Search Results (972)

Endotoxins, lipopolysaccharides released from the outer membrane of Gram-negative bacteria, pose a significant risk in healthcare environments, particularly in Central Sterile Supply Departments (CSSDs), where the delivery of sterile pyrogen-free medical devices is critical for patient safety. Traditional methods for controlling endotoxins in water systems, such as ultraviolet (UV) disinfection, have proven ineffective at reducing endotoxin concentrations to comply with regulatory standards (<0.25 EU/mL). This limitation presents a significant challenge, especially in the context of reverse osmosis (RO) permeate used in CSSDs, where water typically has very low conductivity. Despite the established importance of endotoxin removal, a gap in the literature exists regarding effective chemical-free methods that can meet the stringent endotoxin limits in such low-conductivity environments. This study addresses this gap by evaluating the effectiveness of the eBooster™ electrochemical technology—featuring proprietary electrode materials and a reactor design optimized for potable water—for endotoxin removal from water, specifically under the low-conductivity conditions typical of RO permeate. Laboratory experiments using the B250 reactor achieved >90% endotoxin reduction (from 1.2 EU/mL to <0.1 EU/mL) at flow rates ≤5 L/min and current densities of 0.45–2.7 mA/cm². Additional real-world testing at three hospitals showed that the eBooster™ unit, when installed in the RO tank recirculation loop, consistently reduced endotoxin levels from 0.76 EU/mL (with UV) to <0.05 EU/mL over 24 months of operation, while heterotrophic plate counts dropped from 190 to <1 CFU/100 mL. Statistical analysis confirmed the reproducibility and flow-rate dependence of the removal efficiency. Limitations observed included reduced efficacy at higher flow rates, the need for sufficient residence time, and a temporary performance decline after two years due to a power fault, which was promptly corrected. Compared to earlier approaches, eBooster™ demonstrated superior performance in low-conductivity environments without added chemicals or significant maintenance. These findings highlight the strength and novelty of eBooster™ as a reliable, chemical-free, and maintenance-friendly alternative to traditional UV disinfection systems, offering a promising solution for critical water treatment applications in healthcare environments. Full article

Background/Objectives: Mild Cognitive Impairment (MCI), a condition between normal aging and dementia, is characterized by cognitive changes that do not significantly affect instrumental activities of daily living. The Memory Support System (MSS), an evidence-based behavioral intervention developed by the Mayo Clinic, has been shown to aid those living with MCI and their support partners in coping with cognitive challenges. However, the MSS has not been offered clinically within the Canadian context. Therefore, we conducted a study assessing the feasibility of the MSS from the perspectives of individuals living with MCI and their support partners. Methods: Participants from an institutional registry of research participants, patients, and support partners at a memory clinic, as well as members of a local Dementia Society, were approached to complete an online or paper version of a survey assessing feasibility dimensions. Responses were compared between and within groups for differences in mean scores and associations between linked binary choice response questions. Results: A total of 77 responses were received; 39 surveys were completed by participants with MCI, and 38 by support partners. Respondents found the MSS to be acceptable and practical. On average, participants thought it would be more difficult to train in using the MSS than support partners. Both groups expressed interest in the intervention. On average, participants with MCI and support partners preferred virtual MSS training to in-person and indicated more interest in participating in training over six weeks as compared to two weeks. Conclusions: Flexibility in duration and format when offering the MSS are important considerations when offering the intervention as part of a clinical program. Future research should evaluate cost-effectiveness (e.g., financial, staff resources, etc.) of the MSS approach if it were to be institutionalized in the Ontario healthcare system. Full article

