Sheep production in the U.S. spans diverse geographies and management practices, which are traditionally classified by climate alone. By combining information on climatic conditions and their management practices, we assigned groups of flocks to distinct eco-management clusters that characterized their shared production environments. Ninety-seven producers, whose geographically distributed flocks represented five breeds enrolled in the National Sheep Improvement Program, completed an online management survey. Breeds included Katahdin (n = 50), Polypay (n = 21), Suffolk (n = 13), Rambouillet (n = 8), and Targhee (n = 5). The questionnaire considered parasite control, lambing and udder health management, culling strategies, feeding methods, and climate mitigation practices. We characterized the climates at producer locations based on elevation, seasonal precipitation, soil moisture, and the Comprehensive Climate Index (CCI). The CCI integrated ambient temperature, humidity, wind speed, and solar radiation to reflect thermal stress. Clusters were first formed based on climate or management data via Principal Component Analysis and Multiple Correspondence Analysis, respectively. Both sources of information were then combined to form eco-management clusters using Factorial Analysis of Mixed Data. Cluster quality was assessed using silhouette widths. Differences among clustering approaches were tested with chi-square cross-tabulations and permutation tests. Flock assignments to climate and to management clusters were, statistically, independent within breeds (P > 0.16). Flock allocations to eco-management and management clusters, however, typically aligned (P ≤ 0.01), although less so in Targhee-Rambouillet (P = 0.18). Such was also the case for climate-based clusters (P ≤ 0.04) except in Suffolk (P = 0.50). Overall, coupling of climate and management appeared weakest in Suffolk flocks. Across eco-management clusters, differences in management practices were found for 26 husbandry practices in Katahdin, 21 in Polypay, 7 in Suffolk, and 5 jointly in Rambouillet and Targhee (P < 0.05). Although climate influenced husbandry strategies, producers often adopted unique management practices in response to local conditions. Collectively, climate and management defined distinct yet complementary drivers of environmental heterogeneity, supporting the concept of eco-management clustering as a holistic approach to characterizing the production environments of sheep flocks. Sheep producers across the United States manage animals in a wide range of environmental conditions, including different climates with varying forage availabilities and parasite challenges. Traditionally, production environments are defined based on geographic regions. However, that approach overlooks the distinct strategies producers use to accommodate their local conditions. In this study, we used a holistic method combining climate data with producer reported management practices to define “eco-management clusters”, groups of flocks experiencing similar environmental pressures and adopting similar management styles. Using responses from a survey of sheep producers enrolled in the National Sheep Improvement Program, we characterized differences in flock sizes, lambing systems, and feeding and parasite control strategies. Climatic conditions were defined based on a flock’s location. Although climate data alone explained much of the variation in environments, management data helped delineate differences in practices used in flocks located in the same ecoregion. For example, Katahdin producers employed various parasite control strategies while Polypay producers implemented a mix of lambing and feeding systems even within similar climates. By defining production environments based on eco-management clusters, management and selection strategies can be tailored to match animal genetics with the conditions producers face, ultimately improving animal performance and climatic resilience.
The global population is aging rapidly, straining health care and social systems. Amid digital transformation, older adults face pronounced obstacles to participating in and benefiting from health communication. Prior syntheses emphasized technology adoption or clinical effectiveness, and health communication reviews focused on formal or home-based care. How older adults experience digital health communication as an everyday, relational process in community contexts and how trust and responsibility take shape remain underexplored. This study aimed to synthesize the experiences of older adults engaging in digital health communication in community contexts. We searched PubMed, CINAHL, Embase, PsycINFO, Scopus, ProQuest Health & Medical Collection, Web of Science Core Collection, CNKI, and Wanfang from inception to June 2026. Qualitative and mixed methods studies on the digital health communication experiences of community-dwelling older adults (aged ≥50 y) were included; purely quantitative studies were excluded. Two researchers independently screened records, appraised the studies using the CASP (Critical Appraisal Skills Programme) tool, and extracted qualitative data. Findings were synthesized using the Noblit and Hare meta-ethnography, and confidence was assessed using the GRADE-CERQual (Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative Research) approach. The review was registered with PROSPERO and reported following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), PRISMA-S (PRISMA Extension for Reporting Literature Searches in Systematic Reviews), and ENTREQ (Enhancing Transparency in Reporting the Synthesis of Qualitative Research). The integration of 14 studies across 8 countries yielded 4 themes. Older adults' objectives in community digital health communication encompass obtaining or sharing health information, maintaining health, and learning technology to avoid falling behind. Engagement enhanced health management, improved access to health care services, knowledge, and skills, and increased social participation. Trust was built primarily on patient-provider relationships and authoritative platforms, while accountability was distributed across individuals, families, health care providers, and communities, despite imbalances such as technological dependency and difficulty verifying information. Adaptation to technology was dual in nature: social support, patient-provider trust, and technological affinity were key drivers, whereas insufficient digital literacy, technology anxiety, cost constraints, physiological limitations, and privacy concerns constituted significant barriers. This meta-ethnography treats community-based digital health communication as a communicative practice in its own right. It reframes the community not as a setting in which communication occurs but as a determinant of whether it works and characterizes engagement as an evolving negotiation of motivation, trust, and responsibility. Findings argue for moving beyond efficiency-oriented service delivery toward building community capacity and supporting older adults' autonomy and digital health literacy. Twelve out of 14 studies were of moderate quality, and eligibility was limited to Chinese- or English-language abstracts, which may limit representativeness.
