Search Results (5,037)

Researchers are increasingly engaged in studies to determine and correct negative welfare consequences of animal husbandry and behaviour modification procedures, not least in response to industries’ growing need to maintain their social licence through demonstrable welfare standards that address public expectations. To ensure that welfare recommendations are scientifically credible, the studies must be rigorously designed and conducted, and the data produced must be interpreted with full regard to conceptual, methodological, and experimental design limitations. This commentary provides guidance on these matters. In addition to, and complementary with, the ARRIVE guidelines that deal with animal studies in general, there is a need for additional specific advice on the design of studies directed at procedures that alter behaviour, whether through training, handling, or restraint. The COMPASS Guidelines offer clear direction for conducting welfare-focused behaviour modification research. They stand for the following: Controls and Calibration, emphasising rigorous design, baseline measures, equipment calibration, and replicability; Objectivity and Open data, ensuring transparency, validated tools, and data accessibility; Motivation and Methods, with a focus on learning theory, behavioural science, and evidence-based application of positive reinforcers and aversive stimuli; Precautions and Protocols, embedding the precautionary principle, minimising welfare harms, listing stop criteria, and using real-time monitoring; Animal-centred Assessment, with multimodal welfare evaluation, using physiological, behavioural, functional, and objective indicators; Study ethics and Standards, noting the 3Rs (replacement, reduction, and refinement), welfare endpoints, long-term effects, industry independence, and risk–benefit analysis; and Species-relevance and Scientific rigour, facilitating cross-species applicability with real-world relevance and robust methodology. To describe these guidelines, the current article is organised into seven major sections that outline detailed, point-by-point considerations for ethical and scientifically rigorous design. It concludes with a call for continuous improvement and collaboration. A major purpose is to assist animal ethics committees when considering the design of experiments. It is also anticipated that these Guidelines will assist reviewers and editorial teams in triaging manuscripts that report studies in this context. Full article

Categorical data analysis offers valuable tools for evaluating school-based prevention programs, yet these methods remain rarely applied in cyberbullying research. This literature review examined how categorical approaches, including contingency tables and related techniques, have been used in studies evaluating school-based cyberbullying prevention. A comprehensive search was conducted in Web of Science covering publications from 2020 to 2025, yielding 100 articles. After applying predefined inclusion and exclusion criteria, 24 studies were reviewed in full, of which 8 met all requirements for final analysis. The results revealed a predominant reliance on linear statistical techniques, such as t-tests, ANOVA, and regression models, applied mainly to continuous variables. By contrast, categorical analyses were seldom employed. The chi-square test appeared as the most frequent approach, but its use was generally restricted to descriptive purposes, with little application of complementary methods such as standardized residuals, effect size measures, or logistic models. This restricted application reduced the ability to capture response patterns, subgroup differences, and categorical associations essential for evaluating program outcomes. The findings highlight a methodological gap in cyberbullying prevention research and emphasize the potential of categorical data analysis to enrich interpretation. Incorporating these methods could increase methodological rigor, reveal nuanced behavioral patterns, and provide actionable evidence for educators, policymakers, and program designers seeking to strengthen school-based prevention strategies. Full article

While research on high-incidence tumors such as breast, prostate, and lung cancer has led to significant increases in patient survival in recent years, this has not been the case for low-incidence tumors such as high-grade gliomas, the most common and lethal brain tumors, for which the last significant therapeutic advance dates back to 2005. The high infiltration capacity of these tumors into normal brain tissue essential for both vegetative and relational life, the tumor microenvironment, with poor immunological activity, the multiple resistance mechanisms, and the unattractiveness of research investments due to the limited number of patients have made, and continue to make, the path to achieving significant improvements in the survival of patients with high-grade gliomas long and arduous. The objective of this article is to update the slow but continuous radiotherapeutic progress for adult and pediatric high-grade gliomas to the second half of 2023. We analyzed the progress of preclinical and clinical research on both adult and pediatric high-grade gliomas, with a particular focus on improvements in radiotherapy. Interactions between non-radiant new therapies and radiotherapy were also covered. A literature search was conducted in PubMed using the terms (“glioma* and radio*”) and the time limit of 1 July 2023 to 31 December 2023. The inclusion and exclusion criteria for the review were relevance to advances in radiotherapy for high-grade gliomas in adults and children. Treating patients with advanced disease progression only, using “historical” data as controls, as well as repurposing drugs developed for purposes completely different from their intended use, were the major (but not the only) methods to assess risk of bias in the included studies. The effect measures used in the synthesis or presentation of the results were tabulated and/or displayed in figures. A total of 100 relevant references were reviewed. Advances in preclinical studies and in clinical radiotherapy treatment planning, innovative fractionation, use of radioisotopes/radiopharmaceuticals, radiosensitization procedures, and radiation-induced damage were focused on. While this analysis may be limited by the relatively short publication period, high-grade glioma research remains impacted, especially at the clinical level, by potential issues with trial design, such as treating patients with advanced disease progression, using “historical” data as controls, and repurposing drugs developed for completely different purposes than intended. Addressing these aspects of high-grade glioma research could improve its efficacy, which often remains low despite the associated costs. Full article

