and human health. In tropical and subtropical regions, intense weathering, rapid organic matter turnover, and dynamic redox conditions strongly modulate metal mobility, bioavailability, and long-term soil vulnerability. This review synthesizes current knowledge on the sources, biogeochemical mechanisms, ecological impacts, monitoring approaches, and restoration strategies associated with heavy metal contamination in forest and agroforestry systems, with particular emphasis on tropical landscapes. We examine natural and anthropogenic metal inputs, highlighting how atmospheric deposition, legacy contamination, land-use practices, and soil management interact with mineralogy, organic matter, and hydrology to control metal fate. Key processes governing metal behavior include sorption and complexation, Fe–Mn redox cycling, pH-dependent solubility, microbial mediation, and rhizosphere dynamics. The ecological consequences of contamination are discussed in terms of soil health degradation, plant physiological stress, disruption of ecosystem services, and risks of metal transfer to food chains in managed systems. The review also evaluates integrated monitoring frameworks that combine field-based soil analyses, biomonitoring, and geospatial technologies, while acknowledging methodological limitations and scale-dependent uncertainties. Finally, restoration and remediation strategies—ranging from phytotechnologies and soil amendments to engineered Technosols—are assessed in relation to their effectiveness, scalability, and relevance for long-term functional recovery. By linking mechanistic understanding with management and policy considerations, this review provides a process-oriented framework to support sustainable management and restoration of contaminated forest and agroforestry soils in tropical and subtropical regions. Full article

Urban air pollution remains a critical public health issue, especially in densely populated cities where pedestrians experience direct exposure to traffic-related and environmental emissions. This study develops and tests a pollution-aware pedestrian routing framework for Thessaloniki, Greece, designed to minimize environmental exposure while maintaining route efficiency. The framework combines high-resolution air-quality data and computational techniques to represent pollution patterns at pedestrian scale. Air-quality is expressed as a continuous European Air Quality Index (EAQI) and is embedded in a network-based routing engine (OSRM) that balances exposure and distance through a weighted optimization function. Using 3000 randomly sampled origin-destination pairs, exposure-aware routes are compared with conventional shortest-distance paths across short, medium, and long walking trips. Results show that exposure-aware routes reduce cumulative AQI exposure by an average of 4% with only 3% distance increase, while maintaining stable scaling across all route classes. Exposure benefits exceeding 5% are observed for approximately 8% of medium-length routes and 24% of long routes, while short routes present minimal or no detours, but lower exposure benefits. These findings confirm that integrating high-resolution environmental data into pedestrian navigation systems is both feasible and operationally effective, providing a practical foundation for future real-time, pollution-aware mobility services in smart cities. Full article

Children and adolescents in hot and humid climates face increasing health risks due to climate change. Although the concept of Health-Promoting Schools (HPSs) is widely recognized, a systematic framework that integrates climate adaptability, child-specific needs, and multidimensional environmental design is still lacking. To address this gap, this study conducted a systematic literature review of 89 publications with three objectives: (1) synthesize research from the past decade on the impact of school physical environments on the health and academic performance of children and adolescents; (2) develop an evidence-based synergistic design framework with a categorized indicator system; and (3) integrate qualitative and quantitative evidence on how these indicators influence different health dimensions. The resulting framework emphasizes multidimensional, synergistic optimization and provides climate-responsive design strategies tailored to educational settings in hot and humid regions. By offering a theory-to-practice pathway, the framework complements existing healthy building guidelines for K–12 schools and supports designers and policymakers in creating environments that enhance thermal resilience, cognitive performance, and holistic child development. Full article

The dynamic characteristics of bridges are not only influenced by structural damage but also by ambient environmental variations. If environmental factors are not incorporated into the detection algorithm, they may lead to false positives or false negatives. In recent years, vibration-based damage detection methods have gained significant attention in structural health monitoring (SHM), particularly for assessing structural integrity under varying temperature conditions. This study introduces a deep-learning framework for identifying damage in composite bridges by utilizing both time-domain and frequency-domain vibration signals while explicitly accounting for temperature effects. Two deep learning models—Convolutional Neural Network (CNN) and Artificial Neural Network (ANN)—were implemented and compared. The effectiveness of the proposed damage identification approach was evaluated using an experimental dataset obtained from a composite bridge structure. Furthermore, statistical evaluation metrics—including accuracy, precision, recall, F1 score, and the ROC curve—were used to compare the damage detection performance of the two deep learning models. The results reveal that the CNN model consistently outperforms the ANN in terms of classification accuracy. Moreover, frequency-domain analysis was shown to be more effective than time-domain analysis for damage classification, and integrating temperature data with vibration signals improved the performance of all model architectures. Full article