Background and objectives Preconception care (PCC) comprises a set of biomedical, behavioural, and social interventions provided before conception to improve maternal and neonatal outcomes. PCC remains a critical missing link in the continuum of reproductive healthcare in India. This study assessed public health-system preparedness and community perception related to PCC service delivery in Maharashtra. Methods A mixed-method, pre-intervention situational analysis was conducted to assess public health-system preparedness and community perceptions regarding PCC service delivery in selected districts of Maharashtra, India. Using stratified purposive sampling, 31 public health facilities were assessed using a facility checklist adapted from World Health Organization (WHO) SARA (Service Availability and Readiness Assessment) domains and mapped to WHO health system building blocks. Additionally, 143 key informant interviews (KIIs) were conducted among healthcare providers, and 20 focus group discussions (FGDs) were conducted with newly married couples and mothers-in-law across rural (tribal and non-tribal) and urban (slum and non-slum) settings. Qualitative findings were thematically analysed using the social ecological model. Both models were triangulated using a COM-B (capacity, opportunity, motivation→ behaviour) framework. Results All assessed facilities had basic infrastructure and manpower; however, PCC services were largely restricted to anaemia prophylaxis and family planning commodities. Major systemic challenges included the absence of PCC-specific guidelines, irregular supply of essential medicines and diagnostics, limited health management and information systems (HMIS) integration, weak policy coordination, inadequate human resources, and referral pathways. From the community perspective, PCC awareness was negligible; misconceptions linked it to infertility care, and family gatekeeping limited women's autonomy. Gender norms and poor male involvement further constrained service uptake. Interpretation and conclusions Although Maharashtra has favourable policy support for PCC through the Mission Vatsalya initiative, significant gaps persist in the health system's readiness and community awareness. Developing PCC-specific operational and technical guidelines, capacity building, provision of information, and education material, PCC indicator integration in HMIS, and demand generation, coupled with male involvement, can optimise PCC uptake and improve PCC service utilisation.
Background Document control is a core requirement of laboratory quality management and accreditation, including under the College of American Pathologists (CAP), International Organization for Standardization (ISO) 17025, ISO 15189, the Association for the Advancement of Blood & Biotherapies (AABB), and the Central Board for Accreditation of Healthcare Institutions (CBAHI). Before 2024, many Saudi laboratories relied on paper-based systems or imported platforms that lacked Arabic-language functionality, local hosting, and explicit alignment with Saudi regulatory and governance requirements. Objective To describe the development, standards-based internal validation, and early multisite implementation of the Makeen Document Control System (Makeen DCS), a Saudi-built laboratory document control platform designed for accreditation-oriented use in Saudi Arabia, and to assess early feasibility and user-perceived acceptability rather than comparative effectiveness. Methods This descriptive implementation and feasibility study was conducted from October 2024 to January 2026. System requirements were derived from CAP, ISO 17025, ISO 15189:2022, AABB, CBAHI, FDA 21 CFR Part 11, and Saudi Personal Data Protection Law (PDPL) requirements and translated into software specifications. Development followed staged requirements definition, prototyping, workflow refinement, internal validation, and pilot deployment. Internal validation used 126 structured test cases across user access, document creation and upload, approval workflow, version control, retrieval, audit trail behavior, and administrative functions. Early implementation was undertaken in seven purposively selected pioneer laboratory sites. User feedback was collected through an internally developed implementation survey completed by eight participants from pilot sites. Results The Makeen DCS provided end-to-end document lifecycle management, role-based access control, bilingual Arabic-English interfaces, dynamic master document lists, searchable retrieval, audit-oriented reporting, and a personnel-documentation module. The system supported both Saudi-hosted cloud deployment and on-premises implementation. Functional alignment was mapped against selected CAP, ISO 17025, ISO 15189:2022, CBAHI, AABB, FDA Part 11, and PDPL requirements. Among 126 validation test cases, 109/126 (86.5%) passed on first execution, and 17/126 (13.5%) failed initially; all failed items were corrected and retested, resulting in a final pass rate of 100% (126/126). Early deployment was achieved across seven diverse sites, of which six were fully active, and one remained partially implemented by study cut-off. Median active users across sites were 80 (range: 30-200), median configured departments were 10 (range: 5-15), and median migrated or newly created controlled documents were 76 (range: 10-274) across six sites with available data. User feedback was favorable, with a mean satisfaction score of 9/10, 7/8 (87.5%) respondents willing to recommend the platform, and 8/8 (100.0%) perceiving improved inspection readiness and reduced manual or paper-based workload. Conclusions Makeen DCS was feasible as a Saudi-built/bilingual/locally hosted lab platform for accreditation workflows. Internal validation, pilot use, and small-sample feedback show readiness/acceptability, not operational effectiveness; independent longitudinal evaluation is needed.