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

This review explores the biofilm architecture and drug resistance of Enterococcus faecalis in clinical and environmental settings. The biofilm in E. faecalis is a heterogeneous, three-dimensional, mushroom-like or multilayered structure, characteristically forming diplococci or short chains interspersed with water channels for nutrient exchange and waste removal. Exopolysaccharides, proteins, lipids, and extracellular DNA create a protective matrix. Persister cells within the biofilm contribute to antibiotic resistance and survival. The heterogeneous architecture of the E. faecalis biofilm contains both dense clusters and loosely packed regions that vary in thickness, ranging from 10 to 100 µm, depending on the environmental conditions. The pathogenicity of the E. faecalis biofilm is mediated through complex interactions between genes and virulence factors such as DNA release, cytolysin, pili, secreted antigen A, and microbial surface components that recognize adhesive matrix molecules, often involving a key protein called enterococcal surface protein (Esp). Clinically, it is implicated in a range of nosocomial infections, including urinary tract infections, endocarditis, and surgical wound infections. The biofilm serves as a nidus for bacterial dissemination and as a reservoir for antimicrobial resistance. The effectiveness of first-line antibiotics (ampicillin, vancomycin, and aminoglycosides) is diminished due to reduced penetration, altered metabolism, increased tolerance, and intrinsic and acquired resistance. Alternative strategies for biofilm disruption, such as combination therapy (ampicillin with aminoglycosides), as well as newer approaches, including antimicrobial peptides, quorum-sensing inhibitors, and biofilm-disrupting agents (DNase or dispersin B), are also being explored to improve treatment outcomes. Environmentally, E. faecalis biofilms contribute to contamination in water systems, food production facilities, and healthcare environments. They persist in harsh conditions, facilitating the spread of multidrug-resistant strains and increasing the risk of transmission to humans and animals. Therefore, understanding the biofilm architecture and drug resistance is essential for developing effective strategies to mitigate their clinical and environmental impact. Full article

Background: The surge in COVID-19 cases during the pandemic created a disease burden. An epidemiological study on COVID-19 is required as not much is known about the impact of containment and mitigation on health. We aimed to compare the epidemiological features during the years of the COVID-19 pandemic in the Vidarbha region in Maharashtra, India, to understand the epidemiology changes throughout the pandemic’s progression. Method: All of the cases reported at our testing centers in Nagpur and its periphery during the three years of the pandemic (i.e., from February 2020 to December 2022) were included. Descriptive analyses of variables of interest and statistical measures were compared. Results: There were 537,320 tests recorded during the study period. Of these, 13,035 (13.29%), 42,909 (13.70%), and 19,936 (15.91%) tested positive in 2020, 2021, and 2022, respectively. Hospitalization decreased from 2020 to 2022. An age group shift from 45 to 16–30 years over the pandemic was noticed. Seasonally, positivity peaked in September (27.04%) in 2020, in April (43.4%) in 2021, and in January in 2022 (35.30%). The estimated case fatality ratio was highest in 2021 (36.68%) over the three years in the hospital setting. Conclusion: Understanding the changing epidemiology of SARS-CoV-2 strengthens our perceptive of this disease, which will aid in improving the healthcare system in terms of both controlling and preventing the spread of COVID-19. Full article

This study presents a DIKWP-driven artificial consciousness framework for IoT-enabled smart healthcare, integrating a Data–Information–Knowledge–Wisdom–Purpose (DIKWP) cognitive architecture with a software-defined IoT infrastructure. The proposed system deploys DIKWP agents at edge and cloud nodes to transform raw sensor data into high-level knowledge and purpose-driven actions. This is achieved through a structured DIKWP pipeline—from data acquisition and information processing to knowledge extraction, wisdom inference, and purpose-driven decision-making—that enables semantic reasoning, adaptive goal-driven responses, and privacy-preserving decision-making in healthcare environments. The architecture integrates wearable sensors, edge computing nodes, and cloud services to enable dynamic task orchestration and secure data fusion. For evaluation, a smart healthcare scenario for early anomaly detection (e.g., arrhythmia and fever) was implemented using wearable devices with coordinated edge–cloud analytics. Simulated experiments on synthetic vital sign datasets achieved approximately 98% anomaly detection accuracy and up to 90% reduction in communication overhead compared to cloud-centric solutions. Results also demonstrate enhanced explainability via traceable decisions across DIKWP layers and robust performance under intermittent connectivity. These findings indicate that the DIKWP-driven approach can significantly advance IoT-based healthcare by providing secure, explainable, and adaptive services aligned with clinical objectives and patient-centric care. Full article

