Search Results (3,570)

Healthcare professionals must acquire and maintain both declarative knowledge and fine psychomotor skills across a wide range of clinical procedures. Human working memory is physiologically limited, and the high cognitive demands of clinical environments frequently contribute to medical errors and adverse events. Intra-individual performance variability—driven by fatigue, stress, and motivation—represents a further challenge that conventional medical safety education has not adequately addressed. According to the World Health Organization, patient harm ranks fourteenth in the global burden of disease, with approximately 10% of hospitalised patients in high-income countries experiencing harm within healthcare facilities. This study reports the design, theoretical rationale, and preliminary outcomes of an augmented reality (AR) glasses system for hands-free, self-directed medical procedural training, developed from a human factors and ergonomics (HFE) perspective. The system integrates a see-through head-mounted display (HMD; Epson Moverio BT-40S), bone-conduction earphones (Shokz OpenComm), and an industrial-grade voice recognition application (NEC Solution Innovators), achieving fully hands-free operation compatible with aseptic technique. Content design is grounded in cognitive load theory (CLT) and the cognitive theory of multimedia learning (CTML), extended by neuroscientific evidence on multisensory integration and memory consolidation. More than 40 procedure-specific modules have been developed in-house at Tokyo University of Technology, spanning airway management, vascular access, respiratory therapy, dialysis, and cardiac support. In a four-year longitudinal survey (virtual reality (VR) simulator; n = 286), major satisfaction items consistently exceeded the scale midpoint. In an AR endotracheal suctioning cohort (n = 38/22), procedural flow understanding was rated 3.95/5.0. A peer-reviewed randomised controlled trial (Clinical Simulation in Nursing, n = 36) demonstrated significantly superior skill improvement (p < 0.001) and learning motivation (p = 0.001) in the AR group versus textbook self-practice. Principal ergonomic limitations of current HMD hardware—excessive weight, narrow field of view, and absence of medical-grade certification—are documented, and AI-based real-time procedural assessment is identified as a priority for the next research phase. Full article

Background: Digital health technologies are increasingly integral to healthcare delivery worldwide; however, successful adoption depends on more than technological availability. In nursing, readiness is particularly important because digital systems increasingly shape documentation, communication, decision support, and care delivery. Within the context of Saudi Arabia’s healthcare transformation, doctoral nursing students are positioned as future educators, clinicians, and leaders whose perceptions can provide insight into digital health readiness and preparation. Aim: This study aimed to explore doctoral nursing students’ perceptions of their readiness to adopt digital health technologies in Saudi Arabia, guided by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Methods: This exploratory, qualitative, descriptive study recruited 9 doctoral nursing students from a public university in Saudi Arabia using purposive sampling based on predefined eligibility criteria. Individual semi-structured interviews were conducted online and audio-recorded. Data were analyzed using a hybrid inductive–deductive thematic approach. UTAUT2 informed the deductive component of the analysis, while inductive coding and cross-case comparison supported theme generation. Results: Four interrelated themes were identified. First, readiness was positive but conditional, shaped by movement from openness to professional necessity, familiarity, workflow fit, and caution about the possible weakening of foundational or manual competence. Second, adoption depended on practical value and system credibility, including access, convenience, efficiency, safety, documentation integrity, accuracy, privacy, and reliability. Third, adoption was organizationally mediated through leadership, peer culture, infrastructure, implementation conditions, training, follow-up, and academic preparation. Fourth, digital health was understood as supporting, not substituting for, nursing work by reducing avoidable burden and creating more space for direct care while preserving human presence, communication, and clinical judgment. Conclusions: In this sample of doctoral nursing students, digital health readiness was positive but conditional. The findings suggest that readiness reflects a context-sensitive professional judgment shaped by educational preparation, organizational support, system credibility, workflow compatibility, and the perceived ability of digital technologies to enhance nursing work rather than replace it. Implications: The findings suggest that nursing education and practice should strengthen applied digital health competencies through simulation-based preparation, electronic documentation training, privacy and ethics education, workflow-aligned implementation, and sustained organizational support. Full article

