Search Results (2,673)

Background/Objectives: Cerebral palsy (CP) hip displacement requires longitudinal surveillance, frequently imposing significant burden on caregivers. While Multimodal Large Language Models (MLLMs) offer a potential solution to the health literacy gap, their accuracy in interpreting pediatric pelvic radiographs remains unproven. This study evaluates the effectiveness and safety of MLLMs in addressing caregiver concerns regarding CP hip management. Methods: Fifteen deidentified pediatric pelvic radiographs representing a spectrum of hip displacement severities were processed through three MLLMs: GPT-4o, Claude 3.5, and Gemini 1.5 Pro. Nine standardized caregiver prompts (n = 95 total responses per model) were utilized to simulate common clinical queries. Outcome measures included response word count, interactive characteristics, frequency of medical disclaimers, and diagnostic accuracy. Results: Quantitative analysis revealed that Claude 3.5 produced significantly shorter responses compared to other models (p < 0.01). GPT-4o demonstrated the highest safety alignment, with a 96.9% disclaimer rate, significantly exceeding Claude (60.0%) and Gemini (76.8%) (p = 0.03). Diagnostic “hallucinations” were observed, notably Claude misidentifying non-operative cases as bilateral hip replacements. While management recommendations were clinically relevant, they remained generic rather than patient-specific, failing to measure or apply migration percentage thresholds. Encouragingly, all models consistently directed users to consult an orthopaedic surgeon. Conclusions: MLLMs represent an opportunity to enhance health literacy by providing accessible management summaries and emphasizing professional consultation. However, significant radiographic hallucinations and a lack of specific, evidence-based guidance preclude their use as standalone diagnostic tools. Currently, MLLMs should be viewed as educational adjuncts requiring expert oversight in the pediatric orthopaedic care continuum. Full article

Changes in human attention, workload, or alertness over time can affect task performance and may even increase the risk of injury. Detecting these changes in real time can be beneficial in improving system performance and safety. We reviewed 27 studies that developed models to sense physiological signals, classify one’s cognitive state, and deliver automated intervention. Interventions included providing real-time feedback, adjusting the task’s difficulty, or modifying automation levels across driving, education, rehabilitation, and human–robot collaboration applications. The findings showed that electroencephalography (EEG) sensors were used in 70% of studies, with attention (56%) and mental workload (26%) considered as the most targeted cognitive states. Within-subject classification reached 81.85–95.81% for multi-class tasks in laboratory settings. The most common interventions included neurofeedback display (30%) and task difficulty adjustment (19%), while automation adjustment was less frequent (11%). Only 33% of studies mentioned a latency of 15 milliseconds to 2.5 s, and all systems operated reactively by detecting cognitive states after their onset rather than anticipating them. The provided recommendations focus on the detection of multiple interacting cognitive states and predictive cognitive state trajectories. This review presents key directions for future research and provides a foundation for designing more effective cognitive state adaptive systems. Full article

Upper respiratory tract infections and inflammatory nasal disorders are highly prevalent in childhood and represent a major cause of morbidity and healthcare utilization. Humans are continuously exposed to airborne microorganisms, allergens, and pollutants. Although the nasal mucosa provides effective mechanical and immunological defenses, these mechanisms may be impaired by inflammation, environmental pollutants, and mucociliary dysfunction, increasing susceptibility to infection and airway inflammation. Nasal irrigation (NI) contributes to the restoration of nasal homeostasis by mechanically removing mucus, pathogens, allergens, and inflammatory mediators, while also improving mucociliary clearance (MC), mucus rheology, and epithelial barrier function. Hypertonic solutions (HS) may provide additional osmotic and decongestant effects. Current evidence suggests that NI is a safe and well-tolerated adjunctive intervention that may improve symptoms and support mucosal function in acute and chronic upper airway diseases. This narrative review provides an updated overview of NI, with particular focus on pediatric populations. This paper integrates the pathophysiological mechanisms of mucociliary dysfunction, environmental exposures, and pediatric-specific anatomical and functional characteristics into a unified framework to understand the role of NI in childhood respiratory diseases. Clinical indications, administration techniques, solution selection, safety aspects, and age-specific practical considerations are discussed, highlighting the importance of appropriate technique, caregiver education, and adherence to basic hygiene principles. Full article