Background/Objectives: Healthcare workers (HCW) in primary care settings play a significant role in recommending vaccines to patients. We aimed to describe COVID-19 vaccination knowledge, attitudes, perception, and practices (KAPP) of HCWs in Tunisia and identify associated factors. Methods: We conducted a national cross-sectional survey (29 January to 3 February 2024) among HCWs in primary public healthcare centers using purposive sampling. Factors associated with good knowledge, positive attitude, and good practice, measured through Likert scales using face-to-face questionnaires, were identified using binary logistic regression. Results: We included 906 HCWs (mean age = 41.87 ± 8.89 years). In total, 37.75% (342/906) of HCWs had good knowledge and perception, 4.30% (39/906) had a positive attitude, and 24.9% (226/906) had good practices related to COVID-19 vaccination. Working in urban compared to rural areas was associated with good knowledge (aOR = 1.57, 95%CI = 1.12–2.21) and positive attitude (aOR = 4.94, 95%CI = 1.19–20.44) to COVID-19 vaccination. Physicians had better KAPP scores than other medical professionals. HCWs working in departments with high-risk patients were more likely to have good knowledge (aOR = 1.28, 95%CI = 1.00–1.72). Positive attitude was also associated with being male (aOR = 2.97, 95%CI = 1.75–5.07) and having at least one non-communicable disease (aOR = 1.92, 95%CI = 1.14–3.23). Being male (aOR = 1.97, 95%CI = 1.35–2.88) and having more years of professional experience (aOR = 1.81, 95%CI = 1.29–2.52) were associated with good practice. Conclusions: Just over a third of HCWs in primary healthcare clinics had good knowledge of COVID-19 vaccination, while positive attitudes and good practices were low. Targeted interventions, particularly for HCWs with less professional experience working in rural settings, are needed to increase good practices and improve COVID-19 vaccination coverage in Tunisia. Full article

Background/Objectives: Mobile health (mHealth) interventions can enhance chronic disease management, but their integration into public healthcare systems remains complex. DiabeText is the first SMS-based intervention in Spain delivering personalized diabetes self-management support using electronic health record data. This study explored perceived barriers and facilitators to the implementation of DiabeText in the Spanish public health context from the perspective of key stakeholders. Methods: A qualitative study was conducted using semi-structured interviews with 14 purposively selected stakeholders involved in digital health, diabetes care, data protection, and healthcare management across several Spanish regions. Interviews were thematically analyzed using Braun and Clarke’s approach and guided by the Implementation Research Logic Model. Results: Participants reported several barriers, including concerns regarding data protection, uncertainty about long-term sustainability, insufficient training and engagement of healthcare professionals and low digital literacy among certain patient groups. Facilitators included favorable institutional momentum for digital innovation, funding availability, perceived clinical utility and scalability of DiabeText, and growing patient familiarity with digital tools. Recommended strategies included integration into existing healthcare systems and workflows, professional training and use of familiar communication platforms. Conclusions: Effective implementation of DiabeText requires addressing regulatory, organizational, and equity-related barriers while leveraging institutional support and readiness for innovation. Early involvement of healthcare professionals, robust data governance, and investment in digital literacy are essential to ensure sustainable and equitable adoption. These findings provide actionable insights to support the integration of mHealth tools into chronic disease care in Spain and similar settings. Full article