Hereditary angioedema is a rare but potentially life-threatening disorder in which outcomes depend not only on correct diagnosis and effective medicines, but also on how health systems organize referral, laboratory confirmation, emergency pathways, reimbursement, home treatment, and long-term follow-up. Selected health systems in the Balkan Peninsula area provide a particularly informative setting for health-system comparison because neighboring countries with active hereditary angioedema expertise differ substantially in rare-disease governance, registry maturity, diagnostic infrastructure, treatment coverage, and patient-organization capacity. This Policy and Practice Review synthesizes international guidance, published regional literature, comparative country information from the Balkan Experts in Angioedema: Consensus and Ongoing Navigation (BEACON) initiative, and advocacy-informed implementation insights to assess current care delivery in Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Greece, Romania, Serbia, Slovenia, and Türkiye. Across the region, the most consistent problems are prolonged diagnostic delay, unequal access to complement and genetic testing, approved-but-not-reimbursed modern therapies, hospital-only access to rescue medication, uneven use of home treatment and self-administration, incomplete emergency preparedness, and variable registry and advocacy infrastructure. Countries with stronger alignment between policy frameworks, specialist centers, registries, reimbursement pathways, and patient organizations appear better positioned to deliver guideline-concordant care, whereas fragmentation at any point in the care pathway reduces the practical value of therapeutic advances. The review argues that the main barriers to equitable hereditary angioedema care across the included health systems are now predominantly regulatory, financing, organizational, and educational rather than scientific. We therefore propose actionable recommendations for ministries and payers, specialist centers and professional societies, emergency-care systems, registry stakeholders, and patient organizations, with the goal of converting regional heterogeneity into a structured quality-improvement agenda.
Enhanced recovery after surgery protocols have shortened orthopedic hospital stays but have shifted rehabilitation and safety-monitoring tasks to patients and families after discharge. In this study, AI refers to patient-facing digital systems for orthopedic transitional care, including large language model chatbots, computer vision or platform-based monitoring tools, and wearable sensor-enabled systems for education, rehabilitation guidance, motion correction, and risk alerts. However, patient-reported preferences for different AI-supported functions across the hospital-to-home transition remain underexplored. This study aimed to map the evolution of care needs from hospital to home recovery and to identify specific preferences and factors associated with the willingness to use AI systems in orthopedic transitional care. We conducted a multicenter cross-sectional survey among patients recovering from orthopedic surgery in 33 Guangdong hospitals, China. Of the 860 submitted questionnaires, 752 responses were included after prespecified quality control, including exclusion of responses completed in 180 seconds or less based on pilot-informed screening. Participants rated standardized function-based AI descriptions rather than a specific prototype or live tool. The data covered demographic and clinical characteristics, task priorities across care phases, perceived transitional care challenges, and stated willingness to use AI. The survey was informed by the technology acceptance model, although perceived usefulness, perceived ease of use, and attitude toward use were not directly measured. Exploratory factor analysis was used to examine perceived challenges. Descriptive mapping summarized care needs and AI function preferences, and multivariable logistic regression explored factors associated with willingness. Most respondents reported a willingness to use AI (604/752, 80.3%). Care priorities varied by phase: inpatient priorities were more often related to information acquisition and care instruction, whereas home-stage priorities more often involved functional safety, rehabilitation guidance, motion correction, and risk alerts. Exploratory factor analysis identified 3 perceived challenge dimensions: home rehabilitation self-management barriers, lack of professional support, and symptom uncertainty. In adjusted exploratory analysis, willingness to use AI was associated with older age (adjusted odds ratio [aOR] 1.02, 95% CI 1.00-1.03), comorbidities (aOR 1.72, 95% CI 1.09-2.69), later rehabilitation stage (aOR 1.28, 95% CI 1.01-1.62), and urban residence (aOR 1.85, 95% CI 1.14-3.01). Unmarried, divorced, or widowed status was associated with lower willingness than married status (aOR 0.59, 95% CI 0.39-0.89). Physical disability and self-care ability were not independently associated with willingness after adjustment. In this hospital-based convenience sample, most respondents were willing to use AI, and their stated priorities shifted from information support during hospitalization to functional safety and rehabilitation support after discharge. The associated factors should be interpreted as exploratory associations rather than causal determinants. Because participants evaluated function-based AI descriptions rather than actual AI tools, these findings can inform future prototype development and real-world evaluation, particularly around usability, trust, privacy, digital accessibility, and clinician oversight.
