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Quishing, a form of phishing conducted through QR codes, has emerged as a critical threat to user information security in mobile environments. Quishing attacks exploit the QR scanning workflow by opening malicious URLs in WebView and impersonating legitimate services to steal user credentials. Recent variants further evade static inspection by exposing credential-harvesting behavior only after user interaction, form submission, redirection, or page-state changes. In this paper, we propose WebView-Based Hybrid Analysis of Link and Event for On-Device QR Phishing Detection (WHALE), an On-Device multi-stage phishing detection framework based on an isolated Sandbox WebView. WHALE first loads the QR-decoded URL into the Sandbox WebView instead of directly delivering it to the User WebView, thereby separating the analysis process from the user session. In the static stage, WHALE extracts 54 features from the URL string, initial HTML, and DOM snapshot, and computes a static phishing risk score using a lightweight model. Inputs with uncertain static scores are forwarded to the dynamic stage. In the dynamic stage, WHALE inserts decoy credentials instead of real user credentials, triggers a controlled submit event, and analyzes 59 credential-flow state-transition features extracted before and after submission. The static model achieved an accuracy of 93.86%, precision of 93.08%, recall of 94.78%, and F1-score of 93.92%. The dynamic model achieved an accuracy of 0.915, precision of 0.895, recall of 0.946, specificity of 0.882, and F1-score of 0.920 on a source-group-disjoint independent test set. Real-device evaluation on a Samsung Galaxy S23 Ultra showed that WHALE maintains practical mobile overhead, with an average static internal runtime of 58.75 ms, dynamic internal runtime of 4165.42 ms, combined model inference time of 0.088 ms, and model asset size of 0.681 MB. These results demonstrate that WHALE can detect QR-based phishing threats On-Device while reducing user credential exposure through sandboxed credential-flow analysis.
Out-of-hospital community births account for 1.6% to 2% of births in the United States and are associated with fewer obstetric interventions but increased neonatal risk. Little is known about how maternity care providers' characteristics, values, and prior exposure to community birth influence attitudes toward community birth. We conducted an observational cross-sectional survey using a 40 to 43 item Research Electronic Data Capture questionnaire distributed October 2 to 30, 2024. Eligible participants ("providers") included in-hospital physicians, midwives, community birth providers, and registered nurses. The survey assessed demographics, practice characteristics, provider values, prior community birth experience, and attitudes toward community birth. Descriptive statistics were used to summarize characteristics. Group comparisons between in-hospital and community birth providers were conducted using analysis of variance and χ2 or Fisher exact tests. Associations between attitudes and provider values were evaluated using linear models with Bonferroni correction. Sixty-seven providers completed the survey (51 in hospital, 16 community based). Most respondents were female (89.6%) and White (77.6%), with a median of 7 years in practice (IQR, 3-14.5). Attitudes significantly differed by role (P =  .007) and credentials (P =  .002). In-hospital providers reported safety concerns about community birth and perceived antenatal counseling to be inadequate. Perceived patient distrust during transfer was common among both in-hospital and community-based providers (69% and 81%, respectively). After adjustment for provider role and multiple comparisons, no significant differences in personal values were noted by attitude group; however, providers with positive attitudes toward community birth were more likely to believe that patients value compassion (β = 2.3, P =  .004). Provider attitudes toward community birth appear to be shaped more by professional role and clinical experience than by differences in underlying value systems. High levels of perceived patient distrust during transfer highlight the need for interventions that strengthen compassion across maternity care settings.
Dental hygiene practice is rapidly evolving in response to emerging evidence on the oral-systemic health connection, advances in preventive technologies, and increased emphasis on individualized, minimally invasive care. A commitment to lifelong learning and continuing professional development is essential for maintaining clinical competence and integrating new scientific knowledge into practice. Biological dental hygiene has emerged as a complementary framework that emphasizes whole-body health, biocompatibility, reduction of toxic exposures, and prevention-centered care. This approach expands traditional dental hygiene practice by incorporating enhanced risk assessment, salivary diagnostics, targeted preventive strategies, as well as patient education focused on nutrition, inflammation reduction, and systemic health influences. This short report describes the principles of biological dental hygiene and its clinical application, including minimally invasive periodontal therapy, risk-based preventive protocols, and the use of biocompatible materials and adjunctive technologies. It also reviews professional development opportunities through the International Academy of Oral Medicine and Toxicology and the International Academy of Biological Dentistry and Medicine, which provide structured educational programs, ongoing professional development opportunities, and advanced credentials in biologically oriented oral health care. While these certifications do not alter licensure scope of practice, they support professional development and interdisciplinary collaboration. Biological dental hygiene offers an expanded framework for integrating oral and systemic health considerations into preventive care. Continued engagement in evidence-informed education and professional certification may enhance patient education, clinical decision-making, and overall care delivery within dental hygiene practice.