Background: Medication errors remain a major threat to patient safety in acute care settings worldwide and are associated with preventable morbidity, mortality, and increased healthcare costs. Nurses play a critical role in identifying, intercepting, and preventing medication-related harm. However, limited qualitative evidence has explored nurses’ perspectives on medication safety within the Saudi Arabian healthcare context. This study explored nurses’ experiences of medication safety, perceived systemic challenges, and strategies for error prevention in Saudi hospitals. Methods: A qualitative descriptive design was employed. Fourteen (n = 14) nurses from two major referral hospitals in Saudi Arabia participated in semi-structured face-to-face interviews. Interviews were audio-recorded, transcribed verbatim, and analyzed using Braun and Clarke’s six-phase thematic analysis framework. Results: Five overarching themes were identified: (1) Communication gaps; (2) Medication processes; (3) Technology and safety; (4) Workload and staffing; and (5) Staff competence. Participants described how communication failures, staffing pressures, workflow interruptions, and documentation ambiguities compromised medication safety. While barcode systems and EHRs were perceived as valuable safeguards, participants emphasized that their effectiveness depended on staff vigilance, adequate training, and supportive workplace cultures. Conclusions: Medication safety is a dynamic socio-technical process shaped by communication, competence, staffing capacity, and human interaction with technology. Improving safety requires integrated organizational strategies that combine workforce investment, structured communication practices, continuous professional education, and non-punitive incident reporting cultures. These findings provide practical insights for healthcare leaders seeking to strengthen medication safety systems in Saudi Arabia and comparable settings. Full article

Background/Objectives: Artificial Intelligence (AI) integration in healthcare promises improved diagnostic accuracy, patient safety, and operational efficiency. However, AI acceptance among healthcare workers remains limited due to knowledge gaps, risk concerns, and governance challenges, particularly in developing countries like Saudi Arabia, where rapid healthcare modernization faces unique infrastructure, organizational, and cultural challenges. This research investigates the factors influencing AI acceptance among medical practitioners, nurses, administrators, and students in Saudi Arabian hospitals to identify key determinants and barriers to adoption. Methods: This cross-sectional study employed an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework integrated with ethical considerations from the Model for Ethical Assessment and Analysis of AI in Medicine (MEAAM). A structured bilingual questionnaire was administered to 119 healthcare professionals and students across Saudi Arabia, measuring constructs including Awareness and Knowledge, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Social Influence, Trust, Perceived Risk, Ethical Governance, and Price Value. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for quantitative analysis, supplemented by thematic analysis of open-ended qualitative responses. Results: The PLS-SEM analysis explained 59.8% of variance in behavioral intention to adopt AI (R² = 0.598). Awareness and Knowledge emerged as the strongest predictor (β = +0.505, p < 0.001), followed by Performance Expectancy (β = +0.229, p < 0.05) and Social Influence (β = +0.123). Perceived Risk functioned as the primary barrier (β = −0.185, p < 0.05). Qualitative findings identified infrastructure gaps, regulatory ambiguities, and training deficiencies as major implementation barriers, while emphasizing opportunities in diagnostic accuracy and remote monitoring. Conclusions: AI acceptance in Saudi healthcare is primarily driven by knowledge, with perceived usefulness and peer support as secondary facilitators, while safety and accountability concerns remain substantial obstacles. Successful AI integration requires coordinated efforts in education, transparent governance frameworks, and institutional support. This study contributes theoretically by validating extended UTAUT in a non-Western healthcare context and practically by providing evidence-based strategies for sustainable AI adoption that enhance healthcare quality while respecting professional roles and ethical principles. Full article