Background/Objectives: Across geographical and cultural contexts, how individuals identify, communicate and help-seek for distress is often shaped by how mental health itself is understood. Insight into how adolescents and adults in their routine environment, such as teachers, understand mental health is crucial for developing context-specific mental health promotion strategies to young people. Sri Lanka, a country that navigates the dual legacies of pre-and-post-colonial mental health frameworks, has this need. The aim was to explore Sri Lankan school-going adolescents’ and their teachers’ perspectives of mental health and its determinants. Methods: Semi-structured interviews were conducted with 28 school-going adolescents in grades 10–12/13 and 14 of their school teachers, from seven secondary schools in Gampaha District, Sri Lanka. Interviews were transcribed, translated, coded inductively and analysed thematically. Results: All participants drew on culturally meaningful language that is rooted in Buddhist perspectives to conceptualise mental health. Causes and risk factors of poor mental health were attributed to individual, immediate environmental and structural factors. School environment played a central role in exacerbating other risk factors. Adolescents exhibited more knowledge of informal care avenues for mental health-related concerns. Conclusions: Findings highlight several implications including opportunities to leverage culturally contextualised language/frameworks when promoting mental health to Sri Lankan adolescents, diversifying mental health research and initiating school-based mental health programmes that integrate mental health promotion into routine educational practice to transform learning institutions across Sri Lanka to become mental health-promoting schools. Full article

Background: Intimate partner violence (IPV) represents a major public health problem in Europe, with significant physical, psychological, and social consequences. Nurses are often the first professionals capable of detecting early signs of IPV, yet they lack validated instruments to assess their clinical competency in detection, evaluation, documentation, and intervention. This study aimed to develop and validate the Intimate Partner Violence Nursing Competency Scale (IPVNCS), aligned with the Nursing Intervention Classification (NIC 6403). Methods: A cross-sectional psychometric study was conducted among registered nurses in the Community of Madrid. A 30-item Likert-type self-administered instrument (1–5 scale) was developed based on NANDA, NIC 6403, and NOC frameworks. A total of 202 nurses participated. Reliability was assessed through Cronbach’s alpha. Construct validity was examined using exploratory factor analysis (EFA) with Promax rotation and confirmatory factor analysis (CFA) using AMOS 26. Ethical approval was obtained (CEU San Pablo, code 843/24/104). Results: After item refinement, 26 items remained across four dimensions: (1) Intervention and Referral, (2) Detection and Assessment, (3) Documentation and Recording-keeping, (4) Psychosocial Support. The instrument showed excellent reliability ($\alpha$ = 0.97). KMO was 0.947 and Bartlett’s test was significant (p < 0.001). CFA demonstrated satisfactory fit: ${\chi }^2$/df = 2.066, RMSEA = 0.073, CFI = 0.92, TLI = 0.91, NFI = 0.86. The final model adequately represented the latent structure. After debugging, its psychometric properties were significantly improved. Four redundant items were eliminated, achieving internal consistency ($\alpha$ = 0.97), a KMO value of 0.947 and a significant Bartlett’s test of sphericity. It showed a better fit, according to ${\chi }^2$/df = (2.066); Parsimony = (720.736); RMR (0.0529; RMSEA (0.073); NFI (0.860); TLI (0.910) and CFI (0.920). The final model provides an adequate representation of the latent structure of the data. This study provides initial evidence of construct validity and internal consistency reliability of the IPVNCS. Conclusions: The IPVNCS is a valid and reliable tool to assess nursing competencies for clinical management of IPV. It supports structured evaluation across four core nursing domains, enabling improved educational planning, clinical decision-making, and quality of care for victims. The scale fills a gap in clinical nursing assessment tools and can support protocol development in emergency, primary care, and hospital settings. Full article

Pharmacy-based point-of-care (POC) services have evolved from pilot initiatives to an essential component of decentralized healthcare delivery. These services—ranging from rapid infectious-disease screening to chronic-disease monitoring—improve access, reduce diagnostic delays and empower pharmacists as front-line healthcare providers. The present paper is an updated, in-depth review of the evolution of pharmacy POC services worldwide, combined with the analysis of the regulatory and educational frameworks supporting implementation, technological drivers such as biosensors, mobile health and artificial intelligence and in-depth socioeconomic considerations. Benefits for patients, pharmacies and healthcare systems are contrasted with challenges including variable reimbursement, uneven regulatory oversight and workforce preparedness. Full article

The number of older women imprisoned is increasing around the world, leading to an increased demand on health and social care services within prisons. Imprisoned women are considered older by age 50 as they experience a disproportionate burden of cancer and disease. Access to prison cancer screening programmes in prison should mirror access in the community; however, this is not always the case. The purpose of this scoping review is to systematically review the literature relating to enablers and barriers of cancer screening programmes in imprisoned older women. We performed a scoping review using the Arksey and O’Malley framework. Twelve studies were identified. Locations of studies varied across high-income countries. Enablers and barriers were identified within operational, personal, and accessibility categories. To improve mortality relating to cancer diagnosis it is vital that older imprisoned women are supported to access cancer screening. It was identified that older imprisoned women have different needs to other prison populations, and the barriers and enablers identified relate to staffing, communication, peer support, and processes to improve the experience of the older prison population. There is limited research in this area, and older women are a minority in a marginalized prison population. More research is needed to ensure the appropriate and effective development of cancer screening services. Full article