Advanced practice nursing in anesthesia (APNA) has emerged as an important workforce strategy to address global anesthetist shortages and rising surgical demand. However, the scope of practice and level of professional autonomy granted to APNAs vary substantially across healthcare systems. Existing literature has focused primarily on clinical competencies while paying less attention to the structural conditions shaping APNA roles. To examine global variation in APNA scope of practice and identify the structural determinants influencing professional autonomy across healthcare systems. A scoping review of peer-reviewed and gray literature published between 2001 and 2025 was conducted using the Arksey and O'Malley framework and reported according to the Preferred Reporting Items for Systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) guidelines. Searches were performed in PubMed, Embase, CINAHL, PsycINFO, the Cochrane Library, and selected organizational websites. Data were charted and synthesized using inductive thematic analysis. Thirty-five sources were included. Thematic synthesis identified a global spectrum of APNA autonomy ranging from independent practice to strict physician supervision. Six interrelated structural determinants shaped this variability: legislative and regulatory mechanisms, educational standards and credentials, economic incentives and reimbursement models, health system demands and access, professional power and interprofessional conflict, and macro-political forces and policy reform. Across jurisdictions, formal regulatory frameworks frequently diverged from actual clinical practice, particularly in rural and resource-constrained settings where workforce shortages expanded APNA responsibilities beyond statutory boundaries. Global variation in APNA scope of practice appears to be shaped more strongly by structural and political conditions than by clinical capability alone. Harmonized educational standards, clearer regulatory recognition, and reimbursement policies not contingent upon physician supervision may facilitate more consistent integration of APNAs within the global anesthesia workforce.
Academic programs in health informatics have been urged to align curricula with evolving workforce needs to better prepare graduates for practice. Such alignment supports workforce readiness, addresses talent shortages, and reduces onboarding burdens for employers. Although employers increasingly seek graduates who can demonstrate applied skills and competencies beyond textbook knowledge, academic programs continue to face challenges in translating workforce demand into curricular design. This Viewpoint is directed at health informatics program faculty and administrators and presents the author's perspective on a skills-first curriculum mapping approach aligned with current industry needs. The author argues that connecting program-level outcomes, course objectives, and learning activities to industry-recognized competencies strengthens workforce readiness while maintaining academic rigor. Drawing on the literature on competency-based education, workforce development, and health informatics training, this paper argues for intentional curriculum design that integrates transferable skills, stackable credentials, and stakeholder engagement. The key messages are as follows: (1) workforce demand should anchor curriculum design in health informatics programs, (2) curriculum mapping is a practical mechanism for operationalizing skills-first alignment, and (3) credential integration and continuous congruency evaluation support long-term program sustainability. This approach positions health informatics education to remain responsive, scalable, and aligned with the rapidly evolving professional landscape.
Artificial Intelligence (AI) is presently reshaping higher education in a rapid way, due to the high engagement of students with AI. The study's aim was to explore strategies driving transformation in higher education at large and particularly dental education. This article is a narrative review adopting a structured approach for literature search, study selection, and data extraction. A comprehensive search of electronic databases, including PubMed, Scopus, Google Scholar, and ScienceDirect for studies published between 2015 and 2025 was conducted. The review is discussed under the themes of transformative education, institutional readiness, including resistance to change, ethical considerations and global perspectives in health professions, and dental education. Further, transformative education explores faculty development, including micro-credentials and lifelong learning, a safe learning environment, infrastructure, and assessment. AI is well acknowledged in both health profession education and clinical practice. While GenAI has the potential to improve creativity, feedback, and collaborative learning, the issues of plagiarism, assessment validity, and authorship transparency are also discussed. AI encounters limitations in gauging psychomotor dexterity and clinical reasoning. Ethical concerns about algorithmic prejudice, data privacy, monitoring, and the deterioration of human-centered learning are also included. To conclude, transformative strategies for institutional readiness to be considered under the domains of governance and policy, curriculum integration and faculty training, academic integrity and assessment reforms, and leadership and change management to ensure proper integration of AI and to prepare competent, adaptable, and socially responsible health professionals. Maintenance of human oversight at the center of higher education is essential, and universities should treat AI as a catalyst for modernization rather than a threat.
