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Ongoing neurodevelopmental care is essential for children with congenital heart disease (CHD). Understanding delivery and uptake of neurodevelopmental care pathways can inform implementation and resource planning. This study applied simulation modelling to explore outcomes from a neurodevelopmental care pathway for children with CHD. The model was developed using data from a Queensland program to explore health service interactions for neurodevelopmental screening, formal assessment, and early intervention, up to five years. Modelling was intended to provide a baseline understanding of the pathway, rather than evaluating against a reference standard. Hypothetical scenarios explored how changes in screening and referrals influenced the identification of developmental concerns, and how developmental concern severity affected intervention referrals. Based on available data, 58% of the cohort remained under routine surveillance and 25% had accessed early intervention for one or more developmental delays. Scenarios defined by increased screening projected up to 55% of the cohort having a developmental concern identified during screening and 45% having a developmental delay identified following assessment. Simulation modelling was useful for understanding outcomes from a neurodevelopmental pathway and how differences in screening and assessment affected health service interactions. Findings may inform policy and resource planning for future neurodevelopmental pathways. This study shows that simulation modelling is a useful approach for evaluating a neurodevelopmental care pathway for children with CHD, to understand movement through neurodevelopmental screening, assessment, and interventions. Scenario-based modelling provides insights into factors influencing pathway engagement, contributing evidence to strengthen understanding of service gaps and areas where improvements can most effectively impact engagement and resourcing. This study identifies neurodevelopmental screening as the most influential stage impacting downstream outcomes, underscoring its importance as a strategic intervention point. This study's approach provides a general framework for evaluating similar pathways and a potential baseline for assessing future policy or service changes.

Insurance fraud detection remains challenging to predict in reality because claims data is often uneven among classes, and the information concerning claims is often multidimensional and nonhomogeneous. The present research used a unified evaluation framework to assess the predictive and interpretive capabilities of three distinct model families: CatBoost (tree-based ensemble learning), Bi-GRU with Attention (sequence-oriented learning), and TabTransformer (categorical feature contextual). The model families were tested using a standardised experimental protocol.The study is novel in the sense of a cross-model interpretability framework that unites Shapley Additive Explanation (SHAP)-based feature attribution with attention-based contextual analysis to enable a clear comparison of model reasoning between the suggested frameworks. The data on which the experiments were done consisted of 4,000 life insurance claims that were characterized in terms of 83 attributes. Common preprocessing procedures like missing values, scaling numerical variables, and selecting highly correlated variables were used before training the models. Experimentally, CatBoost is proven to be the most precise on legitimate claims, Bi-GRU is the most recall on fraudulent claims, and TabTransformer is the best in terms of tradeoff between accuracy, interpretability, and computational efficiency. Practical characteristics such as the quantity of claim, tenure in a policy, and diagnosis were repeatedly emphasized in both SHAP and attention analyses. Combined, the current research study provides a consistent and explainable benchmark that may be applied to conduct fraud detection research reliably and assist practitioners in choosing models that are accurate and understandable.

To examine early-career U.S. midwives' involvement in abortion care provision. We analyzed data from a 2024 national survey of certified nurse-midwives and certified midwives within five years of certification, assessing self-reported abortion care provision. Overall, 18.8% of respondents reported providing abortion care; among those practicing in states where abortion is legal and permitted under licensure, 26.0% reported providing abortion care. Provision varied by policy context and provider characteristics. Early-career midwives contribute to abortion care in the United States. Findings inform understanding of the abortion care workforce.

Government-led repurposing programmes are reshaping the division of labour in pharmaceutical innovation. A new power drafted into the European Union pharmaceutical reform package will allow the European Medicines Agency (EMA) to add new therapeutic indications to marketed medicines without the marketing authorization holder's consent. Companies oppose this power, but in weighing up enacting the power, society has a poor understanding of its potential to help patients. This study offers the first empirical assessment of the promise of the power. It analyses 198 medicines from 12 years, comparing EMA-authorized labels with those authorized by the US Food and Drug Administration and a leading reference for off-label uses. Sixty-seven per cent of the medicines have at least one additional use supported by clinical evidence, yielding 320 potential new uses. Of these, 39 per cent are for new diseases and 61 per cent for new patient cohorts, a third of the latter concerning paediatric populations. Commentators generally omit discussing repurposing for new patient cohorts, even though it is a focus of the European Commission. The study's results suggest that the power could be used to authorize a meaningful number of evidence-based uses, especially those already authorized in the USA, while also revealing a policy synergy for neglected populations.