Background/Objectives: In Saudi Arabia, noncommunicable diseases (NCDs) are an increasing public health concern, with almost 70% of deaths related to chronic diseases. The study aimed to analyze 33-year trends in NCD risk factors and apply machine learning (ML) models to identify ecological associates of premature NCD-related mortality, sex-specific analyses and project trajectories to 2030. Methods: A longitudinal ecological time-series design which used WHO Global Health Observatory (GHO) NCD Indicators (1990–2022; select lipid indicators from 1980). Five supervised regression ML models—OLS, LASSO, Ridge, Random Forest, and Gradient Boosting—were trained with TimeSeriesSplit cross-validation (five folds) to preserve temporal order and prevent data leakage. A formal PELT changepoint algorithm confirmed trend breakpoints. Linear projections to 2030 were estimated with 95% prediction intervals. Results: Adult obesity increased by +20.6 percentage points (pp) over 33 years. Under a no-policy-change scenario, female obesity is projected at 50.3% by 2030 (95% PI: 50.0–50.5%). Premature NCD mortality declined by −5.9 pp. Under TimeSeriesSplit CV, all models yielded negative R², confirming LOOCV R² = 0.98 reflected shared time-trend artefacts; the ML component is reframed as descriptive feature-importance analysis. The obesity sex gap (female minus male) was the strongest ecological associate of premature NCD mortality. Diabetes treatment coverage showed a strong inverse ecological association (r = −0.913). Conclusions: NCD risk factors in Saudi Arabia are evolving in complex ways. Targeted interventions addressing sex-specific disparities and healthcare system performance are urgently needed to meet national and global NCD targets. Full article

This study investigates data augmentation as a strategy for addressing dataset scarcity in Internet of Medical Things (IoMT) cybersecurity and improving intrusion-detection system performance. Four augmentation methods—Rule-Based, Tabular Variational Autoencoder (TVAE), Conditional Tabular Generative Adversarial Network (CTGAN), and Gaussian Copula—were applied to two publicly available IoMT datasets (ECU-IoHT and WUSTL-EHMS) to generate augmented training data with differing class distributions and feature characteristics. Eleven machine learning algorithms were evaluated using Matthews Correlation Coefficient (MCC), F1-score, accuracy, and error-based metrics. Results showed consistent performance improvements across all evaluated models relative to the baseline datasets. The Rule-Based method produced the strongest overall results, achieving the highest MCC (0.9757), F1-score (99.19%), and accuracy (99.18%) with LightGBM, alongside low false-positive and false-negative rates. Among the generative approaches, TVAE delivered the strongest overall practical performance (F1-score = 96.94%, accuracy = 96.92%), while CTGAN achieved a marginally higher MCC (0.9047) and also produced competitive results with balanced class representation. Gaussian Copula generated the weakest overall outcomes, primarily due to highly skewed class distributions. Traditional models, such as Logistic Regression and Naive Bayes, recorded the largest relative gains, indicating that augmentation can substantially improve simpler classifiers in data-scarce environments. Overall, the findings demonstrate that augmentation quality depends not only on dataset expansion, but also on preserving class balance, feature diversity, and realistic traffic relationships. These results provide practical guidance for strengthening IoMT intrusion-detection systems in healthcare environments. Full article

Background/Objectives: Continuous quality improvement (CQI) requires timely, patient-centered evidence on how people experience healthcare delivery. Structured surveys provide important benchmarks, but their predetermined items may miss emerging or system-specific concerns. This study assesses whether unsolicited online patient reviews can serve as a scalable patient-experience data source for identifying hospital service quality priorities across contrasting healthcare systems. Methods: We analyzed 8247 Google Maps hospital reviews posted in 2024, including 5007 Chinese-language reviews from 24 Taiwanese medical centers and 3240 English-language reviews from 21 large U.S. referral hospitals. Separate language-specific preprocessing pipelines and Latent Dirichlet Allocation (LDA) topic models identified patient-salient service quality dimensions in each country. Cross-lingual semantic mapping then distinguished universal dimensions from system-specific concerns, and star-rating differences across semantically equivalent dimensions were compared. Results: Seven service quality dimensions emerged in each country: five were cross-nationally shared (emergency care, positive care experience, professional medical team, administrative process, and inpatient/treatment care), and each system had two system-specific dimensions. Taiwanese reviews foregrounded service attitude and facility/environment quality, while U.S. reviews foregrounded billing/insurance and clinic systems/access. Ratings for emergency care and administrative process were consistently low across both systems, whereas ratings for the professional medical team were substantially higher in U.S. reviews. Conclusions: Online patient reviews can complement formal patient-experience instruments by revealing actionable CQI priorities that are both universal and context dependent. Emergency care and administrative efficiency represent shared improvement needs across both systems. System-specific interventions include interpersonal training and infrastructure investment in high-utilization single-payer settings, and billing transparency and care coordination in fragmented multi-payer systems. Institutional structures appear to play a more prominent role than cultural factors in shaping which service quality dimensions emerge, though both forces contribute. Established frameworks may inadequately capture system-specific patient concerns. Full article