Background: Falls among older adults are a major public health concern associated with injury, disability, reduced mobility, and loss of independence. Functional impairment, chronic diseases, and unsafe home environments may increase the risk of falls. This study examined environmental, functional, and health-related factors linked to falls among community-dwelling older adults in Iran. Methods: A comparative cross-sectional study was conducted among 329 community-dwelling older adults. Data were collected using standardized assessments of functional ability, home safety, health status, and fall history. Conventional regression and Elastic Net analyses were applied to identify significant predictors of falls. Results: Overall, 28.6% of participants reported at least one fall during the previous 12 months. Falls were significantly more common among females, adults aged ≥85 years, individuals without a spouse, and those with lower educational levels. Fallers showed poorer mobility, balance, and functional independence, greater fear of falling, and a higher risk of home accidents (all p < 0.001). Elastic Net analysis identified use of movement aids as the strongest risk factor, whereas better Performance-Oriented Mobility Assessment (POMA) scores were the main protective factor. Conclusions: Falls among community-dwelling older adults appear to result from the interaction of physical, medical, socioeconomic, and environmental factors. These findings highlight the need for multidimensional fall-prevention strategies in primary care settings. Full article

Fire safety in high-rise buildings represents a critical challenge in the United Arab Emirates (UAE), where intensive urbanization, extreme climatic conditions, and multilayered regulatory frameworks impose unique competency demands on architects and Fire Safety Engineering (FSE) consultants. Despite this, no empirically validated competency framework exists that simultaneously addresses both professional groups and is tailored to the specificities of the UAE context. This study aimed to construct and empirically validate such a framework. A three-phase sequential exploratory mixed-method design was employed. In the first phase, a systematic literature review yielded a preliminary set of 69 competency indicators organized within a Knowledge, Skills and Attitudes (KSA) structure. In the second phase, a three-round Delphi technique with an expert panel of 18 specialists validated the set to 62 final indicators. In the third phase, importance–performance analysis (IPA) was conducted on a sample of 250 professionals actively engaged in fire safety projects across four UAE. IPA identified 16 priority competency gaps, most pronounced in digital transformation (BIM, CFD, AI; gap = 1.23), proactive client advisory competencies (gap = 1.21), and regulatory navigation and Civil Defence coordination (gap = 1.00). A counterintuitive finding emerged whereby architects systematically rated competencies higher than FSE consultants across all dimensions (all p < 0.05). Psychometric validation confirmed excellent instrument reliability (Cronbach’s Alpha > 0.95) and a theoretically consistent three-factor KSA structure explaining 70.06% of variance. The developed framework of 62 empirically validated indicators represents the first competency model of its kind for architects and FSE consultants in the Gulf Cooperation Council (GCC) region. Its findings provide a direct empirical basis for curriculum reform, Continuing Professional Development (CPD) programmes, and professional licencing standards in the UAE and across the GCC region. The study makes three original contributions: the first empirically validated UAE-specific competency framework for these professional groups; a methodological combination of Delphi, IPA, EFA, Mann–Whitney, and Kruskal–Wallis not previously applied in fire safety competency research; and empirical confirmation that 74% of indicators required original development or adaptation, demonstrating the limitations of generic international competency models in the UAE context. Full article

This paper presents and validates a unified spreadsheet-based framework for engineering mechanics education and preliminary design. Three modules are integrated within a single openly available workbook: multi-point resultant force and moment computation; axial normal stress with stress concentration effects for three geometric configurations (plate with hole, shoulder plate, stepped shaft); and beam deflection for simply supported and cantilever configurations under point loads. All governing equations are implemented as explicit closed-form expressions validated against analytical reference solutions for six independent cases; relative errors fall below ${10}^{-10}$ in all cases. Three worked exercises demonstrate the practical scope of the framework. A biomechanical multi-point force system yields joint moments of $-6880$, −33,421, and −58,241 N·mm at the wrist, elbow, and shoulder, respectively. A tensile shoulder plate with $K_t\approx 1.85$ produces ${\sigma }_{max}=232$ MPa against ${\sigma }_y=200$ MPa, identifying a design failure; a parametric redesign with fillet radius $r=10$ mm reduces $K_t$ to approximately 1.59 and ${\sigma }_{max}$ to approximately 198.7 MPa, restoring structural safety. A cantilever beam subjected to a 20,000 N tip load yields a maximum deflection of 13,133 μm. The framework constitutes a validated intermediate layer between manual analytical derivations and high-fidelity numerical simulations, applicable to preliminary design, parametric sensitivity studies, and engineering education at the linear elastic level. Full article