This study investigates the impact of online gambling on problem behaviors among South Korean adolescents across three phases of the COVID-19 pandemic: pre-pandemic (2018), early pandemic (2020), and late pandemic (2022). We applied a doubly robust estimation approach that combines propensity score matching with regression analysis using nationally representative survey data from the Korea Problem Gambling Agency. Our findings indicate that online gambling significantly intensified adolescents' problem behaviors in all periods, with a more pronounced effect observed during the late pandemic phase in 2022 compared to the early phase in 2020. Sensitivity analysis further demonstrated that the estimated effects were substantially robust to unobserved confounding, particularly in 2018 and 2022. We conclude with a discussion of adolescents' heightened vulnerability to online gambling-related problem behaviors and the corresponding need for targeted interventions and policy responses.

To evaluate the clinical and economic impact of universal screening for cytomegalovirus (CMV) in pregnant women in Italy, with valacyclovir (VCV) therapy in the case of maternal primary CMV infection, compared with no screening. We developed a decision-analytic model using a deterministic decision tree and compared the no-screening strategy (Scenario 1) with universal screening until 13 + 6 weeks' gestation (Scenario 2), and universal screening until 23 + 6 weeks' gestation (Scenario 3) as recommended by the Italian National Health Service. The model was applied in a hypothetical population of 400 000 pregnant women, representative of the annual number of women giving birth in Italy. Only women susceptible to primary CMV infection were considered, in whom CMV screening by serological testing (IgG/IgM testing ± IgG avidity), followed by VCV treatment (8 g/day) in the case of primary CMV infection, is recommended. Outcomes included the numbers of primary maternal CMV infections diagnosed, fetal congenital CMV (cCMV) infections, terminations of pregnancy (TOPs) and symptomatic and asymptomatic neonatal cCMV infections, and the cost per symptomatic cCMV case avoided (in Euros (€)) from the perspective of the Italian National Health Service. Universal screening until 13 + 6 weeks' gestation would identify 910 maternal primary CMV infections. Compared with no screening, it would prevent 92% of symptomatic cCMV infections (183 vs 15 cases) and prevent 70% of TOPs (33 vs 10 cases). Extending the universal screening period to 23 + 6 weeks' gestation would result in 280 additional diagnoses of maternal primary CMV infection and a further 2% and 9% reduction in symptomatic cCMV infections and TOPs, respectively. Both screening strategies would increase costs by approximately €7 million compared with Scenario 1, with a cost per symptomatic cCMV case avoided of ~ €45 500 for Scenario 2 and ~ €44 400 for Scenario 3. Universal serological CMV screening in pregnancy until 24 weeks' gestation, with VCV treatment in the case of maternal primary infection, substantially reduces the burden of cCMV-related disabilities and appears economically justifiable in the Italian healthcare context. These findings may inform policy decisions in countries with a similar CMV seroprevalence and National Health Service. © 2026 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

The Health and Social Care Professionals' Knowledge and Attitudes towards Later-Life Intimacy and Sexuality (HSCP-KALLIS) is designed to assess health and social care professionals' knowledge and attitudes toward later-life intimacy and sexuality. Additional care considerations are included for older adults with dementia and those from diverse gender backgrounds. This study aimed to evaluate the reliability and validity of the HSCP-KALLIS scale. This methodological study was a subsequent phase of the HSCP-KALLIS scale development undertaken between 2022 and 2023, using an online survey approach with participants who were health and social care professionals. Internal consistency was assessed using McDonald's Omega and Cronbach's alpha, while the underlying factor structure of the scale was examined through exploratory factor analysis. A total of 98 participants were recruited for the study. Participants primarily were females, registered nurses, worked in aged care, and demonstrated high levels of knowledge and positive attitudes towards later-life intimacy and sexuality. The final HSCP-KALLIS Scale consists of 30 knowledge items across two factors and 25 attitude items across three factors, with satisfactory internal consistency demonstrated. This study provides preliminary evidence that the HSCP-KALLIS scale is a reliable tool for measuring health and social care professionals' knowledge and attitudes towards later-life intimacy and sexuality. This scale shows potential for identifying staff training needs, evaluating training effectiveness, and informing policy and guidelines development. The primary study limitations include methodological constraints and a small sample size. Future research should involve a larger sample size to enable confirmatory factor analysis. Not applicable.