Falls constitute a leading cause of injury-related mortality among older adults globally. Chinese short-video platforms collectively reach over 900 million users, presenting unprecedented opportunities for health education, but the quality of fall prevention content and its relationship with user engagement have not been systematically evaluated. To evaluate fall prevention video quality across major Chinese short-video platforms, identify content creator characteristics associated with higher-quality information, and examine whether user engagement metrics correlate with video quality. We conducted a cross-sectional analysis of 216 fall prevention videos from five platforms (Douyin, Kuaishou, Bilibili, Xiaohongshu, Xigua Video) during October-November 2025. Two independent medical-school graduates with formal medical education and research expertise in medical informatics assessed video quality using the modified DISCERN instrument (mDISCERN; range 5-25) and Global Quality Scale (GQS; range 1-5). Interrater agreement was quantified using both intraclass correlation coefficients (ICC) and Cohen's weighted κ. User engagement metrics were extracted and analyzed using both Pearson and Spearman correlations. Interrater reliability was excellent for mDISCERN (ICC=0.890; weighted κ=0.890) and good for GQS (ICC=0.723; weighted κ=0.722). Mean mDISCERN score was 17.61 (SD 2.87), with 48.1% achieving high quality. Uploader type demonstrated the strongest quality association (ε²=0.64): healthcare professionals substantially outperformed self-media creators (Cohen d=3.42). Platform verification strongly predicted quality (88.7% vs 9.1% high-quality; φ=0.79). Engagement metrics showed weak association with quality in this sample (Spearman ρ=0.149 for likes, explaining only 2.2% of variance), with detection power constrained by severe right-skewness and floor effects (e.g., 30.1% of videos had zero comments). Content creator credentials and platform verification effectively discriminate video quality, while engagement metrics show only weak association in this sample. These findings support platform policies prioritizing verified professional content and indicate that engagement-based metrics, despite their algorithmic prominence, do not reliably signal health information quality in this dataset.
In late 2025, the Cyberspace Administration of China released new requirements around the provision of online professional advice by users without relevant credentials, as part of broader efforts to curb misinformation. In this News and Perspectives article, JMIR Correspondent and long-time PC and consumer technology analyst Tim Bajarin reports his opinion on the potential implications of this initiative for the United States.
Robotic-assisted total knee arthroplasty (RA-TKA) has spread on the promise of greater precision, yet whether that precision improves what patients experience is unsettled. This review synthesizes evidence on the radiological precision and clinical outcomes of RA-TKA, situates its health-economic case, and defines benchmarks for emerging platforms. Structured non-systematic review of peer-reviewed literature indexed in PubMed/MEDLINE (January 2015-December 2025), with predefined eligibility criteria and a level of evidence assigned to every cited clinical study by Oxford Centre for Evidence-Based Medicine 2011 criteria. Manufacturer and institutional sources were used only where peer-reviewed data are absent, and are identified as such. RA-TKA more than halves the risk of a hip-knee-ankle deviation beyond three degrees, with the largest gains in severe deformity; between robotic platforms these differences largely disappear. Component positioning improves against manual instrumentation, though gap-balancing evidence is thin and largely single-platform. Early recovery favors robotics, but one-year scores, satisfaction, and implant survival mostly match conventional TKA (C-TKA). One retrospective series reported more manipulation under anesthesia after robotic surgery; the finding is not reproduced elsewhere and tracks a default tibial slope target. The economic case holds under bundled payment but not under French activity-based tariffs. RA-TKA delivers measurable radiological precision whose translation into durable patient benefit remains unproven at a predominantly Level III standard of evidence. Most comparative data derive from a single image-based platform and rarely extend beyond two years. Emerging platforms should be judged against defined evidentiary standards, including safety, rather than engineering credentials. Level of Evidence. V (narrative review).