Advances in Earth observation (EO) remote sensing technologies have delivered a range of aerosol and trace gas pollution data with ever-improving spatial and temporal resolution, significantly benefitting assessments of global air quality (AQ). Furthermore, the application of data synthesis techniques incorporating satellite EO with other information sources has improved the availability of satellite-derived estimates of pollutant exposure at local to global scales. These data have been applied to address a diversity of use cases in AQ monitoring and public health, from long-term trend tracking, exposure assessment, and epidemiological analysis to short-term emissions identification and early warning. Successful application of satellite EO to address AQ and AQ-related health problems requires an alignment between (1) the technical capabilities of satellite data to provide relevant information, (2) a defined case for using this information to address a particular need, and (3) the human capacity, computational resources, operational plans, and policy and governance frameworks to implement a solution and take action, and to sustain the solution for as long as the need remains. Only when there is substantial alignment across all these factors can satellite EO information be effectively translated into public health benefits. This paper surveys applications of satellite EO to AQ assessment and AQ-related health management globally, synthesizing key commonalities into recommendations for how satellite EO can effectively support health needs. We also identify gaps in current satellite EO capabilities, use-case applications, and feasibility factors where future research and investment could reduce barriers to increased application of satellite EO to address pressing public health concerns related to AQ worldwide.Implications: This paper summarizes insights collected through the Group on Earth Observations (GEO) Health Community of Practice Air Quality and Respiratory Health Work Group on the current state and gaps in the use of satellite EO to support air quality and related health decision-making globally. We synthesize these insights into general recommendations for how satellite EO capabilities, use cases, and feasibility considerations can be aligned towards effective use of satellite EO data for air quality and related health effects. We also identify barriers and gaps in current capabilities, uses, and capacities, making recommendations for how these might be addressed.
Health coaching is the process of using conversation, clinical strategies and interventions to engage clients in setting goals and identifying strategies to facilitate behaviour changes that allow clients to better self-manage their health. Health coaching is a new and growing industry in the USA. With increasing budgetary strain and limited resources, understanding the financial outcomes of adding health coaching is critical. The objective of this review was to examine what is known in the literature about health coaching and cost analyses since 2017, building and expanding on the findings of a prior review. This review seeks to identify existing and persisting gaps in the literature and suggest future directions for cost analyses in health coaching interventions. Full-text publications, excluding editorials and opinion pieces, included in this scoping review were published in 2017 or later. Included publications had to be written in English and align with the definition of health coaching described by the National Board for Health and Wellness Coaching. They also had to contain some measurement of cost or cost analysis, indicated by the mention of cost or a related synonym in the methods section. PubMed, Embase and the Health Medicine Collection were searched from 1 January 2017 to 7 January 2025 for peer-reviewed research, with an additional search on 5 May 2026 to reflect any additions to the literature since the initial submission. The scoping review was structured according to the enhancement by Levac et al to Arksey and O'Malley's framework for conducting scoping reviews.Information related to the cost analysis methodology and results was extracted from each of the included articles. Trends across articles were summarised based on key characteristics of the study and the main questions being addressed in the review. Only two studies found statistically significant effects on healthcare costs from health coaching: one found an increase in costs and the other found a decrease. Only one study found health coaching to be cost-effective, with another two studies finding it to be not cost-effective or cost-effective only if the coaching costs less than a certain amount or has an assumed efficacy threshold. Overall, the cost analyses for health coaching lacked transparency in methodology reporting and had a wide variety of methodology and costs included. Synthesis of results was not possible due to inter-study heterogeneity. As there is a move towards standardisation and credentialing of health coaches, there needs to be a similar move towards the standardisation of their cost analyses. This scoping review found mixed, limited evidence regarding the cost outcomes and cost-effectiveness of health coaching. Future research should conduct cost analyses of health coaching interventions according to the structured framework listed in the Consolidated Health Economic Evaluation Reporting Standards, with greater transparency of methods, longer-term results and greater generalisability of results to other geographic locations and health conditions. Cost analysis of health coaching remains an urgent area for standardised and rigorous analysis to better understand the financial implications of adding health coaching to an institution.