The green and digital transitions are reshaping the global economy, requiring new human capital paradigms that move beyond technical skills and instrumental, metric-driven models. This paper reimagines human capital development through the Daoist classic Zhuangzi, which critiques rigid categorization and promotes spontaneity, perspectival flexibility, and harmony with change. Rather than viewing human capital as a fixed set of skills, Zhuangzi offers a model focused on adaptability, ethical humility, and intuitive responsiveness. Through a structured hermeneutic analysis of the text, we derive a conceptual framework organized around five core capacities: adaptive learning, ethical humility, embodied and intuitive skill, relational attunement, and frugality-oriented judgment, which are positioned as foundational to an enhanced intellectual capital framework that prioritizes dynamic, relational, and sustainability-oriented capabilities. These traits align with systems thinking, participatory governance, and frugal innovation in green and digital contexts. The paper proposes a Zhuangzi-inspired framework for education and policy, emphasizing metacognitive awareness, narrative pedagogy, and the integration of philosophical inquiry into technical training. Zhuangzi, far from being a historical curiosity, serves as a vital guide in modern discussions on sustainability, automation, and human development. It encourages a shift from control-based models to those grounded in trust, simplicity, and ethical awareness. Daoist thought provides a philosophical compass for fostering a more resilient, humane, and context-responsive approach to human capital. Through an illustrative application on digital environmental monitoring, the paper demonstrates how the framework reframes competence as cultivated responsiveness rather than technical control. By connecting ancient philosophy with modern sustainability challenges, and directly engaging with intellectual capital theory, this paper positions Zhuangzi as a key resource in reshaping human capital toward wisdom-oriented adaptability.

The recent introduction of the right to oncological oblivion in some European states raises critical issues. While designed to protect cancer survivors from discrimination, this right may compromise occupational health surveillance for workers exposed to carcinogenic hazards. This commentary raises questions for future policy and research.

Cervical cancer remains a significant public health concern. In Vietnam, national strategies have been introduced to increase screening coverage, but population-level data assessing progress remain limited. This study aimed to estimate cervical cancer screening prevalence and trends in Vietnam and identify associated demographic and socioeconomic factors using nationally representative data. We conducted a secondary analysis of the 2015 and 2021 Vietnam WHO STEPwise Approach to NCD Risk Factor Surveillance (STEPS) surveys. Cervical cancer screening prevalence was defined as self-reported history of ever screening via Pap smear, VIA, VILI, or HPV testing. Survey-weighted methods were used to estimate prevalence and assess changes over time. Temporal trends were evaluated using the Cochran-Armitage test. Multivariable survey-weighted logistic regression models were applied to identify associated factors. Among 4,168 women, the overall screening prevalence was 20.47%, decreasing from 24.86% in 2015 to 16.36% in 2021 (p < 0.001). Screening was more likely among women of Kinh ethnicity (aOR = 2.56; 95% CI, 1.45 - 4.50), urban residents (aOR = 1.27; 95% CI, 1.01 - 1.60), and those who were currently married or separated/divorced/widowed. Disparities by ethnicity, wealth, and geography widened over time. Cervical cancer screening prevalence in Vietnam remains low and has declined in recent years. Significant disparities persist and have widened, particularly among ethnic minorities, rural populations, and women with lower socioeconomic status. To meet national and global cervical cancer elimination goals, urgent policy action is needed to expand equitable access to screening and reduce structural barriers for underserved populations.

Recovery housing provides critical support for individuals with opioid use disorder (OUD), yet residents who use medications for OUD (MOUD) often face barriers to entry and long-term support. No existing validated instruments currently assess these barriers, which can differ by MOUD type and reflect both attitudinal stigma and logistical capacity within recovery housing settings. We developed and tested two parallel versions (Operator and Resident) of a novel tool, the Recovery Housing Barriers to Medications for Addiction Treatment (RHB-MAT) measure. Item generation was informed by literature review and structured input from current housing operators and residents, resulting in scales addressing attitudinal barriers (for both operators and residents) and capacity barriers (for operators) and MOUD type (buprenorphine, methadone, naltrexone). Surveys were administered to 145 recovery housing operators and 250 residents across the United States. Exploratory and confirmatory factor analyses were conducted to establish dimensionality. Internal consistency, and convergent, divergent, and concurrent criterion validity were examined using established measures of stigma and related constructs. Factor analyses supported a multidimensional structure, distinguishing attitudinal barriers across both groups and capacity barriers among operators. Internal consistency across scales was acceptable to strong (&#x3b1;&#x202f;=&#x202f;0.74-0.92) across all but one subscale. Convergent validity was supported while divergent validity was less consistent. Concurrent criterion validity was generally demonstrated with associations between Operator RHB-MAT scores and their house's unique medication acceptance policies by MOUD type. Overall, residents evidenced higher attitudinal barrier scores than operators. The RHB-MAT represents the first validated measure of MOUD-related barriers in recovery housing, with tailored versions for both operators and residents. This tool can be used in research, policy, and practical quality improvement efforts to identify and address attitudinal and capacity-related barriers that impede access to evidence-based OUD treatment in recovery residences.