This study provides a review of recent publications on different quality control (QC) techniques for radiotherapy linear accelerators (linacs). QC in radiotherapy is essential to ensure patient safety, deliver optimal quality treatments, monitor equipment performance over time and to satisfy statutory or recommended testing. Whilst conventional QC methods are still widely used and valuable, there have been advances in QC methods and approaches which aim to improve efficiency and keep pace with the rapidly advancing complexity of clinical equipment and treatment delivery methods. Existing reviews of QC concepts mainly focus on single QC techniques. There are limited reviews that explore and compare the variety of techniques to QC, which is the aim of this report. QC techniques were separated into seven domains: conventional QC, automated & manufacturer integrated QC, risk, statistical, artificial intelligence (AI), end-to-end & patient-specific QC (PSQC), external dosimetry audits & clinical trial credentialing audits. An overview of each technique with example studies from literature is presented.
In response to individual and systemic barriers hindering the timely and effective treatment of eating disorders (EDs), the Australia & New Zealand Academy for Eating Disorders (ANZAED) introduced an eating disorder credential for clinicians in June 2022. The Credential aims to enhance treatment access, quality, and outcomes. While the Credential has been well received by stakeholders, its effectiveness from the perspective of those with lived experience of an ED needs to be more fully understood. The current study aims to explore the experiences and perspectives of people living with an ED in relation to their treatment experiences provided by Credentialed Eating Disorder Clinicians (credentialed clinicians) and non-credentialed clinicians. An exploratory mixed-methods cross-sectional study was conducted involving 100 participants with personal lived experience of an ED. Participants were recruited via Australian eating disorder services and organisations, including the ANZAED and National Eating Disorders Collaboration (NEDC) membership databases, with recruitment information distributed through their email and social media platforms. Participants completed a survey with open- and closed-ended questions on their attitudes towards the Credential and experiences of treatment by a credentialed clinician or non-credentialed clinician. Descriptive statistics and Mann-Whitney U tests were used to examine differences in attitudes, treatment experiences, and helpfulness ratings between participants who had seen credentialed and non-credentialed clinicians, alongside inductive thematic analysis of open-ended survey responses. Irrespective of their own clinicians' credentialing status, participants valued the Credential; almost two thirds identified that their most helpful treatment experience was with a credentialed clinician. Three themes were generated from open-ended survey responses that explored the treatment experiences of those with lived experience of an ED: (1) Expertise, Accessibility, and Continuity of Care, (2) A Collaborative Approach, and (3) Personalised and Effective Treatment Delivered with Understanding, Compassion, and Respect. The current study adds to the ED literature by highlighting the perceived value of the ANZAED Eating Disorder Credential by individuals with lived experience. Further, it supports existing research that identifies clinician's expertise, a collaborative approach to treatment, and the provision of individualised treatment as key factors contributing to positive treatment outcomes. However, barriers to accessibility, including the cost of treatment and availability of credentialed clinicians, remain and need to be addressed for individuals to receive the full benefits of the Credential. In June 2022, the Australia & New Zealand Academy for Eating Disorders (ANZAED) introduced the ANZAED Eating Disorder Credential to the public, to improve timely access to eating disorder treatment provided by appropriately trained and experienced clinicians. The current study explores the perspectives of those with a lived experience of an eating disorder towards the Credential and their treatment experiences with credentialed and non-credentialed clinicians. Participants valued the Credential’s existence, regardless of their own clinician’s credentialing status, expressing preference to receive treatment from a credentialed clinician, placing greater trust in their advice and believing the Credential would improve health outcomes and access. Almost two thirds of participants reported that their most helpful treatment experience was with a credentialed clinician and highlighted the importance of expertise, a collaborative approach, and tailoring treatment to the individual. Barriers to accessing care, a lack of interdisciplinary collaboration, and forced or involuntary treatment were found to be key contributors to participants’ least helpful treatment experiences, pointing to a need for ongoing improvements to ensure the Credential delivers its full potential.