Background/Objectives: It is essential to explore and disseminate positive deviance strategies that promote resilience, mindfulness, and well-being beyond stress and burnout reduction strategies for residents and physicians who experience high levels of occupational stress. This scoping review maps studies that investigate positive deviance strategies to enhance the well-being of residents and physicians. Methods: A scoping review was conducted by PRISMA guidelines to identify English-language studies on strategies for physician well-being. PubMed, MEDLINE, Embase, and ERIC were searched using terms related to well-being, coping, and medical education. Results: Among the 38 studies included, 17 (44.7%) targeted physicians in graduate medical education (GME), while 19 (50%) focused on continuing medical education (CME). Positive deviance strategies were identified in 26 studies and were most frequently implemented at the microsystem level, such as small group interventions (e.g., coaching, mentoring, and workshops). These strategies addressed individual and organisational factors that contribute to physician well-being and were associated with improvements in life satisfaction, resilience, professional identity, and psychological safety. The review found that positive deviance strategies were often proactive, values-driven, and disseminated organically over time, emphasising the importance of longitudinal engagement and sustained institutional support. Conclusions: This scoping review highlights the growing use of positive deviance strategies, especially at the microsystem level, to promote physician well-being. These approaches emphasise sustainable, values-driven practices and may offer effective, context-sensitive solutions within healthcare systems. Full article

Background/Objectives: Fear detection through EEG signals has gained increasing attention due to its applications in affective computing, mental health monitoring, and intelligent safety systems. This systematic review aimed to identify the most effective methods, algorithms, and configurations reported in the literature for detecting fear from EEG signals using artificial intelligence (AI). Methods: Following the PRISMA 2020 methodology, a structured search was conducted using the string (“fear detection” AND “artificial intelligence” OR “machine learning” AND NOT “fnirs OR mri OR ct OR pet OR image”). After applying inclusion and exclusion criteria, 11 relevant studies were selected. Results: The review examined key methodological aspects such as algorithms (e.g., SVM, CNN, Decision Trees), EEG devices (Emotiv, Biosemi), experimental paradigms (videos, interactive games), dominant brainwave bands (beta, gamma, alpha), and electrode placement. Non-linear models, particularly when combined with immersive stimulation, achieved the highest classification accuracy (up to 92%). Beta and gamma frequencies were consistently associated with fear states, while frontotemporal electrode positioning and proprietary datasets further enhanced model performance. Conclusions: EEG-based fear detection using AI demonstrates high potential and rapid growth, offering significant interdisciplinary applications in healthcare, safety systems, and affective computing. Full article

Introduction: Adolescents and young adults (AYAs), especially those from underserved communities, often face barriers to sexual and reproductive health (SRH). This pilot study evaluated the implementation of mobile health technologies to promote SRH care, including the integration of the Rapid Adolescent Prevention Screening^TM (RAAPS) and the Health-E You/Salud iTu^TM (Health-E You) app at a School-Based Health Center (SBHC) in Los Angeles using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Methods: This multi-method pilot study included the implementation of an integrated tool with two components, the RAAPS electronic health screening tool and the Health-E You app, which delivers tailored SRH education and contraceptive decision support to patients (who were sex-assigned as female at birth) and provides an electronic summary to clinicians to better prepare them for the visit with their patient. Quantitative data on tool usage were collected directly from the back-end data storage for the apps, and qualitative data were obtained through semi-structured interviews and in-clinic observations. Thematic analysis was conducted to identify implementation barriers and facilitators. Results: Between April 2024 and June 2024, 60 unique patients (14–19 years of age) had a healthcare visit. Of these, 35.00% used the integrated RAAPS/Health-E You app, and 88.33% completed the Health-E You app only. All five clinic staff were interviewed and expressed that they valued the tools for their educational impact, noting that they enhanced SRH discussions and helped uncover sensitive information that students might not disclose face-to-face. However, the tools affected clinic workflows and caused rooming delays due to the time-intensive setup process and lack of integration with the clinic’s primary electronic medical record system. In addition, they also reported that the time to complete the screener and app within the context of a 30-min appointment limited the time available for direct patient care. Additionally, staff reported that some students struggled with the two-step process and did not complete all components of the tool. Despite these challenges, clinic staff strongly supported renewing the RAAPS license and continued use of the Health-E You app, emphasizing the platform’s potential for improving SRH care and its educational value. Conclusions: The integrated RAAPS and Health-E You app platform demonstrated educational value and improved SRH care but faced operational and technical barriers in implementing the tool. These findings emphasize the potential of such tools to address SRH disparities among vulnerable AYAs while providing a framework for future implementations in SBHCs. Full article