Objective: To evaluate the impact of urban–rural health insurance integration on the health outcomes and financial burden of rural older adults. Methods: Utilizing panel data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2013 to 2018, we employed a staggered difference-in-differences model coupled with propensity score matching (PSM-DID) for rigorous causal identification. Results: The policy significantly reduced out-of-pocket medical expenditures for rural households by approximately 5.6% (p = 0.034). Concurrently, significant improvements were observed in both physical health (a 0.092-point reduction in ADL impairment scores) and mental health (a 0.725-point reduction in CES-D depression scores). Mechanism analyses revealed that the integration did not significantly increase the probability of outpatient or inpatient visits—thereby ruling out supplier-induced demand and moral hazard—while effectively reducing the incidence of catastrophic health expenditure by 1.9% (p = 0.004). Heterogeneity analyses indicated that while the financial relief was universally distributed across varying educational levels, the policy dividends were predominantly captured by the younger-old demographic. Notably, the reduction in financial burden was not statistically significant for the oldest-old cohort (aged 75 and older). Conclusions: The urban–rural health insurance integration has achieved a dual dividend of financial protection and health enhancement without triggering the overutilization of medical services. Nevertheless, the unmet care expenses for older adults with severe disabilities underscore the urgent necessity for a secondary safety net, such as long-term care insurance. Full article

Generative large language models (LLMs) are increasingly used to support writing feedback. However, the pedagogical safety and usefulness of LLM feedback for primary students remains under-evaluated. This study reports an educator-centered evaluation of GPT-4 Turbo for Year 5 narrative and persuasive writing in the context of an established online tutoring program. Using authentic students’ drafts paired with tutor feedback, we generated parallel LLM feedback via rubric-aligned prompting and compared the two feedback sources in a blinded, within-script design. Four experienced English specialists co-designed a six-dimensional rubric (clarity, specificity, helpfulness, feasibility, relevance, and overall effectiveness) and rated tutor versus LLM feedback for each script; their written reflections were analyzed thematically to surface boundary conditions and risk perceptions. Across dimensions, tutor feedback received slightly higher mean ratings, with the clearest descriptive advantage in perceived helpfulness; however, none of the differences remained statistically significant after Holm-Bonferroni correction. LLM feedback was often rated similarly for clarity and feasibility but was frequently characterized as generic, surface-focused, and occasionally misaligned with the student draft, which increased verification effort and posed a risk of misleading learners if used without mediation. Synthesizing ratings and educator reflections, we identify conditions under which LLM feedback is most appropriate as rapid first-pass support for routine structure and surface revision, and least appropriate for developmental judgment and context-sensitive guidance. We translate these findings into design requirements for teacher-in-the-loop primary writing feedback systems, including alignment to explicit pedagogical constructs, editable workflows, and safeguards that reduce unsupported feedback before release to students. Full article