Automatic vehicle license plate detection and recognition has become an important component in intelligent transportation systems, traffic monitoring, and law enforcement applications. However, existing approaches for Bangladeshi license plates often rely on optical character recognition (OCR) or recognition models with a limited number of character classes, which restricts their ability to handle the complex structure and large variation of Bangla license plate components. To address these challenges, this study proposes a vehicle license plate detection and recognition (VLPDR) framework based on a cascading architecture of three YOLOv12 models. The first model detects vehicles, the second model localizes the license plate region, and the third model performs character-level recognition without relying on conventional OCR engines. The proposed recognition model incorporates 104 classes, covering a wide range of Bangladeshi license plate components, including city codes, vehicle types, and numeric digits. Two datasets consisting of 9,357 images have been used for training, validation, and testing, while an additional 150 images have been used for external validation. The license plate detection (LPD) model has achieved testing precision, recall, and mAP@50 of 0.986, 0.965, and 0.963, respectively. The license plate number recognition (LPNR) model has obtained testing precision, recall, and mAP@50 values of 0.95, 0.898, and 0.949. During external validation, the cascaded framework achieved 100% license plate detection accuracy, 95.33% full-number recognition accuracy, 98.82% character-wise mean accuracy, and 99.57% Levenshtein-based similarity accuracy. The system has also been evaluated on multiple hardware platforms, demonstrating inference times of 2311.53 ms on a CPU-based laptop and 284.31 ms on a GPU-enabled computer. These results indicate that the proposed cascaded YOLO-based framework provides an effective and practical solution for Bangladeshi license plate detection and recognition with improved class coverage and strong generalization capability.
The 2022 transition of United States Medical Licensing Examination (USMLE) Step 1 from numeric to pass/fail scoring represents a fundamental shift in neurosurgery residency applicant selection. Historically, Step 1 scores served as a key objective metric. With numeric scores no longer available, programs may place greater emphasis on alternative metrics. To the authors' knowledge, this study is the first that aimed to evaluate how predictors of neurosurgery match outcomes have shifted before and after Step 1 became pass/fail. We conducted a retrospective cohort analysis of neurosurgery residency applicant data from pre-pass/fail (Step 1 numeric) and post-pass/fail eras. Data were used from the 2023 and 2024 application cycles. Variables included demographics, USMLE Step 2 clinical knowledge (CK) scores, Step 1 pass status, research output variables, dedicated research years, postgraduate training after medical school graduation, Alpha Omega Alpha (AOA) membership, home institution status, and other academic metrics. Descriptive statistics were compared for matched and unmatched applicants within each era. Independent predictors of match success were identified through multivariable logistic regression analysis. In the pre-pass/fail era, matched applicants had higher Step 2 CK scores and more review article, neurosurgery-specific, neurosurgery-specific first-author, and total publications than unmatched applicants (p < 0.001 for all). Independent predictors of match success included Step 2 CK score and review article productivity. Research year and postgraduate training were negative predictors. In the post-pass/fail era, Step 2 CK, home institution, AOA membership, research year, neurosurgery-specific publications, and basic science publications were significant positive predictors. Review articles no longer predicted match success. The transition to pass/fail Step 1 has shifted the emphasis of neurosurgery residency applicant selection from general research productivity and review articles toward specialty-specific scholarship, home institution affiliation, AOA membership, and dedicated research experience. Step 2 CK has remained a consistent predictor across eras.
Spine centers are common, but no standardized regulations govern their designation. Existing certifications are issued by multiple independent organizations and are not necessarily equivalent, while many centers remain non-accredited. Consequently, centers may vary in qualifications, quality of care, and services. This study examined and compared the defining characteristics of spine centers in Northeast America. A total of 194 spine centers were identified and compared based on accreditation, services, provider numbers, and proximity to metropolitan areas. Accreditation requirements from The Joint Commission (TJC), Det Norske Veritas (DNV), Aetna, and Blue Cross Blue Shield (BCBS) were analyzed. While substantial overlap existed, Aetna and BCBS largely built upon TJC standards, whereas DNV requirements differed, and exact criteria varied across organizations. Overall, 56% of centers were accredited. Compared with non-accredited centers, accredited centers more frequently employed neurosurgeons, offered multidisciplinary care, and were affiliated with academic medical centers. Logistic regression demonstrated that employment of neurosurgeons and academic affiliation independently predicted accreditation. Accredited centers also tended to be closer to metropolitan areas and employed more providers. However, rates of non-surgical treatment, minimally invasive surgery, and physical therapy services were similar regardless of accreditation status. Although accredited centers reported certain characteristics at higher rates, the variability between accreditation requirements and similarity between accredited and non-accredited centers could confuse prospective patients. While this study provides a preliminary profile of Northeast spine centers, our findings reinforce the need for standardized guidelines for spine center status.