The mosquito Aedes aegypti is the vector responsible for the transmission of important arboviruses such as dengue fever, Chikungunya, Zika virus, and yellow fever. These diseases affect millions of people and exert impacts on healthcare systems throughout the world. Given the increasing resistance to synthetic insecticides, essential oils from plants constitute an ecologically viable alternative for the control of this vector. The aim of the present study was to investigate the larvicidal activity of the essential oil (EO), aqueous extract, rutin, and hydrolate from the leaves of Myrciaria floribunda against Aedes aegypti larvae in the initial L4 stage. The yield of EO was 0.47%. Thirty-seven chemical constituents were identified and quantified using chromatographic methods. The major constituents were (E)-caryophyllene (27.35%), 1,8-cineole (11.25%), β-selinene (4.92%), and α-muurolene (4.92%). In the larvicidal tests, the lethal concentration (LC₅₀) was 201.73 ppm for the essential oil, 15.85% for the aqueous extract, and 22.46 ppm for rutin. The hydrolate had no larvicidal activity. The compounds that exhibited larvicidal activity against Aedes aegypti constitute a promising option for the development of natural formulations to diminish the propagation of this vector. Full article

Background: Tobacco use is disproportionately high in rural areas, contributing to elevated cancer mortality, yet it often goes untreated due to limited access to care, high poverty and uninsured rates, and co-occurring substance use disorders (SUDs). This study explored the utility of using rapid qualitative analysis (RQA) to guide the adaptation of a tobacco-free workplace program (TFWP) in Texas healthcare centers serving adults with SUDs in medically underserved areas. Methods: From September–December 2023 and May–July 2024, we conducted 11 pre-implementation, virtual semi-structured group interviews focused on adapting the TFWP to local contexts (N = 69); 7 with providers (n = 34) and managers (n = 12) and 4 with patients (n = 23) in 6 healthcare centers. Two qualified analysts independently summarized transcripts, using RQA templates of key domains drawn from interview guides to summarize and organize data in matrices, enabling systematic comparison. Results: The main themes identified were minimal organizational tobacco cessation support and practices, and attitudinal barriers, as follows: (1) the need for program materials tailored to local populations; (2) limited tobacco cessation practices and partial policies—staff requested guidance on enhancing tobacco screenings and cessation delivery, and integrating new interventions; (3) contradictory views on treating tobacco use that can inhibit implementation (e.g., wanting to quit yet anxious that quitting would cause SUD relapse); and (4) inadequate environmental supports—staff requested treating tobacco-use training, patients group cessation counseling; both requested nicotine replacement therapy. Conclusions: RQA identified key areas requiring capacity development through participants’ willingness to adopt the following adaptations: program content (e.g., trainings and tailored educational materials), delivery methods/systems (e.g., adopting additional tobacco care interventions) and implementation strategies (e.g., integrating tobacco cessation practices into routine care) critical to optimizing TFWP fit and implementation. The study findings can inform timely formative evaluation processes to design and tailor similar intervention efforts by addressing site-specific needs and implementation barriers to enhance program uptake. Full article

Background/Objectives: Access to specialized care for patients with cognitive impairment in remote areas is often limited. Despite the increasing adoption of telemedicine, standardized guidelines have not yet been specified. This study aimed to develop a comprehensive protocol for the specialized neurological, neuropsychological, and neuropsychiatric assessment of patients with cognitive disorders in remote areas through telemedicine. Methods: We analyzed data from (i) a comprehensive literature review of the existing recommendations, reliability studies, and telemedicine models for cognitive disorders, (ii) insights from a three-year experience of a specialized telemedicine outpatient clinic for cognitive movement disorders in Greece, and (iii) suggestions coming from dementia specialists experienced in telemedicine (neurologists, neuropsychologists, psychiatrists) who took part in three focus groups. A critical synthesis of the findings was performed in the end. Results: The final protocol included: technical and organizational requirements (e.g., a high-resolution screen and a camera with zoom, room dimensions adequate for gait assessment, a noise-canceling microphone); medical history; neurological, neuropsychiatric, and neuropsychological assessment adapted to videoconferencing; ethical–legal aspects (e.g., data security, privacy, informed consent); clinician–patient interaction (e.g., empathy, eye contact); diagnostic work-up; linkage to other services (e.g., tele-psychoeducation, caregiver support); and instructions for treatment and follow-up. Conclusions: This protocol is expected to serve as an example of good clinical practice and a source for official telemedicine guidelines for cognitive disorders. Ultimate outcomes include the potential enhanced access to specialized care, minimized financial and logistical costs, and the provision of a standardized, effective model for the remote diagnosis, treatment, and follow-up. This model could be applied not only in Greece, but also in other countries with similar healthcare systems and populations living in remote, difficult-to-access areas. Full article