Background: The role of healthcare workers (HCWs) is crucial in promoting and educating about sustainable behaviors. This study aimed to assess Italian HCWs’ knowledge, attitudes, practices, and educational role regarding climate change and its health implications. Methods: A cross-sectional study was conducted from May to December 2024. Results: Among the 564 HCWs who participated, 45% and 40.3% considered climate change very important and urgent, respectively. Nurses, who had at least one chronic disease, who self-assessed their knowledge of climate change as good/very good, who needed additional information, and those who knew that problems in global food supply are consequences of climate change were more likely to consider it an urgent problem. Women, those married/cohabitant, and who knew that the spread of infectious diseases, problems in the global food supply, water scarcity or clean water conservation were consequences of climate change, were more likely to believe that climate change is causing health problems. Men, who had at least one chronic disease, who knew that infants/children, elderly and people with multiple medical conditions are more sensitive to climate change, those very scared of climate change, and who received information in training courses were more likely to educate patients for improving sustainability and health protection. Conclusions: Tailored training and integrating sustainability for HCWs could significantly support the health sector in adapting in climate change mitigation. Full article

Diabetic retinopathy is a leading cause of vision loss worldwide, particularly impacting individuals in low- and middle-income countries with limited healthcare access. Early detection through automated screening systems is essential for improving outcomes, as timely intervention can prevent severe vision impairment. However, most of the available AI models have not been evaluated in low-resource settings. Hence, this study presents an evaluation of the efficacy of advanced deep learning architectures for detecting rDR across diverse population datasets. A dual-phase validation approach was employed to assess model performance. Internal validation utilised the BrSET dataset to establish baseline performance metrics, while external validation was conducted on the MoDRIA dataset, which encompasses various conditions and demographics, to evaluate model robustness. Key performance metrics, including accuracy, specificity, sensitivity, F1-score, and calibration scores, were systematically recorded and analysed. Internal validation revealed high accuracy across all models, EfficientNetB0 achieved the highest classification accuracy (0.9561; 95% CI 0.9490–0.9630), EfficientNetB3 demonstrated superior overall discriminative performance, achieving the highest AUROC (0.9892; 95% CI 0.9841–0.9934) highest sensitivity (0.9573), and lowest Brier score (0.0168). Meanwhile, DenseNet exhibited the most balanced clinical screening performance, achieving the highest F1-score (0.7259; 95% CI 0.6797–0.7669) and Youden Index (0.2381), indicating improved balance between sensitivity and specificity. In contrast, external validation revealed substantial deterioration in model performance across all architectures, highlighting major limitations in cross-population generalisability. Although EfficientNetB0 achieved the highest external accuracy (0.8821; 95% CI 0.8746–0.8898), AUROC values declined markedly across models (0.5140–0.6104), accompanied by poor sensitivity, reduced F1-scores, and substantial calibration instability. EfficientNetB3 achieved the highest external sensitivity (0.5939), whereas calibration analyses demonstrated unreliable probability estimation under domain-shift conditions. These findings suggest that AI models trained on geographically homogeneous retinal imaging datasets may not generalise reliably across underrepresented populations. Population differences and imaging variability substantially affected external model performance, highlighting the need for diverse datasets, rigorous external validation, and adaptive recalibration before clinical deployment of AI-driven DR screening systems. Full article