Pneumonia is a common infectious disease, and antibiotic treatment in hospitalized patients must balance efficacy, safety, and resistance risk. However, antibiotic selection and dose adjustment still rely heavily on clinician experience. Although large language models (LLMs) are promising for clinical reasoning, their direct use for antibiotic selection and dose recommendation is limited by hallucinations and weak adherence to clinical constraints. This study aimed to develop and externally validate a constrained LLM-based clinical decision support pipeline for antibiotic selection and dose recommendation in hospitalized patients with pneumonia. We conducted a multicenter retrospective study using electronic health record narratives, antibiotic orders, and laboratory indicators of hepatic and renal function from 331 hospitalized patients with pneumonia from 2 hospitals in China. The development cohort included 233 patients, and the external validation cohort included 98 patients. The pipeline integrated dual-branch retrieval (similar-case vector retrieval plus guideline-based knowledge graph retrieval), clinician-defined rule constraints, and hybrid-context reasoning. DeepSeek-V3, GLM-4.6, and GPT-4o were evaluated using F1-score and Jaccard accuracy. On the internal test set, the full pipeline using DeepSeek-V3 achieved the best performance, with an F1-score of 0.8110 (95% CI 0.7371-0.8762) and Jaccard accuracy of 0.7624 (95% CI 0.6810-0.8386) for antibiotic selection and an F1-score of 0.7538 (95% CI 0.6671-0.8329) and Jaccard accuracy of 0.7076 (95% CI 0.6145-0.7938) for joint antibiotic selection plus dosing recommendation. On the external validation set, performance remained high, with an F1-score of 0.8605 (95% CI 0.7891-0.9252) and Jaccard accuracy of 0.8571 (95% CI 0.7857-0.9184) for antibiotic selection, and an F1-score of 0.8503 (95% CI 0.7789-0.9150) and Jaccard accuracy of 0.8469 (95% CI 0.7755-0.9133) for antibiotic selection plus dosing recommendation. The system also provided traceable evidence and rule trigger information to support clinician review. A constrained, retrieval-augmented LLM pipeline improved the consistency and interpretability of antibiotic selection and dose recommendation for hospitalized patients with pneumonia and provided preliminary evidence of cross-site generalizability.
Efficient patient flow management is a key factor for optimizing workflows in cost-intensive hospital units such as operating rooms. While existing prediction models can accurately estimate surgical durations, uncertainties in patient transport and availability of resources continue to affect daily schedules. Real-time location systems offer the potential to address this gap by providing information on patient and device locations. However, commercially available solutions are often costly and closed by providers. In this work, we present a scalable, research-oriented real-time location system, designed for low-power and low-cost deployment in hospital environments. Our system uses Bluetooth Low Energy beacons for device tracking and OpenThread as a transport layer to a database. A custom localization algorithm enables room-level assignment and triangulation-based localization in terms of coordinates. This setup is designed for low-power and low-cost deployment for research purposes. Preliminary results demonstrate the feasibility of the proposed network for room-level assignment and position estimation of beacons while revealing notable variability in accuracy. Triangulation-based localization achieved a mean positioning error of 3.53 m, while room-level assignment showed error rates ranging from 0 to 40%, reflecting typical RSSI (Received Signal Strength Indicator) effects such as shadowing and signal reflections. The presented system provides an open, standards-based foundation for future improvements, including latency analysis, reliability assessments, advanced filtering methods and latest ranging techniques and represents a promising approach for adaptive patient flow management and clinical workflow optimization.
Digital platforms have become important channels for public health risk information and everyday health decision-making. Misleading risk information may distort public risk cognition, weaken trust in regulatory systems, and reshape protective behavioral intentions. Grounded in Protection Motivation Theory, this study examined tech-fearmongering food production short videos as a case of misleading health risk information in platform environments. A scenario-based experimental design was used with 487 valid responses from Chinese internet users. Single-mediator and parallel multiple mediator models were estimated using PROCESS Model 4 with 5,000 bootstrap resamples to test the mediating roles of health threat appraisal, negative emotions, and trust erosion. Cognitive, affective, and social trust pathways all contributed to the mechanism linking misleading risk information to public health decision-making. In the parallel mediation model, health threat appraisal and trust erosion showed unique significant indirect effects on public risk cognition, while health threat appraisal was the dominant unique mediator for protective behavioral intention. Tech-fearmongering food production short videos can influence public health decision-making through health threat appraisal, negative emotions, and trust erosion. Digital health risk information governance should address emotional reactions and trust erosion in addition to cognitive threat appraisal, with implications for platform governance, health risk communication, and public health information quality control.
Coagulopathy is a common complication in patients with sepsis, ranging from subclinical coagulation activation only seen in laboratory values to disseminated intravascular coagulation (DIC). Over the past 25 years, several scoring systems have been developed to diagnose coagulopathy and DIC in critically ill patients. However, the presence of multiple overlapping definitions, diagnostic criteria and numerous scoring systems adds complexity and poses challenges for clinical decision-making. This scoping review aims to systematically map how coagulopathy and DIC in adult patients with sepsis are defined, diagnosed and managed, and to summarise risk factors and reported clinical outcomes. Knowledge gaps will be identified to inform future research and clinical practice. Eligible studies will include original clinical research of any design published from 1 January 1996 onwards reporting on coagulopathy or DIC in adult patients (≥ 18 years) with sepsis. Non-original articles (reviews, opinion pieces, editorials, guidelines, case reports, consensus statements) and conference abstracts will be excluded. We will only include studies published in English. Searches will be conducted in PubMed, EMBASE, Web of Science and CENTRAL, and supplemented by reference list screening. Two reviewers will independently screen abstracts and full texts, and extract data in duplicate using a piloted extraction form. In case of disagreement, a third senior reviewer will adjudicate and make the final decision on study inclusion. Extracted information will include study characteristics, population details, diagnostic approaches, frequency of coagulopathy, management strategies and clinical outcomes, as well as contextual factors such as hospital settings and geographical origin. Results will be presented using descriptive statistics, tables and narrative summaries. A critical appraisal of the quality of the included studies will be conducted. This scoping review will provide a comprehensive overview of definitions, diagnostic methods, management patterns and reported outcomes of coagulopathy and DIC in adult patients with sepsis. The findings will clarify the current practice variation, highlight knowledge gaps and areas of uncertainty, and guide priorities for future research and clinical decision-making.