Climate-driven sea ice decline is accelerating the commercial use of Arctic routes and raising the need for Green Shipping Corridors that couple decarbonization with safety and ecosystem protection. This study introduces the concept of Arctic Green Maritime Data—environmental, meteorological, operational, and emission datasets generated in polar navigation—and examines how the EU Data Act can serve as a legal–institutional backbone. Using a multilayered integrative analysis, we (i) interpret core provisions on user access, portability, compensation, public-interest requests, cloud switching, and interoperability; (ii) map the Act’s roles of data holder, user, and recipient onto shipping stakeholders; (iii) assess whether polar operational datasets qualify as “data generated through the use of a product”; and (iv) derive a contractual architecture for corridor operations. We propose a three-layer governance model: firm-level instruments (a Standard Arctic Green Maritime Data Transaction Agreement, enterprise data governance architecture, and FRAND (Fair, Reasonable, and Non-Discriminatory) based contracting), association-level tools (industry model terms, public-purpose data protocols, and a neutral data-trust intermediary), and IMO-level integration aligning EU Data Act principles with Polar Code and MARPOL. The analysis showed that structured rights and obligations reduce vendor lock-in, enable safe public-interest data flows (with emergency access and fair compensation), and improve interoperability across clouds and jurisdictions. The results provide implementable pathways for shipping companies to turn Arctic Green Maritime Data into strategic assets while supporting sustainable and resilient green shipping corridor operations. Full article

Social media has the potential to serve beneficial purposes. The abundance of uploaded content and responses from the public generates various opinions, allowing them to be identified as positive or negative regarding the portrayal of Bandung Regency. This research aims to analyse the classification and frequency of words for each sentiment expressed by X (Twitter) users regarding Bandung Regency. The research employs the Support Vector Machine (SVM) method. We expect the results to aid in formulating governmental programmes for Bandung Regency. The research revealed that the SVM model, which uses the Sigmoid kernel function with parameters $C$ = 10 and gamma ($\gamma$) = 1, is the most optimal sentiment classification model for handling an imbalanced dataset. This model achieved an 83.01% negative recall value. Furthermore, frequent words appearing in both classes indicate that several positive opinions about Bandung Regency exhibit similar dominance, except for football dominance in negative opinions. This research pertains to the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 16 (Peace, Justice, and Strong Institutions). The suggested technique facilitates evidence-based policy reviews, transparent governance, and enhanced responsive public services by analysing public sentiment regarding local government performance. The results illustrate how social media analytics can aid local governments in assessing popular sentiment and pinpointing areas for policy response. Full article

Background: The healthcare industry demands nurses with both clinical proficiency and leadership skills. However, formal leadership training remains limited among undergraduate nursing students, underscoring the need for clinical mentorship to support leadership development. Purpose: This study investigated the association between clinical mentorship quality and leadership competencies among undergraduate nursing students enrolled at a public university in northern Saudi Arabia. Methods: Data were collected using a cross-sectional design from 224 nursing students through a self-administered online survey, which comprised three sections: demographic information, students’ perceptions of clinical mentorship quality, and a standardized assessment of leadership competencies. Results: Students reported positive perceptions of their leadership competencies, with an average score of 2.82. A strong positive correlation was observed between mentorship quality and leadership competencies, particularly in strategic thinking, emotional intelligence, influence, and teamwork. Differences were observed based on sex and academic performance, with female students and those with higher GPAs exhibiting stronger leadership competencies. Regression analysis revealed mentorship quality (β = 0.642, p < 0.001) and academic performance (β = 0.131, p = 0.013) as significant predictors of leadership competencies, while gender and academic year were not statistically significant. Conclusions: High-quality clinical mentorship substantially contributes to the development of leadership competencies among nursing students, with academic performance providing additional support. Integrating structured mentorship programs into nursing curricula may enhance preparedness for leadership roles within healthcare settings. Full article