This study investigates the impact of different types of personal protective equipment (PPE), specifically Powered Air-Purifying Respirators (PAPRs) and traditional N95 masks with face shields, on the physiological stress responses of healthcare workers (HWs) during the COVID-19 pandemic. Utilizing an interventional randomized crossover trial design, the research encompasses a simulation phase with ten participants followed by field testing involving thirty frontline healthcare professionals in a tertiary-care hospital setting. Heart rate (HR) and movement data were collected through smartwatches, while trained observers recorded the duration and nature of various activities undertaken during simulations. Data analysis employed statistical techniques, including Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE), to explore potential correlations between PPE type, HR, and movement. Clustering validation measures such as the Calinski–Harabasz, Davies–Bouldin, and Silhouette scores were applied to evaluate the difference between each type of PPE. The results indicated no significant differentiation in HR responses between the two PPE types. However, because HR may lack the sensitivity to fully capture variations in cognitive load or stress, these findings should be interpreted as an exploratory baseline. Additionally, no clear distinctions were observed regarding individual user responses or the activities performed, even when considering movement data. Although the findings imply non-inferiority of the examined PPE, future research including heart rate variability as a more comprehensive indicator of stress would be informative. This research contributes valuable insights into PPE selection and its implications for healthcare worker performance and well-being in high-stress environments, ultimately aiming to inform guidelines and training programs to enhance healthcare delivery during infectious disease outbreaks. Full article

Background: Cultural, religious, and spiritual (CRS) needs are central to holistic palliative and end-of-life care (PEoLC), yet the confidence and perceived preparedness of community and voluntary sector staff in addressing them remain underexplored. As PEoLC increasingly occurs in community settings, understanding staff preparedness for culturally and spiritually sensitive care is vital. Objective: This service evaluation examined CRS perceived preparedness and confidence among staff across Leicester, Leicestershire, and Rutland (LLR), exploring perceived challenges and available resources. Methods: A modified Confidence and Perceived preparedness in the CRS Care Survey was distributed to healthcare, hospice, charity, and community staff (May–August 2025). Likert scale data (n = 39) were analysed descriptively; qualitative responses underwent thematic analysis using Braun and Clarke’s framework, which was co-produced with stakeholders. Results: Staff placed high importance on CRS needs (cultural M = 4.48, SD = 0.61; religious/spiritual M = 4.66, SD = 0.53) but reported lower confidence in the organisational capacity to meet them (M = 3.15 and M = 3.05). Qualitative survey findings showed that staff recognised CRS needs as central to holistic, individualised care, emphasising proactive assessment and avoiding assumptions. Barriers included fear of causing offence, organisational constraints, and challenges in supporting families, alongside concerns about unmet needs. Participants highlighted reliance on informal resources and a clear need for accessible, lived-experience-based training and practical guidance. A prototype CRS resource toolkit, including lived-experience videos and guidance for supporting Muslim patients, was co-developed and reviewed by healthcare, community, and public contributors. Conclusions: Staff commitment to CRS-sensitive PEoLC is strong, but practical tools and training are lacking. A virtual CRS toolkit could enhance confidence, communication, and culturally responsive care across multidisciplinary settings. Full article

Background/Objectives: The gut microbiota is fundamental to human health. Probiotics are key interventions for modulating microbial balance, requiring future healthcare professionals to understand these concepts. Evidence evaluating the knowledge, attitudes, and practices (KAP) of medical students in Ecuador is limited. This study assessed these aspects among students in Greater Guayaquil. Methods: A cross-sectional study was conducted at a university in Samborondón between August and November 2025. A previously published questionnaire was used to collect data on microbiota and probiotic knowledge, attitudes, and personal practices. Data were analyzed using descriptive statistics and multivariable regression. Results: Among 382 participants, the mean knowledge score was 22.76 ± 9.1 out of 44 (52.7%). Higher scores were associated with advanced academic standing and prior formal instruction. Significant gaps were observed in probiotic safety and microbiota–drug interactions. Attitudes were positive (median 10/16), with strong support for enhanced training. Probiotic use was common, though uncertainty about product composition and administration persisted. Conclusions: Medical students possess moderate yet uneven knowledge of microbiota and probiotics, alongside positive attitudes. These findings suggest the need for greater emphasis on microbiota science, probiotic safety, and drug interactions within medical curricula. Full article