The timeliness of treatment for out-of-hospital cardiac arrest (OHCA) is critical for patient survival. Automated External Defibrillators (AEDs) are a proven effective intervention, yet China's rapidly developing Public Access Defibrillation (PAD) program may be accompanied by significant spatial inequities in AED distribution. This study developed a comprehensive multi-dimensional evaluation model to assess the spatial equity of AED allocation in four first-tier Chinese cities: Beijing, Shanghai, Guangzhou, and Shenzhen. The model integrated four dimensions: resource allocation (supply-demand ratio), spatial coverage (service coverage index), opportunity accessibility (accessibility index via an enhanced Gaussian two-step floating catchment area method), and spatial distribution (Gini coefficient). These dimensions were aggregated into a Comprehensive Equity Index (CEI) using the Entropy Weight Method (EWM). Leveraging high-resolution gridded population data and precise AED locations, our analysis captures fine-scale spatial variations often obscured in aggregate statistics. Furthermore, to uncover the spatially heterogeneous drivers of equity, we employed an integrated Principal Component Analysis and Geographically Weighted Regression (PCA-GWR) framework to analyze socioeconomic and urban environmental factors. The results indicate that: (1) Overall comprehensive equity was low across all cities (mean CEI&#x2009;<&#x2009;0.3). Shenzhen exhibited the highest equity (mean CEI: 0.252), followed by Beijing (0.207), with Shanghai and Guangzhou lagging. (2) A significant "core-periphery" disparity was observed in all cities, with core districts showing markedly higher equity than suburban districts, a gap particularly pronounced in Beijing and Shanghai. (3) The PCA-GWR analysis revealed pronounced spatial heterogeneity in the associations between external factors and AED equity. Degree of urbanization showed a generally positive association, which was consistently weaker in urban cores. Public service facility provision exhibited inconsistent (often negative) associations, while the wealth-population density trade-off demonstrated marked city-specific variation. This study provides a systematic, multidimensional assessment of AED allocation equity in major Chinese cities. By employing a spatially nuanced PCA-GWR framework, it reveals that equity is shaped by complex, location-specific interactions of urban development, service provision, and socioeconomic structure. The findings underscore the necessity for spatially differentiated policy interventions within China's PAD program to achieve more equitable and efficient deployment of these lifesaving resources.

Respiratory epidemics often place substantial pressure on intensive care units (ICU), which are continuously challenged to managing acute and life-threatening conditions under unpredictable workloads. During these periods, ICUs usually exhibit inefficient patient flows, treatment delays, and critical resource shortages. Proactive decision-making and precise interventions are therefore pivotal for patient survival and minimizing long-term sequelae. This paper proposes a robust approach combining Artificial Intelligence (AI), Bayesian Optimization, and Digital Twin (DT) to support ICU patient flow management. An eXtreme Gradient Boosting (XGBoost) algorithm is used to predict the patient transfer probability from the emergency department (ED) to the ICU within the next 24&#xa0;h. Bayesian optimization is employed for efficient hyperparameter tuning of the XGBoost model. Then, the transfer predictions are inserted into a DT to verify ICU capacity for timely care and design interventions for process mismatches. A case study from a European healthcare group validates the proposed approach. The specificity of the prediction XGBoost model was 94.90% (CI 95% 91.72% - 97.11%), whereas the sensitivity was 81.55% (CI 95% 72.70% - 88.51%). Finally, the median ICU bed waiting time decreased to between 66.74 and 69.38&#xa0;h after implementing a patient transfer policy with a partner hospital having available ICU beds. This study demonstrates the effectiveness of AI-DT in predicting the probability of ICU transfers, assessing the operational response of emergency wards and intensive care units, and crafting practical scenarios for enhancing patient flow management.

To examine interpersonal violence as a public health issue affecting refugees, migrants and people with learning disabilities in the United Kingdom, and to identify system-level drivers and opportunities for prevention and response. Theory-informed conceptual narrative synthesis using two illustrative case studies. We synthesised evidence from public health, migration and disability literature and relevant policy/guidance, organised using an ecological and social determinants framework. We developed two case studies (forced migration and learning disability) to map how systems shape exposure, disclosure and access to protection. Across both populations, violence is structurally produced through immigration/asylum rules, institutional and social care environments, welfare and housing precarity, and service designs that restrict autonomy and undermine disclosure. Common gaps include under-recognition by services, limited staff training, and a lack of culturally and cognitively accessible pathways to safety, contributing to preventable health inequalities. Preventing and responding to interpersonal violence for these groups requires system-level, rights-based, trauma-informed and culturally/cognitively responsive approaches, including routine enquiry, accessible communication tools, clear referral pathways and sustained investment in specialist community-led services.