This article focuses on how rising nativism, manifested through immigrants’ experiences of everyday discrimination, and Florida’s legal context (ascertained through immigrants’ fears of deportation), are related to immigrants’ hesitation when seeking healthcare services. Hesitation to seek healthcare, or healthcare hesitancy, is examined in the context of Florida’s SB1718, a law passed in 2023 that criminalized many aspects of being an immigrant. Based on a survey of 466 Florida immigrants and U.S. citizen adult children of immigrants, logistic regression analysis reveals that everyday experiences with discrimination are associated with a reluctance to seek healthcare services among this population. In particular, those with insecure legal immigrant status (i.e., undocumented and temporary statuses), those with financial hardship, and women demonstrate reluctance to engage with healthcare systems when controlling for other sociodemographic factors. Findings from this study exemplify how immigration policies that restrict access to healthcare and social services not only create logistical barriers to seeking care but also foster a climate of fear and exclusion that deters even those with legal status from seeking medical attention. Full article

This paper presents a Self-Learning Robotic System (SLRS) for healthcare assistance using Deep Imitation Learning (DIL). The proposed SLRS solution can observe and replicate human demonstrations, thereby acquiring complex skills without the need for explicit task-specific programming. It incorporates modular components for perception (i.e., advanced computer vision methodologies), actuation (i.e., dynamic interaction with patients and healthcare professionals in real time), and learning. The innovative approach of implementing a hybrid model approach (i.e., deep imitation learning and pose estimation algorithms) facilitates autonomous learning and adaptive task execution. The environmental awareness and responsiveness were also enhanced using both a Convolutional Neural Network (CNN)-based object detection mechanism using YOLOv8 (i.e., with 94.3% accuracy and 18.7 ms latency) and pose estimation algorithms, alongside a MediaPipe and Long Short-Term Memory (LSTM) framework for human action recognition. The developed solution was tested and validated in healthcare, with the aim to overcome some of the current challenges, such as workforce shortages, ageing populations, and the rising prevalence of chronic diseases. The CAD simulation, validation, and verification tested functions (i.e., assistive functions, interactive scenarios, and object manipulation) of the system demonstrated the robot’s adaptability and operational efficiency, achieving an 87.3% task completion success rate and over 85% grasp success rate. This approach highlights the potential use of an SLRS for healthcare assistance. Further work will be undertaken in hospitals, care homes, and rehabilitation centre environments to generate complete holistic datasets to confirm the system’s reliability and efficiency. Full article

Artificial Intelligence (AI) is transforming smart healthcare by enhancing diagnostic precision, automating clinical workflows, and enabling personalized treatment strategies. This review explores the current landscape of AI in healthcare from two key perspectives: capability types (e.g., Narrow AI and AGI) and functional architectures (e.g., Limited Memory and Theory of Mind). Based on capabilities, most AI systems today are categorized as Narrow AI, performing specific tasks such as medical image analysis and risk prediction with high accuracy. More advanced forms like General Artificial Intelligence (AGI) and Superintelligent AI remain theoretical but hold transformative potential. From a functional standpoint, Limited Memory AI dominates clinical applications by learning from historical patient data to inform decision-making. Reactive systems are used in rule-based alerts, while Theory of Mind (ToM) and Self-Aware AI remain conceptual stages for future development. This dual perspective provides a comprehensive framework to assess the maturity, impact, and future direction of AI in healthcare. It also highlights the need for ethical design, transparency, and regulation as AI systems grow more complex and autonomous, by incorporating cross-domain AI insights. Moreover, we evaluate the viability of developing AGI in regionally specific legal and regulatory frameworks, using South Korea as a case study to emphasize the limitations imposed by infrastructural preparedness and medical data governance regulations. Full article