The purpose of the present study is to improve the efficiency of phishing web resource detection through multimodal analysis and using methods of explainable artificial intelligence. We propose a late fusion architecture in which independent specialized models process four modalities and are combined using weighted voting. The first branch uses CatBoost for URL features and metadata; the second uses CNN1D for symbolic-level URL representation; the third uses a Transformer based on a pretrained CodeBERT for the homepage HTML code; and the fourth uses EfficientNet-B7 for page screenshot analysis. SHAP, Grad-CAM, and attention matrices are used to interpret decisions; a local LLM generates a consolidated textual explanation. A prototype system based on a microservice architecture, integrated with the SOC, has been developed. This integration enables streaming processing and reproducible validation. Computational experiments using our own updated dataset and the public MTLP dataset show high performance: F1-scores of up to 0.989 on our own dataset and 0.953 on MTLP; multimodal fusion consistently outperforms single-modal baseline models. The practical significance of this approach for zero-day detection and false positive reduction, through feature alignment across modalities and explainability, is demonstrated. All limitations and operational aspects (data drift, adversarial robustness, LLM latency) of the proposed prototype are presented. We also outline areas for further research. Full article

The development of street-based outdoor physical activities plays a vital role in improving public health issues and advancing the goals of the “Healthy China” initiative, and the built environment is widely considered a key factor in promoting such activities and urban sustainability. Existing studies have paid limited attention to the nonlinear relationships between the built environment and outdoor physical activity and have mostly focused on a single type of activity (such as walking or cycling), with few comparative analyses across different activity types. With the purpose of addressing these limitations and providing cross-sectional empirical evidence for sustainable street design and active-transport policy, this study examines streets within the Second Ring Road of Changsha and uses large-scale street-level outdoor activity trajectory data to investigate associations between built environment indicators and outdoor activity flows. A Random Forest model, followed by the application of SHapley Additive exPlanations (SHAP), is used to characterize the nonlinear associations and interactions among variables, capturing patterns relevant to sustainable mobility, public health and urban form. The results indicate the following: (1) The built environment indicators are associated with walking, jogging, and cycling in distinctly different patterns—walking shows stronger associations with population density and access to bus stops; jogging demonstrates stronger associations with the accessibility of large open spaces; and cycling is more associated with land use mix and road intersection density. (2) Nonlinear associations and threshold-like patterns commonly exist between built environment variables and activity flows, with indicators such as bus stop density and walking continuity exhibiting pronounced effects within specific intervals. (3) Interaction effects among variables contribute importantly to model predictions, especially for jogging where their influence can even exceed the main effects of individual factors. These results underscore the potential value of implementing tailored street design strategies for different activity types and provide empirical evidence relevant to health-oriented urban planning. Full article

Background: Chest X-ray (CXR) imaging is crucial for diagnosing thoracic abnormalities; however, the rising demand burdens radiologists, particularly in resource-limited settings. Method: We used large-scale, diverse public CXR datasets with noisy labels to train general-purpose deep learning models (ResNet, DenseNet, EfficientNet, and DLAD-10) for multi-label classification of thoracic conditions. Uncertainty quantification was incorporated to assess model reliability. Performance was evaluated on both internal and external validation sets, with analyses of data scale, diversity, and fine-tuning effects. Result: EfficientNet achieved the highest overall area under the receiver operating characteristic curve (0.8944) with improved sensitivity and F1-score. Moreover, as training data volume increased—particularly using multi-source datasets—both diagnostic performance and generalizability were enhanced. Although larger datasets reduced predictive uncertainty, conditions such as tuberculosis remained challenging due to limited high-quality samples. Conclusions: General-purpose deep learning models can achieve robust CXR diagnostic performance when trained on large-scale, diverse public datasets despite noisy labels. However, further targeted strategies are needed for underrepresented conditions. Full article

This study investigates the impact of a self-built architectural intervention implemented in three areas, two intervention sites and one control site of a university campus, focusing on how such interventions can influence the use and care of open spaces. Surveys were administered before and after the intervention to a purposive sample of 54 habitual campus users, recruited through peer referrals and contacted via informal channels such as in-person interactions, phone calls, and shared student groups. The surveys were completed anonymously using Google Forms. Data were analyzed using mixed-effects models to evaluate changes over time, across sites, and time x site interaction. Results showed a significant increase over time in participants’ intention to care for the whole campus. Intentions to spend time in outdoor areas varied significantly across sites but did not change over time, and no time × site interaction was detected, indicating that observed changes were not confined to intervention sites. These findings highlight the potential of user-centered design interventions to enhance the quality, accessibility, and usability of open areas by providing empirical insights relevant to urban planning and the management of public spaces. Overall, this research suggests that self-build initiatives within university campuses can serve as scalable models for fostering sustainable urban environments, promoting citizen engagement, and improving urban well-being. Full article

