The negative symptoms of psychosis are heterogeneous, which complicates efforts to understand their pathophysiology and develop effective treatments. Factor analytic studies of the Positive and Negative Syndrome Scale (PANSS) have reported two factorial negative symptom models, expressive deficit and social amotivation, albeit with different compositions. Although models derived from other assessment scales have been directly compared, no study has previously applied this approach to PANSS.

Our objectives were to (a) to establish which negative PANSS-derived factorial model provided the best fit to our data, (b) test its stability and (c) determine its clinical and demographic correlates.

A cohort of medication naive or minimally treated patients with first-episode schizophrenia (n = 446) were assessed using the PANSS scale before and 4 weeks after amisulpride treatment. Confirmatory factor analysis was performed to test five PANSS models. Hierarchical multiple regression was conducted to examine the associations between identified dimensions and clinical and demographic variables.

A nine-item PANSS model comprising social amotivation and expressive deficit dimensions outperformed the other models: comparative fit index = 0.98, goodness of fit index = 0.97, Tucker–Lewis index = 0.97, root mean square error of approximation = 0.06 (CI 90%: 0.04–0.08), Bayesian information criterion = 191.9, Akaike information criterion = 101.7. At baseline, the social amotivation dimension was associated with more severe depression whereas the expressive deficit dimension was associated with younger age. Both dimensions at baseline were associated with poor functioning, but expressive deficit to a lesser extent.

A nine-item PANSS model incorporating social amotivation and expressive deficit dimensions appeared to best reflect the underlying structure of negative symptoms in our sample.

Cost-effectiveness analyses are used to help to inform resource-allocation decision-making in healthcare systems. The manufacturers of new health technologies may choose to employ “early cost-effectiveness analysis” (eCEA) to inform the technology development process in anticipation of a value-based assessment if and when the technology is launched. We aim to provide guidance on how eCEA can effectively inform health technology development processes, presenting novel methodological approaches to address key decision-making questions.

We present three core health technology development questions that eCEAs can address, as well as recommendations for deriving and presenting insights from eCEA models. A hypothetical treatment for cutaneous squamous cell carcinoma (CSCC) called “dummymab” demonstrates the analytic techniques and presentation formats.

We provide guidance for addressing: 1. What is a health technology’s value-based price (VBP) under a range of scenarios? 2. To what extent do different attributes of the technology contribute to its value? 3. Regarding what model parameters is further evidence most valuable? A novel net benefit approach for value driver analysis provides more reliable estimates than traditional ‘switch-on’ methods by avoiding parameter interaction effects. The manufacturer-perspective value-of-information framework enables evidence prioritization aligned with commercial decision-making while maintaining cost-effectiveness principles.

eCEA can systematically inform technology development through value-based price estimation, value driver identification, and evidence prioritization. Implementing development decision-making based on eCEA insights can foster alignment with value-based principles of HTA-orientated decision-making systems while supporting more efficient resource allocation in technology development.

We evaluated whether patient perceptions of cleanliness are associated with objective measures of Clostridioides difficile infection (CDI), as an early indicator of facility-level CDI rates and prevention.

Cross-sectional analysis of Medicare-certified hospitals across the United States.

Data from the CMS Hospital Compare website and U.S. Census Bureau from 2023 were analyzed using multivariate logistic regression models. The primary outcome was C. difficile standardized infection ratios (SIRs) compared to the national average. The primary exposure was patient-rated cleanliness star ratings from the Hospital Consumer Assessment of Healthcare Providers and Systems survey.

The population studied was 3,616 medicare-certified hospitals with an estimated 17,994,034 unique patient admissions. There was no association between better patient-rated cleanliness and improved CDI performance. Facilities with a 5-star cleanliness rating were not more likely to have an SIR less than or equal to the national average compared to those with a lower star rating. For every 1% increase in patients who reported their room and bathroom as always clean, the odds of CDI observed cases being higher than predicted increases by 4.2% (ie, increasing patient-related cleanliness was weakly associated with worse CDI performance).