Background/Objectives: Sedation is a fundamental component of gastrointestinal endoscopy, improving patient comfort, procedural quality, and overall satisfaction. However, traditional drug-centered sedation models are increasingly challenged by rising procedural volumes, aging populations, and limited anesthesiology resources. The aim of this narrative review is to provide an integrated overview of evolving pharmacological agents, monitoring strategies, organizational models, and future directions toward personalized, technology-supported sedation pathways. Methods: A structured literature search was conducted across PubMed/MEDLINE, Scopus, and Web of Science for studies published between January 2010 and December 2025. Relevant guidelines, randomized controlled trials, meta-analyses, and large observational studies were included. Evidence was synthesized qualitatively, emphasizing clinical applicability and real-world relevance. Results: Propofol remains the most widely used sedative agent due to its rapid onset and recovery profile, although its narrow therapeutic window and lack of antagonist limit its safety in high-risk patients. Emerging agents such as remimazolam and ciprofol demonstrate comparable efficacy with improved respiratory and hemodynamic safety profiles, particularly in elderly populations. Adjunctive strategies, including procedure-specific approaches such as spinal anesthesia, may further optimize sedation. Advanced monitoring tools, such as capnography, bispectral index, and high-flow nasal cannula, show potential in enhancing safety, especially in selected high-risk groups. Structured training programs and standardized discharge criteria are essential for ensuring quality and safety. Conclusions: Sedation in gastrointestinal endoscopy is transitioning from a standardized, drug-centered approach to a personalized, risk-adapted, and technology-supported model. Integration of novel pharmacological agents, advanced monitoring, and structured training will be key to improving patient safety, procedural efficiency, and healthcare sustainability. Full article

Background/Objectives: Inappropriate antibiotic prescribing in primary healthcare (PHC) contributes to bacterial antimicrobial resistance (AMR). Antibiotic stewardship, including measuring the appropriateness of antibiotic prescribing using quality indicators, is a priority in PHC where most antibiotics are used. Using previously developed WHO AWaRe classification-based quality indicators, we aim to test the clinimetric properties of 13 acute respiratory tract infection (RTI) quality indicators and qualitatively explore factors influencing PHC antibiotic prescribing in South Africa. Methods: We conducted a mixed-methods exploratory feasibility study using point prevalence surveys (PPSs) with clinimetric assessment and prescriber interviews. PPSs were conducted at four PHC facilities in Gauteng province that had taken part in previous PPS studies, alongside face-to-face interviews with PHC personnel. Results: In total, 52/52 (100%) RTI patients received antibiotics. Four (30.8%) indicators achieved scores above 85%, while six (46.2%) scored below 50%. All indicators had applicability scores ≥10%. Twelve (92.3%) indicators had a measurability score of 100%, while one (7.7%) had a measurability score <75%. Twelve (92.3%) indicators met all predefined acceptable scores for applicability and measurability. No participant knew of the WHO’s AWaRe classification and none had specific training on antibiotic prescribing and AMR. They also had no antibiotic stewardship programmes (ASPs) or specific antibiotic-prescribing guidelines at their facilities. Key factors affecting antibiotic prescribing included shortages, patient expectations and fear of complications. Conclusions: The indicators demonstrated acceptable clinimetric properties in South Africa. Robust locally validated indicators, combined with ASPs promoting the AWaRe classification, are imperative for accurate assessment and improvement of antibiotic prescribing. Full article

Background/Objectives: Healthcare workers (HCWs) face occupational hazards that increase their risk of Coronavirus Disease of 2019 (COVID-19). This study aims to evaluate HCWs’ perceptions of the effectiveness of Personal Protective Equipment (PPE) in preventing COVID-19 infection and to identify risk factors associated with HCW infection. Methods: A cross-sectional study design was used, with a structured, self-administered, closed-ended questionnaire to collect retrospective data for the period 2020 to 2022 at a tertiary hospital in Johannesburg, South Africa. Results: PPE was effective in reducing COVID-19 infection, according to 230 (57.07%) participants, while 173 (42.93%) disagreed. A significant association (p = 0.034) with a small effect size (Cramer’s V = 0.161) was found between the number of HCWs infected with COVID-19 and their perceptions of PPE’s effectiveness. White HCWs were more likely to perceive PPE as effective than Black HCWs (AOR = 3.82, p = 0.046). Support and clerical staff reported higher perceived effectiveness of PPE (AOR = 2.98, p = 0.040). Conclusions: HCWs encountered COVID-19 infections and various challenges that necessitate interventions and policies to safeguard them in hospital settings and ensure prompt virus management, including ensuring sufficient PPE supplies. The perceptions of PPE effectiveness among HCWs are shaped by an interplay of institutional practices, personal beliefs, and structural factors. These perceptions are closely tied to essential elements such as training, reliable PPE availability, and regular hand hygiene practices, underscoring the need to address both systemic and behavioral dimensions. Full article