(1) Background: As social infrastructures, cemeteries have always played a central role in various human cultures. The changing function of cemeteries and the recognition of their potential as green spaces have resulted in the fact that cemeteries are a subject of considerable urban planning research. However, there still is a knowledge gap for the case of Vienna. In this study, from the perspective of urban planning and the city of Vienna as an operator of interdenominational cemeteries on the one hand, and of operators of denominational cemeteries on the other hand, consideration of cemeteries in strategic urban planning is discussed, and prospects for the future are outlined. (2) Methods: A qualitative content analysis of relevant strategic planning documents and a qualitative theme-centred stakeholder survey using guideline interviews were conducted. The results were put into the context of the international literature. (3) Results: Cemeteries are an integral part of urban morphology and fabric. Interdenominational cemeteries serve multiple purposes, for example, as places of remembrance, leisure and recreation. In addition, the growing importance of interdenominational cemeteries in particular as green infrastructure for the public is evident. (4) Conclusions: Despite population growth and the associated pressure on land and densification, no changes such as the decommissioning of cemeteries are to be expected in the medium term. Full article

Knowledge-sharing is a deliberate exchange of information to enhance accessibility and reuse which is critical for improving healthcare delivery. This study assessed knowledge-sharing practices among dentists, pharmacists, and allied health professionals (AHPs) in nine public hospitals in South Africa’s Eastern Cape Province. A cross-sectional survey was conducted using purposive and stratified random sampling to recruit 99 participants. Data were collected via a validated questionnaire and analysed with SPSS v.22.0 using descriptive statistics. Respondents were predominantly female (77.6%) and aged 21–35 years (63.6%); AHPs comprised 65.7% of the sample. The results show a statistically significant association between profession and encouragement to adopt a global perspective (p = 0.017), while significant differences were observed between profession and encouragement to seek inter-team solutions (p = 0.020), and access to leadership-driven opportunities for interdisciplinary knowledge-sharing (p = 0.016). Despite observable patterns in the descriptive results, no other statistically significant differences by profession were observed for all other items. Collaboration with external communities and leadership-driven knowledge-sharing opportunities were also highest among dentists but limited overall. Adoption of information systems for knowledge exchange was low, particularly among pharmacists and AHPs. Participation in professional development and recognition of long-term knowledge-sharing strategies followed similar patterns. These findings highlight the need to strengthen leadership-driven opportunities for interdisciplinary knowledge-sharing and to develop targeted interventions to address specific gaps between professions. Full article

Background: Hypermobile Ehlers–Danlos Syndrome (hEDS) results in multiple, complex health-related risks and associated fear of movement (kinesiophobia). Therefore, the purpose of this research study was to examine how a holistic, embodied, and performative movement program (EDS-HEART) can affect body schema, physical and mental health, and lifestyle, which contribute to the joy of movement and physical activity participation among adult women with hEDS. Methods: This was a hermeneutic, phenomenological, quasi-experimental, and community-based research study among six women with hEDS, who participated in the EDS-HEART movement program at a local physical therapy clinic. The seven-week program incorporated stretching and strength training activities as well as performative-thematic movement sequences. Results: Based on the qualitative analysis, three themes emerged regarding reasons for the joy of the EDS-HEART program: (a) improved body schema: body awareness, confidence, posture, and proprioception; (b) highly motivating program: holistic, embodied, performative, pleasant, and safe; and (c) psychosocial reasons: supportive setting, sense of pleasure and euphoria, and freed from social comparisons and the fear of movement. Conclusions: Based on the study results, public health experts should develop and implement easily accessible and holistic movement programs among people with hEDS and similar conditions to improve physical health, psychosocial health, and the joy of movement. Full article