Background and Objectives: Immunosenescence is a complex biological process associated with aging, characterized by a progressive decline in immune function and increased chronic inflammation (“inflammaging”), with clinical implications such as frailty, functional decline, multimorbidity, and a higher risk of adverse events in older adults. Nurses in community and primary care settings play a central role in preventive and health promotion interventions that may indirectly influence these processes. However, the available literature remains fragmented. Therefore, this scoping review aims to map and synthesise nursing interventions targeting older adults (≥60 years) that may indirectly influence immunosenescence by acting on its clinical correlates and modifiable determinants, organising the evidence within a four-pillar conceptual framework. Materials and Methods: A scoping review was conducted following JBI methodology and the PRISMA-ScR checklist. We included primary studies on nurse-led interventions in community, home care, primary care, territorial, or long-term care settings. PubMed, Scopus, and Web of Science were searched (English; last 10 years). Interventions were classified into four pillars: nursing nutrition and immunonutrition support, physical activity and exercise support, nursing vaccination coaching, and frailty monitoring and prevention of functional decline. Results: Twenty-five primary studies were included, mostly randomised or cluster-randomised trials in community, primary care, home care, and transitional care settings. Interventions mapped mainly to Pillar 4 and Pillar 2, while Pillar 1 was less frequent and usually part of multicomponent programmes; no primary studies targeted Pillar 3. Overall, effectiveness appeared driven more by intervention intensity and integration than by frailty identification alone: structured, multicomponent nurse-led programmes combining exercise with nutritional and psychosocial components showed the most consistent benefits on frailty, functional outcomes, and well-being, whereas low-intensity preventive consultations and Comprehensive Geriatric Assessment (CGA)-based models often showed limited improvements over usual care. Conclusions: This scoping review highlights the key role of community and primary care nurses in preventive interventions targeting clinical correlates of immunosenescence. Multicomponent nurse-led programmes integrating physical activity, nutrition, and psychosocial support appear most promising for frailty and functional outcomes, while low-intensity interventions show limited effectiveness. No primary studies addressed nurse-led vaccination coaching, representing an evidence gap. Future research should include biological/immunological markers alongside clinical outcomes. Full article

Modern healthcare systems increasingly depend on wearable Internet of Medical Things (IoMT) devices for the continuous monitoring of patients’ physiological parameters. It remains challenging to differentiate between genuine physiological anomalies, sensor faults, and malicious cyber interference. In this work, we propose a hybrid fusion framework designed to attribute the most plausible source of an anomaly, thereby supporting more reliable clinical decisions. The proposed framework is developed and evaluated using two complementary datasets: CICIoMT2024 for modelling security threats and a large-scale intensive care cohort from MIMIC-IV for analysing key vital signs and bedside interventions. The core of the system combines a supervised XGBoost classifier for attack detection with an unsupervised LSTM autoencoder for identifying physiological and technical deviations. To improve clinical realism and avoid artefacts introduced by quantised or placeholder measurements, the physiological module incorporates quality-aware preprocessing and missingness indicators. The fusion decision policy is calibrated under prudent, safety-oriented constraints to limit false escalation. Rather than relying on fixed fusion weights, we train a lightweight fusion classifier that combines complementary evidence from the security and clinical modules, and we select class-specific probability thresholds on a dedicated calibration split. The security module achieves high cross-validated performance, while the clinical model captures abnormal physiological patterns at scale, including deviations consistent with both acute deterioration and data-quality faults. Explainability is provided through SHAP analysis for the security module and reconstruction-error attribution for physiological anomalies. The integrated fusion framework achieves a final accuracy of 99.76% under prudent calibration and a Matthews Correlation Coefficient (MCC) of 0.995, with an average end-to-end inference latency of 84.69 ms (p95 upper bound of 107.30 ms), supporting near real-time execution in edge-oriented settings. While performance is strong, clinical severity labels are operationalised through rule-based proxies, and cross-domain fusion relies on harmonised alignment assumptions. These aspects should be further evaluated using realistic fault traces and prospective IoMT data. Despite these limitations, the proposed framework offers a practical and explainable approach for IoMT-based patient monitoring. Full article