Balancing cognitive load and clinical psychomotor skills within a limited curriculum time remains a core challenge in dental education. Faced with new healthcare demands driven by an aging population, dental education systems in both China and Japan require essential reforms. While current cross-national comparative studies mainly focus on macro-policy levels, introducing an objective educational model helps systematically analyze the core logical differences in micro-level pedagogical implementation and cognitive load management strategies. This study aims to examine differences in the distribution of 4C/ID components across Chinese and Japanese dental curricula, the localized strategies each country employs to refine cognitive load in dental education, and the feasibility of using the 4C/ID model as a retrospective curricular diagnostic tool to guide dental education reform. This study used a retrospective comparative case study design, analyzing comprehensive undergraduate syllabi and clinical practicum documents from Zhejiang Chinese Medical University (ZCMU, China) and Okayama University (OU, Japan). Using the Four-Component Instructional Design (4C/ID) model, all courses were mapped into four categories: authentic learning tasks (C1, clinical practice or simulation), supportive information (C2, subclassified into C2a: dental-specific theory and C2b: general/medical theory), procedural information (C3, instructor demonstrations), and part-task practice (C4, skill repetition). By combining semantic frequency analysis with the review of key pedagogical cases, this study assessed the instructional priorities of both countries. Both curricula prioritize authentic learning tasks (C1) as a foundational means to foster professional competency, but differ in their structural approaches to modulating students' cognitive load. Relying on a broad medical foundation, ZCMU front-loads general medical theory (C2b: 19.9%) while delaying dental-specific theory (C2a: 10.9%), concentrates clinical immersion in the last year (C1: 61.0%), and has limited skill training (C3+C4: 8.2%). In contrast, OU (C1: 39.7%) exhibits a longitudinal integration of C2a (15.9%) and C2b (24.3%) throughout the program, while dedicating considerably more hours to demonstrations and skill repetition (C3+C4: 20.1%). Analyzing the curriculum with the 4C/ID model offers valuable empirical insights that inform global dental education reform. To address the comorbidity challenges of a super-aged society, future dental reforms might incorporate lessons from Japanese and Chinese experiences by combining detailed theoretical scaffolding (C2) with comprehensive medical diagnostic reasoning to potentially manage cognitive load. Additionally, utilizing advanced digital simulation technology to initially separate procedural information (C3) and part-task practice (C4) from authentic learning tasks (C1) may offer a practical method to balance theoretical understanding with the development of complex psychomotor skills.
As global populations age, nutrition management is important for healthy aging. Digital technologies, including mobile applications, web-based platforms, messaging tools, and artificial intelligence (AI)-enabled systems, are used in personalized nutrition interventions. However, evidence on their characteristics, effectiveness, and user experiences remains limited. This scoping review examined technology-based personalized nutrition interventions for older adults. This review followed the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. PubMed, Embase, and Web of Science were searched for studies published from January 1, 2010, to June 30, 2026. Among 2,727 records, 2,044 were screened after duplicate removal, 28 full-text articles were assessed, and 13 articles representing 12 studies were included. Technologies included mobile, messaging, web-based, information and communications technology, tablet-based, and AI-supported systems. Interventions involved dietary recording, personalized feedback, remote counseling, coaching, and self-monitoring. Outcomes included dietary intake and quality, nutritional status, physical function, frailty, cognition, cardiometabolic indicators, engagement, usability, and acceptability. Findings were more consistent for dietary behaviors and individualized nutrition management. Evidence for physical function, frailty, cognition, cardiometabolic health, and quality of life was limited and often based on small or multidomain studies. Familiar interfaces and professional support were accepted, whereas low digital literacy, complex navigation, and limited food databases were barriers. Digital personalized nutrition interventions may support dietary behavior change and individualized nutrition management in older adults. Larger studies and user-centered systems addressing digital literacy, usability, cultural context, and AI-feedback validation are needed.