This case report details the diagnostic, therapeutic, and aeromedical trajectory of a 58-yr-old pilot diagnosed with squamous cell carcinoma exhibiting perineural invasion and orbital floor involvement with treatment goal of return to flight. The malignancy presented with insidious symptoms of fascial swelling, numbness, and tingling, complicated by initial diagnostic anchoring bias. The patient had a relevant past medical history of squamous and basal cell carcinomas, including a Mohs micrographic surgery for a lesion on the left nares 10 yr prior. Treatment necessitated a total maxillectomy with multiple skin flaps, and orbital floor reconstruction initially using a titanium implant and later an autologous scapular bone graft. Postoperative management addressed complex ocular manifestations, including mechanical diplopia and inferior rectus muscle dysfunction, alongside the challenges caused by multiple skin-flap failures. From an aeromedical perspective, the case highlights the rigorous standards of the Federal Aviation Administration for First-Class medical certification, focusing on binocular fusion, visual acuity, and auditory thresholds. The report outlines the regulatory pathway for Special Issuance and the eventual return to flight duty, emphasizing the balance between aggressive oncological control and the preservation of critical sensory functions required for aviation safety. This case provides an example of a structured framework for managing high-stakes professional requirements in the context of advanced midfacial malignancy and complex reconstructive surgery. Krebsbach SK, Fredricks TR. Ocular management and aeromedical certification of maxillary squamous cell carcinoma. Aerosp Med Hum Perform. 2026; 97(8):644-647.
Open-source, mid-scale large language models (LLMs) have emerged as scalable, privacy-preserving alternatives to ultra-large foundation models (eg, GPT-4) in health care systems. Techniques such as retrieval-augmented generation (RAG) enable sub-100-billion-parameter models to address highly specialized medical domains such as anesthesiology. However, studies evaluating RAG architectures on complex medical examinations remain scarce, highlighting the need for rigorous benchmarking to bridge the gap between raw parametric knowledge and clinically relevant application. This study aimed to systematically evaluate RAG pipelines for answering anesthesiology board-style questions, quantify the effects of key design choices including hyperparameter settings, embedding models, source complexity, and chunking strategies, and compare the performance of reasoning-oriented models with that of conventional LLMs. We conducted large-scale benchmarking using American Board of Anesthesiology-style multiple-choice questions to compare multiple RAG-enabled configurations with matched standalone LLM baselines. Configurations were first optimized on a 46-item diagnostic set and then validated on a 350-item corpus. Additional experiments on three 100-question subsets derived from the 350-item corpus were used to assess the effects of source selection, source complexity, information density, and chunking strategy on answer accuracy. Models including Llama-3-8B-Instruct, Llama-3.1-8B-Instruct, Llama-3.2-3B-Instruct, Llama-3.3-70B-Instruct, Qwen2.5-7B and Qwen2.5-72B, and Qwen3-8B and Qwen3-32B reasoning models were evaluated under this framework. Self-reflective RAG (self-RAG) with adaptive retrieval techniques was also implemented and evaluated. Cochran Q and McNemar tests were used to assess performance differences across configurations and model pairs. The RAG framework increased the number of correct answers. System stability peaked under highly deterministic sampling configurations (temperature=0.1, top-p [nucleus sampling]=0.1). High-capacity general-text embeddings and applying context-preserving semantic chunking further improved accuracy. Standard RAG provided only modest gains over nonaugmented baselines, improving accuracy from 50.29% to 56.57%, and self-RAG yielded similarly limited gains of up to 4.85 percentage points. Overall, the Qwen family outperformed the Llama series. The 32-billion-parameter reasoning model Qwen-3-32B achieved an 89% correct ratio under complex distractor-heavy retrieval conditions and up to 96% with direct context, significantly outperforming the much larger 72-billion-parameter conventional model Qwen-2.5-72B-Instruct (84%). Smaller reasoning models also showed greater robustness to noise or suboptimal retrieved documents than larger conventional LLMs. Within the Llama family, increasing parameter size to 70 billion did not produce proportional performance gains on this benchmark. RAG-based LLM systems improved performance on anesthesiology board-style questions, but gains depended strongly on retrieval design. Careful optimization of retrieval settings, embeddings, and chunking strategies improved robustness and answer accuracy. Reasoning-oriented models demonstrated that multistep reasoning can, in some settings, compensate for larger parameter scale. These findings provide a methodological foundation for developing locally deployable LLM systems for anesthesiology education within structured examination settings.