Background/Objectives: Institutional catering serves vulnerable populations, including schoolchildren. Surfaces in food preparation environments are key control points for food safety and reservoirs and transmission routes for antimicrobial-resistant (AMR) bacteria. This study characterized the hygienic status of food-contact surfaces (FCS) and non-food-contact surfaces (NFCS) in Hungarian school kitchens, identified contamination hotspots, and examined how routine monitoring can support AMR prevention. Methods: We retrospectively analyzed routine environmental hygiene monitoring records from 96 school kitchens (2019–2024). In total, 8412 swab samples were collected, 8407 had quantifiable counts, 6233 from FCS (e.g., plates, trays, boards, utensils), and 2174 from NFCS (e.g., sinks, fridges, workers’ hands). Total aerobic mesophilic counts were measured with a redox-potential method and expressed as CFU/100 cm²; 250 CFU/100 cm² (2.4 log₁₀) was the hygienic threshold. Results: Overall, 12.4% of surfaces exceeded the threshold. Non-food-contact surfaces were more likely to be non-compliant than food-contact surfaces (OR 2.77, 95% CI 2.43–3.17; p < 0.001). Hotspots included transport-container lids (67.2% non-compliant; OR 43.82), sink basins (32.8%; OR 10.46), and cutting boards (21.6%; OR 5.89). Seasonally, non-compliance was highest in summer (16.5%) and lowest in winter (9.0%; p < 0.001). Conclusions: Multi-year monitoring revealed substantial contamination concentrated in a few hotspots that, within a One Health framework—which recognizes the interconnectedness of human, animal, and environmental health—may represent environmental reservoirs and cross-contamination nodes relevant to AMR prevention. Targeted optimization of cleaning and disinfection for these surfaces, combined with trend analysis of indicator data and periodic AMR-focused environmental sampling, could reduce foodborne and AMR-related risks in public catering. Full article

Background/Objectives: Federated learning (FL) offers a way for healthcare institutions to collaboratively train machine learning models without sharing sensitive patient data. This systematic review aims to comprehensively synthesize the ethical dimensions of FL in healthcare, integrating privacy preservation, algorithmic fairness, governance, and equitable access into a unified analytical framework. The application of FL in healthcare between January 2020 and December 2024 is examined, with a focus on ethical issues such as algorithmic fairness, privacy preservation, governance, and equitable access. Methods: Following PRISMA guidelines, six databases (PubMed, IEEE Xplore, Web of Science, Scopus, ACM Digital Library, and arXiv) were searched. The PROSPERO registration is CRD420251274110. Studies were selected if they described FL implementations in healthcare settings and explicitly discussed ethical considerations. Key data extracted included FL architectures, privacy-preserving mechanisms, such as differential privacy, secure multiparty computation, and encryption, as well as fairness metrics, governance models, and clinical application domains. Results: Out of 3047 records, 38 met the inclusion criteria. The most popular applications were found in medical imaging and electronic health records, especially in radiology and oncology. Through thematic analysis, four key ethical themes emerged: algorithmic fairness, which addresses differences between clients and attributes; privacy protection through formal guarantees and cryptographic techniques; governance models, which emphasize accountability, transparency, and stakeholder engagement; and equitable distribution of computing resources for institutions with limited resources. Considerable variation was observed in how fairness and privacy trade-offs were evaluated, and only a few studies reported real-world clinical deployment. Conclusions: FL has significant potential to promote ethical AI in healthcare, but advancement will require the development of common fairness standards, workable governance plans, and systems to guarantee fair benefit sharing. Future studies should develop standardized fairness metrics, implement multi-stakeholder governance frameworks, and prioritize real-world clinical validation beyond proof-of-concept implementations. Full article

Background: Large language models (LLMs) are becoming progressively integrated into clinical practice; however, their role in cardiovascular (CV) prevention remains unclear. This review synthesizes current evidence on LLM applications in preventive cardiology and proposes a governance framework for their safe translation into practice. Methods: We conducted a comprehensive narrative review of literature published between January 2015 and November 2025. Evidence was synthesized across three functional domains: (1) patient applications for health literacy and behavior change; (2) clinician applications for decision support and workflow efficiency; and (3) system applications for automated data extraction, registry construction, and quality surveillance. Results: Evidence suggests that while LLMs generate empathetic, guideline-concordant patient education, they lack the nuance required for unsupervised, personalized advice. For clinicians, LLMs effectively summarize clinical notes and draft documentation but remain unreliable for deterministic risk calculations and autonomous decision-making. System-facing applications demonstrate potential for automated phenotyping and multimodal risk prediction. However, safe deployment is constrained by hallucinations, temporal obsolescence, automation bias, and data privacy concerns. Conclusions: LLMs could help mitigate structural barriers in CV prevention but should presently be deployed only as supervised “reasoning engines” that augment, rather than replace, clinician judgment. To guide the transition from in silico performance to bedside practice, we propose the C.A.R.D.I.O. framework (Clinical validation, Auditability, Risk stratification, Data privacy, Integration, and Ongoing vigilance) as a roadmap for responsible integration. Full article