Oral cancer is among the ten most common malignancies worldwide and can be highly lethal if not diagnosed and treated promptly. Mapping the spatial and geographic distribution of this cancer can assist health authorities in planning effective prevention, control, and treatment strategies by identifying its geographic and demographic patterns. This study aimed to investigate the demographic characteristics and geographic distribution of oral cancer in Golestan Province, Iran, during the period 2014-2021. This trend study used data from the National Cancer Registry System of Golestan Province, Iran, covering the period from 2014 to 2021. Geographic mapping of the cities in Golestan Province was performed using ArcGIS software. The annual incidence of oral cancer was calculated for each city and expressed as the number of cases per 100,000 population per year. A total of 390 patients with oral cancer were identified in Golestan Province between 2014 and 2021. Of these, 200 (51.3%) were male and 190 (48.7%) were female. The mean age of the patients was 56.18 ± 17.37 years, ranging from 2 to 96 years. The standardized annual incidence rate of oral cancer in Golestan Province ranged from 4.25 to 6.75 cases per 100,000 population during the study period. Among the cities of the Province, Maraveh Tappeh showed the highest incidence rate, with an average incidence of 12.35 cases per 100,000 population. The incidence of oral cancer in Golestan Province demonstrated temporal fluctuations during the study period, with higher rates observed in several northern cities. Geographic mapping of the disease may provide valuable insights into the potential influence of environmental, cultural, and lifestyle factors on the distribution of oral cancer and can support more targeted prevention and control strategies.
Physicians operate at the intersection of 2 conflicting imperatives: the clinical mandate to avoid missed diagnoses and the ethical requirement to avoid unnecessary interventions. While advanced imaging can reduce diagnostic uncertainty, overuse introduces systemic inefficiencies, financial waste, and physical harm. This article argues that the solution lies in transitioning from an information maximization mindset to a satisficing framework, rooted in the theory of bounded rationality. Beyond biological risks, additional imaging often identifies insignificant incidental findings, triggering diagnostic cascades and psychological distress. Over-ordering may be motivated by defensive medicine, patient satisfaction pressures, and financial conflicts of interest. A satisficing framework clarifies when additional information is no longer needed. When satisficing, one stops acquiring information once current information is sufficient for action, whereas under a Value of Information (VOI) framework, one stops when the expected incremental benefit of additional information no longer exceeds its incremental costs and harms. Both frameworks reflect that the relationship between clinical utility and imaging data volume is nonlinear; eventually, incremental contributions diminish while cumulative costs continue to rise. Putting this approach into practice requires leveraging Clinical Decision Support Systems (CDSS), minimalist protocols, and increased visibility regarding opportunity costs. Robust safety protocols, including departmental reviews of exception rates and peer reviews, can be used to ensure that satisficing does not lead to increased diagnostic errors. Ultimately, quality in radiology should be defined by whether imaging appropriately informs management, rather than by the volume of data gathered. The goal is to provide the information necessary to act safely and effectively while recognizing when to stop.
Bioimaging experiments in plasma medicine generate datasets that extend beyond conventional imaging studies by combining microscopy data with heterogeneous metadata from biological experiments and gas plasma treatments. These data are often distributed across multiple systems, making it difficult to maintain links between imaging data, plasma treatment conditions, biological metadata, and microscopy acquisition settings. This fragmentation limits data sharing and repository deposits. To address this challenge, we present a data management workflow for FAIR sharing of bioimaging datasets in plasma medicine. The workflow is implemented as an open-source Jupyter Notebook and connects the established research data management tools Open Microscopy Environment Remote Objects (OMERO) for image data management, eLabFTW as an electronic laboratory notebook for experimental documentation, Adamant as a schema-based metadata acquisition tool, and Micro-Meta App for the standardized capture of microscopy settings. The workflow guides researchers through the data management process, supporting the adoption of the FAIR data principles for the sharing and reuse of imaging datasets. We demonstrate how biological metadata, plasma-treatment parameters, microscopy settings, and image data are associated across the Screen, Plate, and Well hierarchy in OMERO through structured JSON metadata records generated in Adamant, stored in eLabFTW, and linked to imaging datasets. By means of a structured FAIR assessment, the contribution of the workflow components to the achievement of FAIR imaging datasets in plasma medicine is demonstrated, resulting in a FAIR compliance level of 50-60%. Thus, the Jupyter Notebook workflow supports researchers in plasma medicine and other domains with similar requirements by linking image data and metadata to experiment descriptions, enabling FAIR sharing and simplified reuse of bioimaging datasets.