Point-of-care ultrasound (POCUS) is integral to emergency medicine, offering rapid, radiation-free diagnostic information across a wide range of clinical scenarios. However, widespread adoption has exposed significant challenges related to standardization of documentation, quality assurance (QA), image storage, credentialing, and billing. Without a reliable, centralized management system, there is an increased risk of inefficiencies, data loss, missed billing opportunities, and potentially worse patient outcomes. This implementation report describes the planning, deployment, and early outcomes of integrating a middleware, specifically Fujifilm's Synapse Synchronicity, into our institution's POCUS workflow. The objective is to evaluate how middleware integration affects documentation, QA, education, compliance, and billing, and to provide practical insights for institutions considering similar system-level transitions. The integration of a middleware within our institutional Emergency Department has reshaped the clinical, educational, technical, and financial aspects of POCUS. By consolidating a fragmented workflow into a single, cohesive platform, the department has created a scalable, efficient, and high-performing infrastructure. Despite these benefits, substantial challenges emerged, including increased workflow complexity, system delay, login and access barriers, ultrasound image assignment delays, and dependence on reliable network connectivity. Middleware integration through Synapse Synchronicity fundamentally restructured the Emergency Department's POCUS workflow, showing how integrating a centralized ultrasound workflow platform can improve patient care, provider education, and hospital operations. The lessons learned during implementation can serve as a roadmap for other institutions seeking to enhance their POCUS operations while ensuring quality, compliance, and patient-centered care.
This article examines the life, work and contributions of Jerry Ann Johnson, who was president of the American Occupational Therapy Association from 1973-78 during a pivotal time of Association reorganization. Specifically, for the first time, all fifty states had functioning occupational therapy associations as well as Puerto Rico and the District of Columbia. Johnson addressed issues that included professionalism versus semi-professionalism, characteristics of a profession and leadership, credentialing processes including licensure and continued competency, community and private practice, and the need for graduate education and research. Over her career, her prolific writing offers profession historical knowledge during the growth of occupational therapy in the 1970's and1980's.
Charge nurses are pivotal frontline leaders in acute care, yet many assume the role without formal preparation, particularly in multicultural health systems. Confidence in leadership, clinical judgment, and communication is central to safe and effective charge nurse practice, but evidence from Gulf-region tertiary hospitals remains limited. To evaluate the effectiveness of a structured Charge Nurse Development Program (CNDP) in improving nurses' confidence in leadership, clinical, and professional responsibilities within a large multinational tertiary hospital in the United Arab Emirates. A quantitative quasi-experimental pre-post design was conducted with 103 nominated registered nurses working in inpatient and critical care units. The three-phase CNDP combined self-directed e-learning, a didactic workshop with simulation and case-based activities, and three supervised charge nurse shadowing shifts, guided by Bandura's Self-Efficacy Theory, adult learning principles, and experiential learning. Confidence was measured before and 1 week after the program using the 21-item Confidence in Managing Challenging Situations Scale (CMCS). Data were analyzed using paired-samples t-tests, Welch's ANOVA, and multiple linear regression; effect sizes and internal consistency (Cronbach's α) were reported. Confidence improved significantly across all 21 items and both subscales. Leadership & Ethical Practice increased from 27.48 ± 5.31 to 32.95 ± 4.05, and Clinical & Communication Confidence from 36.26 ± 7.01 to 43.56 ± 5.43; total confidence rose from 63.74 ± 11.74 to 76.51 ± 9.26 (all p < 0.001, d ≈ 0.82-0.87). Cronbach's α for the Confidence Scale was 0.963. Baseline differences by credential favored charge nurses, but post-intervention scores no longer differed significantly. No meaningful differences were found across nationality, age, qualification, years of experience, or unit, and regression analyses showed no consistent demographic predictors of change. The CNDP was associated with educationally meaningful improvements in nurses' self-reported leadership and clinical confidence in a highly multicultural workforce. These findings suggest that structured, theory-informed charge nurse development may support perceived readiness for frontline leadership responsibilities. Further controlled and longitudinal studies using objective behavioral, clinical, and organizational outcomes are needed to determine whether confidence gains translate into sustained practice change.