Background: Healthcare-associated infections (HAIs) remain a critical patient safety challenge. Hand hygiene is considered the most effective preventive measure, yet traditional monitoring captures only compliance, not technique quality. This prospective before–after study evaluated whether real-time visual feedback via the Semmelweis UV-fluorescence system is associated with improved hand hygiene quality, measured by ATP bioluminescence and microbiological culture. Methods: Three clinical departments (the Intensive Care Unit, Hematology, and Gynecology) at a Romanian tertiary hospital were purposively selected. Seventy-one healthcare workers (HCWs) were enrolled. The 12-week study comprised Phase 1 (baseline, weeks 1–4), Phase 2 (active intervention with Semmelweis feedback, weeks 5–8), a one-week washout (week 9), and Phase 3 (sustainability assessment, weeks 10–12). Paired ATP-CFU samples were collected weekly. Within-group comparisons used Kruskal–Wallis H tests with post hoc Dunn’s tests and Bonferroni correction. Secondary outcomes included Semmelweis global and zone-specific coverage and the correlation between subject-level Semmelweis coverage and ATP bioluminescence (Spearman’s rho). Results: A total of 781 paired ATP-CFU samples and 497 Semmelweis evaluations were analyzed. Mean ATP declined from 195.9 RLU at baseline to 148.2 RLU in Phase 2 (−24.4%) and 154.8 RLU in Phase 3 (−21.0%; Kruskal–Wallis H = 102.73, p < 0.001). CFU/mL declined from 84.8 to 66.2 (−21.9%) and 70.7 (−16.6%; H = 22.48, p < 0.001). Post hoc comparisons confirmed significant Phase 1 versus Phase 2 and Phase 1 versus Phase 3 differences for both markers (all p < 0.01), while Phase 2 versus Phase 3 was non-significant, indicating stabilization at an improved level. Subject-level Semmelweis coverage correlated negatively with ATP (rho = −0.665, 95% CI −0.778 to −0.510, p < 0.001), supporting construct validity at the operator level. Semmelweis global coverage was 93.1% (Phase 2) and 90.6% (Phase 3); interdigital spaces showed the highest inadequacy rate (73.9% protocol-based, 92.5% targeted). Conclusions: Real-time visual feedback via UV-fluorescence imaging was associated with significant and sustained improvements in hand hygiene quality beyond baseline. ATP, CFU, and Semmelweis assessments captured complementary, non-redundant dimensions, supporting multimodal evaluation. Interdigital spaces and fingertips remained persistent failure points requiring targeted educational reinforcement. Full article

Informal waste picking and scrap collection constitute critical yet highly precarious livelihood strategies among economically marginalised women in rural South Africa. This article presents a cross-sectional mixed-methods study, guided by Sen’s Capability Approach as its analytical framework, examining the lived experiences, motivations, and livelihood outcomes of 126 Black African women engaged in scrap collection along the N2 Highway in the Eastern Cape, specifically in Mthatha, Xhora, and Qumbu. The study integrates quantitative descriptive statistics with qualitative thematic analysis derived from structured interviewer-administered questionnaires. The findings indicate that participation in scrap collection is overwhelmingly driven by structural economic constraints, including chronic unemployment, household poverty, and extensive caregiving responsibilities, rather than autonomous occupational choice. The sample is characterised by limited educational attainment, frequently disrupted by poverty, bereavement, early marriage, and early caregiving roles, which collectively constrain access to formal employment opportunities. Participants consistently described scrap collection as physically hazardous, economically insecure, and detrimental to both physical health and psychosocial wellbeing, while remaining indispensable for household survival. Through the lens of the Capability Approach, these conditions reflect severe restrictions in substantive freedoms, particularly in relation to economic security, bodily health and human dignity. Expressions of acceptance are interpreted as manifestations of adaptive preferences formed under conditions of prolonged structural deprivation rather than indicators of genuine agency. The study contributes to informal economy scholarship by demonstrating how intersecting structural inequalities constrain capability sets and limit livelihood trajectories and calls for targeted policy interventions to enhance occupational safety, income security and access to sustainable livelihood alternatives. Full article