Cardiovascular-kidney-metabolic (CKM) syndrome poses a major health risk. This study assessed the impact of a healthy lifestyle on all-cause and cardiovascular disease (CVD) mortality in CKM individuals. We analyzed 306 831 and 9823 CKM individuals from UK Biobank and NHANES (2007-2018). A healthy lifestyle score was created based on seven factors: no current smoking, moderate drinking, healthy diet, regular physical activity, adequate sleep, low sedentary behavior and appropriate social connection. Primary outcomes were all-cause and CVD mortality from linked health records and death registries. Cox regression models showed that higher lifestyle scores were associated with reduced risks of all-cause (hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.80-0.82) and CVD mortality (HR: 0.82, 95% CI: 0.80-0.84) in UK Biobank. In NHANES, higher scores were associated with 15% (95% CI: 0.80-0.90) and 11% (95% CI: 0.81-0.99) lower mortality risks. Both regular physical activity (HRs: 0.85 and 0.89 for UK Biobank, 0.76 and 0.73 for NHANES) and low sedentary behavior (HRs: 0.85 and 0.91 for UK Biobank, 0.79 and 0.67 for NHANES) were related to reduced mortality risks (p < 0.05). Participants with non-advanced CKM syndrome and a favorable lifestyle had the lowest mortality risks compared to those with advanced CKM syndrome and an unfavorable lifestyle. A healthy lifestyle, particularly regular physical activity and low sedentary behavior, was significantly associated with lower all-cause and CVD mortality in individuals with CKM syndrome. These associations were stronger in the early stages, highlighting the importance of timely and targeted lifestyle interventions.
Objectives　This study examined the availability and readiness of municipal data to assess participation in cancer screening among people with severe mental illness (SMI). In addition, we evaluated the feasibility of linking the Medical Payment for Services and Supports for Persons with Disabilities (MPSS) database and the municipal cancer screening database to calculate cancer screening uptake rates among individuals with schizophrenia spectrum disorder.Methods　A two-phase survey was conducted in municipalities in the Kinki, Chugoku, and Shikoku regions of Japan. In Phase 1, municipalities completed a questionnaire on the digitization status of relevant data items in municipal databases, including the MPSS, Mental Disability Certificate (MDC), and municipal cancer screening databases. In Phase 2, municipalities completed a questionnaire assessing the feasibility of generating aggregated data on cancer-screening participation using the MPSS and municipal cancer-screening databases.Results　Of the 429 municipalities surveyed, 67 (15.6%) responded to Phase 1. Of these, approximately 90% of the municipalities managed the MPSS and MDC databases as electronic data files; however, among those using electronic systems, primary diagnoses coded using the International Classification of Diseases, 10th Revision (ICD-10) were recorded in only 45% and 34% of the MPSS MDC databases, respectively. The municipal cancer screening database was electronically managed in over 95% of the participating municipalities. Primary screening results were recorded in 99% of patients, and attendance at follow-up examinations was recorded in ＞ 94% of patients. In the Phase 2 questionnaire, 13 municipalities (3.0%) successfully provided aggregated data by linking the MPSS and municipal cancer-screening databases, enabling the calculation of the municipal cancer-screening uptake rate among individuals with schizophrenia spectrum disorders. However, barriers included missing diagnostic information, technical difficulties in linking data across systems, privacy and data governance concerns, and limited human resources.Conclusion　Assessing cancer-screening uptake rates among people with SMI using the MPSS and municipal cancer-screening databases is technically feasible in a subset of municipalities. However, several challenges remain including limitations in data item completeness, structural barriers between information systems, and human resource constraints. Continued standardization of local government information systems and improvements in the administrative data infrastructure may enable the use of municipal data to design and evaluate cancer-screening policies that are responsive to the needs of people with SMI.
The aim of this study was to examine temporal trends in metabolic syndrome-associated osteoarthritis (MetS-OA) among patients undergoing revision total knee arthroplasty (RTKA) and to identify patient- and clinical-level factors associated with this condition and related outcomes. A retrospective cohort analysis was conducted using data from the Nationwide Inpatient Sample from 2010 through 2019. Patient demographics, hospital characteristics, length of stay, total hospitalization charges, in-hospital mortality, comorbid conditions, and perioperative complications were assessed. All analyses incorporated NIS discharge weights, and multivariable logistic regression models were used to assess associations between MetS-OA and clinical outcomes among patients undergoing RTKA. Among 1,361,454 RTKA hospitalizations identified, 1,330,099 RTKA hospitalizations were included in the analysis. The overall prevalence of MetS-OA was 16.1%, demonstrating a progressive increase from 2011 through 2019. Factors independently associated with MetS-OA included advanced age, male sex, non-White racial background, and the presence of comorbid conditions such as chronic pulmonary disease, depression, and hypothyroidism. Patients with MetS-OA experienced slightly longer hospital stays and incurred higher median total hospitalization charges, exceeding those without MetS-OA by $1,445.50. In-hospital mortality did not differ significantly between groups. MetS-OA was also associated with a higher likelihood of postoperative complications, including acute myocardial infarction, severe malnutrition, acute cerebrovascular disease, postoperative delirium, acute respiratory distress syndrome, prolonged mechanical ventilation, urinary tract infections, acute renal failure, and lower limb nerve injury. The prevalence of MetS-OA among patients undergoing RTKA has increased over time and is associated with a higher burden of postoperative complications and healthcare utilization. Patient- and hospital-level factors play a substantial role in shaping these outcomes. Targeted preoperative optimization and standardized perioperative management strategies for patients with MetS-OA may mitigate adverse events, enhance postoperative recovery, and reduce overall hospitalization charges.