Background: Sustainable healthcare in obstetric and maternity nursing emphasizes the provision of high-quality, safe, and environmentally responsible care for women and newborns. Nurses’ knowledge, awareness, and clinical practices are central to the implementation of sustainable approaches, including efficient resource management, evidence-based interventions, and patient education. Evaluating these dimensions is essential for identifying gaps, informing targeted training, and supporting sustainable and effective maternal care aligned with global health goals. Accordingly, this study aimed to assess obstetric and maternity nurses’ knowledge, awareness, and clinical practices related to sustainable healthcare. Method: A cross-sectional study design was employed. A convenience sampling technique was used to recruit obstetric and maternity nurses working in the selected study settings during the data collection period. A total sample of 120 participants was targeted. The study was conducted at Al-Azhar University Hospital in New Damietta and selected Family Medicine Centers in Damietta Governorate, Egypt. Data were collected using a structured, self-administered questionnaire developed specifically for this study to assess eco-conscious nursing practices in obstetrics and gynecology units. The questionnaire included sections addressing demographic and professional characteristics, knowledge and awareness of sustainable healthcare, eco-conscious clinical practices in maternity settings, perceived barriers and institutional support, attitudes and advocacy toward environmental sustainability, procedure- and material-related environmental concerns, and energy and water conservation behaviors. Responses were measured using standardized 5-point Likert and frequency scales, with composite scores calculated to categorize levels of knowledge, practices, and attitudes toward sustainability; higher scores indicated greater knowledge, awareness, and engagement in sustainable practices. Results: Overall, among the 120 nurses, of whom 62 (51.7%) had reported having heard about sustainability and received training about it, whereas 58 (48.3%) had not. Most participants held a bachelor’s degree (n = 54, 45.0%), nearly half had more than 10 years of nursing experience (n = 58, 48.3%), and the largest proportion worked in delivery rooms (n = 53, 44.2%). Regarding knowledge, attitude, and practice, good knowledge was observed in 61 participants (50.8%), good practice in 46 participants (38.3%), and positive attitudes in 108 participants (90.0%). The findings also showed that trained nurses in obstetrics and gynecology units demonstrated significantly higher knowledge, more positive attitudes, and better eco-conscious practices compared to untrained nurses across all domains (p < 0.001). Conclusions: The study demonstrates that maternity nurses showed moderate to high awareness and positive attitudes toward sustainability, while environmentally sustainable practices were less consistently implemented, indicating a clear knowledge–attitude–practice gap. Nurses who received sustainability-related training consistently achieved significantly higher knowledge, attitude, and practice scores than untrained nurses. Full article

Independent community pharmacies serve as critical healthcare access points in rural areas, yet they consistently underperform chain pharmacies on contraceptive access measures. This narrative commentary draws on mystery caller studies, implementation research, and policy analyses to examine pharmacy-based contraceptive access in the United States (US). Using emergency contraception (EC) as a case study, we show that independent pharmacies stock EC at dramatically lower rates than chains (e.g., 14.6% vs. 76.3% in West Virginia), provide less accurate information about purchase requirements and timing, and impose more barriers to access. Because independent pharmacies account for 76.5% of pharmacies in rural areas, this disparity concentrates contraceptive inaccessibility in communities already facing the highest rates of unintended pregnancy, maternal mortality, and maternity care deserts. This pattern extends beyond EC to pharmacist-prescribed contraception and over-the-counter daily oral contraceptives. These disparities reflect systemic barriers, such as inadequate reimbursement, limited training infrastructure, and absence of corporate support, rather than failures of individual pharmacies. Drawing on implementation research and the success of West Virginia’s COVID-19 vaccination model, this paper proposes coordinated, sector-specific strategies to transform independent pharmacies from barriers into bridges for rural women’s contraceptive access. Full article