Background/Objectives: Western Canadian and U.S. communities outside urban centres remain underserved by primary, specialist, emergency, mental health, and chronic-disease services. These access problems reflect distance, weather, workforce shortages, specialist maldistribution, primary care attachment gaps, broadband limitations, and the governance realities of Indigenous and Tribal communities. This scoping review with narrative synthesis examined how telehealth and virtual-care models affect rural access in western Canada and the western/frontier United States. Methods: Searches were completed on 21 May 2026 in PubMed/MEDLINE, Embase, CINAHL, Scopus, the Cochrane Library, and PubMed Central. Supplementary searches included Google Scholar, publisher platforms, reference-list checking, and official Canadian and U.S. health-system sources. Peer-reviewed evidence published from 1 January 2016 to 21 May 2026 was eligible when it addressed rural, remote, frontier, Indigenous, underserved, western, or northern healthcare settings and reported access, implementation, safety, continuity, equity, or service-use outcomes. Results: The search identified 112 records; 27 duplicates were removed, 85 records were screened, 37 full texts were assessed, and 28 peer-reviewed records were included. Seven official sources were retained separately. Evidence was mainly observational, qualitative, mixed-methods, implementation-focused, or review-level. Moderate confidence supported telehealth for travel reduction and specialist input, especially through eConsultation, provider-to-provider consultation, telementoring, and real-time emergency support. Confidence was low to moderate for hybrid primary care and telemental health, and low for durable reductions in emergency department use. Conclusions: Telehealth may be most appropriately implemented as a hybrid, locally anchored, culturally safe access model, not as a stand-alone substitute for rural primary care, specialist capacity, or emergency services. Implementation should include broadband support, local physical assessment capacity, documentation, continuity, patient education, and clear escalation pathways. Full article

Recently, the problem of food waste management has attracted the attention of producers, processors, retailers, and consumers due to economic, environmental, food safety, and sustainability consequences, affecting the entire food supply chain. This article reviews data on food waste of animal origin at different stages along the production and transformation systems, from an environmental, economic, or social perspective. Results show differences between developed and developing countries. While in developed countries, most waste occurs at the end of the food chain, in developing countries, most waste occurs in primary production and transportation. Food waste is very expressive in production and retail, but also in final consumption in households and food services. Mitigating measures include upcycling, i.e., recovering valuable food components for industrial use with economic and environmental benefits, and alternatives for food waste reutilization. The role of the consumer is unquestionable, particularly when shopping for food for the household or when consuming food in restaurants or canteens. Hence, it is crucial to understand the behaviours leading to food waste as a way to reduce it and implement strategies to effectively reduce food waste at various levels. The role of education, regulation, and policies is pivotal in achieving minimal food waste. Full article

Generative Artificial Intelligence (GenAI) in cardiac surgery refers to the integration of advanced computational models, such as Large Language Models (LLMs), to automate and enhance clinical decision-making, preoperative risk assessment, and surgical education. In the context of surgical training, it functions as a personalized pedagogical tool that supports various learning activities, ranging from information acquisition and clinical inquiry to procedural practice, while requiring rigorous human oversight to ensure patient safety and clinical accuracy. (1) Background: Generative Artificial Intelligence (GenAI) is increasingly integrated into health professions education, offering new opportunities for learning; however, its specific application and pedagogical mapping in high-stakes fields such as cardiac surgery remain underexplored. This systematic review investigates how GenAI is utilized in cardiac surgery and surgical education, aligning these uses with Laurillard’s six learning types. (2) Methods: Following the PRISMA 2020 guidelines, we searched the Web of Science Core Collection for studies on GenAI in cardiac surgery, resulting in 42 studies that met the inclusion criteria. Study quality was appraised using the Medical Education Research Study Quality Instrument (MERSQI). (3) Results: GenAI applications most frequently supported clinical inquiry (93.8%) and practice (68.8%), demonstrating expanding efficiency across commercial and open-source models (including ChatGPT-4o, Gemini AI, and emerging reasoning architectures such as DeepSeek) for knowledge acquisition and medical production. While it significantly improves individualized learning and preoperative assessment workflows, its practical role in Discussion and Collaboration remains heavily underutilized, highlighting a distinct shift toward individualized solo professional workflows. (4) Conclusions: GenAI provides a transformative and scalable approach to cardiac surgical training by offering personalized and accessible knowledge retrieval. However, clinical educators and governance bodies must deliberately balance these immediate productivity benefits with long-term concerns regarding structural “hallucinations,” data verifiability, and the preservation of collaborative competencies within modern multidisciplinary Heart Teams. Full article