Patient-rated cleanliness was not associated with improved CDI performance in U.S. national hospital data. Findings were consistent across multiple operationalizations of cleanliness and CDI suggesting patient perceptions of cleanliness are not a strong indicator of CDI control measure performance.

Disaster medicine (DM) prepares health care professionals to manage emergencies caused by significant societal disruptions. Training recent graduates and final-year students is an essential element of disaster preparedness. This review aims to examine the use of Virtual Simulation (VS) in undergraduate students’ DM training.

The research team searched Scopus, PubMed, WOS, and Scielo. The team followed the 6-step approach described by Mak to conduct Scoping Reviews. We identified 262 reports, and 17 articles met the inclusion criteria. We extracted and analyzed data, focusing on educational settings, professions involved, and intervention characteristics. The report followed PRISMA guidelines.

The implementation of VS in DM training has been geographically concentrated, with most studies focused on nursing education. Most programs use virtual reality, with limited augmented or mixed reality integration, principally in nursing students. The training focused primarily on triage, disaster preparedness, evacuation, decontamination, improving knowledge retention, self-confidence, and decision-making.

Although VS has effectively enhanced technical skills and disaster preparedness, its use remains limited in undergraduate health education. Further research is needed to expand its application in interprofessional and non-nursing contexts, with deliberate practice principles to maximize efficiency. Integrating VS into community training can reduce costs and enhance large-scale emergency response.

Access to quality healthcare is often limited in rural and underserved areas, leading to higher rates of preventable diseases, avoidable hospitalizations, and mortality. Virtual health clinics, utilizing telehealth and telemedicine technologies, offer a promising solution to bridge these gaps. This scoping review aimed to systematically identify and analyze the benefits, outcomes, and service range of virtual clinics in remote and underserved settings.

This scoping review was conducted following Arksey and O’Malley’s six-stage framework. Relevant literature was searched in PubMed, Web of Science, Scopus, Google, and Google Scholar. Data were extracted using a standardized charting form and thematically analyzed using Braun and Clarke’s method with MAXQDA software.

A total of 38 benefits of virtual clinics were identified, primarily related to improved access to health services, reduced costs, and decreased patient travel. In the domain of governance and leadership, enhanced governmental support and optimal resource allocation were reported. For human resources, improved communication and training were emphasized. Moreover, the use of local technologies, remote medication ordering, and digital record-keeping demonstrated a significant impact, particularly in middle- and high-income countries.

Virtual clinics can effectively enhance the quality and accessibility of health services in underserved areas and play an important role in reducing health inequities.

To assess interagency emergency response capabilities for radiological threats through a tabletop exercise (TTX) simulating a nuclear power plant accident, with focus on communication protocols, patient referral pathways, and public information management in Ukraine’s current security context.

A structured 3-day TTX was conducted in September 2024 by the WHO Ukraine Country Office, simulating a cooling system failure at a fictional North-West Nuclear Power Plant. Twelve organizations participated, including regional health authorities, emergency services, and international partners. The exercise employed a progressive scenario that injects testing accident notification, media management, medical response, and evacuation procedures. Performance was evaluated using structured criteria (Achieved, Partially Achieved, Not Achieved) across predefined indicators.

The exercise identified critical preparedness gaps including the absence of regular radiological-nuclear emergency drills in regions without nuclear facilities, challenges in potassium iodide procurement and distribution, staff hesitancy due to inadequate insurance coverage, and lack of standardized decontamination procedures. Communication protocols functioned effectively, though coordination delays were noted. Patient referral pathways required strengthening, particularly for contaminated casualties.

While Ukraine demonstrates functional emergency response frameworks, specific radiological preparedness requires enhancement. Regular multiagency drills, improved staff protection policies, standardized decontamination protocols, and robust public information systems are essential for effective radiological emergency response.