Search Results (4,377)

The present study aimed to analyze the differences in psychopathological symptomatology between men and women who participate in online gambling, as well as to explore the relationship between this symptomatology and different risk profiles. The sample consisted of 382 participants, all university students from a province in Spain, of whom 261 were men (68.3%) and 121 were women (31.7%), with a mean age of 21.8 years (SD = 3.2; range = 18–30 years). Psychopathological symptomatology was assessed using the SAS-45, while gambling risk profiles were determined using an ad hoc questionnaire. The results of the risk profiles were formed by categorizing the SOG-RA Scale scores into non-risk gambler, at-risk gambler, and pathological gambler. The results evidenced that gender and risk profile are determining factors in the manifestation of psychopathological symptoms. It was observed that women tend to internalize their emotional problems, presenting higher levels of depression, anxiety, and interpersonal sensitivity, while men exhibit a greater propensity to externalize their symptoms, manifesting hostility, paranoid ideation, and psychoticism. Furthermore, gamblers with high-risk profiles showed higher scores in both internalizing and externalizing symptoms. Significant correlations were identified between risk profile, psychopathological symptomatology, and cognitive distortions, suggesting the need for comprehensive interventions differentiated by gender. These findings provide valuable information for the design of specific treatments that address the emotional and cognitive needs of problem gamblers, contributing to improving the effectiveness of therapeutic strategies in the context of problem gambling. University gambling is an emerging public health issue with consequences that extend beyond the individual, affecting educational, social, and economic well-being. This study addresses a critical gap by delineating gender-specific psychopathological profiles across gambling risk categories, providing actionable evidence to inform campus-based screening and targeted prevention strategies. The findings underscore the necessity of integrating gender-responsive interventions and upstream measures—such as early detection within student health services and harm-reduction messaging—to effectively mitigate gambling-related harm. Full article

This study synthesizes empirical evidence on AI-supported skill assessment systems in higher vocational education through a systematic review and meta-analysis. Despite growing interest in generative AI within higher education, empirical research on AI-enabled assessment remains fragmented and methodologically uneven, particularly in vocational contexts. Following PRISMA 2020 guidelines, 27 peer-reviewed empirical studies published between 2010 and 2024 were identified from major international and Chinese databases and included in the analysis. Using a random-effects model, the meta-analysis indicates a moderate positive association between AI-supported assessment systems and skill-related learning outcomes (Hedges’ g = 0.72), alongside substantial heterogeneity across study designs, outcome measures, and implementation contexts. Subgroup analyses suggest variation across regional and institutional settings, which should be interpreted cautiously given small sample sizes and diverse methodological approaches. Based on the synthesized evidence, the study proposes a conceptual AI-supported skill assessment framework that distinguishes empirically grounded components from forward-looking extensions related to generative AI. Rather than offering prescriptive solutions, the framework provides an evidence-informed baseline to support future research, system design, and responsible integration of generative AI in higher education assessment. Overall, the findings highlight both the potential and the current empirical limitations of AI-enabled assessment, underscoring the need for more robust, theory-informed, and transparent studies as generative AI applications continue to evolve. Full article

Background: Evidence-based practice (EBP) has become a foundational component of modern healthcare globally. In Saudi Arabia, the understanding and application of EBP by respiratory therapists (RTs) remains underexplored. This study aimed to assess RTs’ behaviors, attitudes, awareness, knowledge, and barriers related to EBP. Methods: A previously validated online questionnaire was distributed to RTs across Saudi Arabia between February and July 2025. The survey collected sociodemographic data and included 14 items assessing behaviors, attitudes, awareness, knowledge, prior formal EBP training, and perceived barriers to EBP implementation. Results: A total of 301 RTs participated, with 290 completing the survey. Most participants (75.2%) held a bachelor’s degree. Overall, respondents demonstrated positive attitudes toward EBP, with more than 60% agreeing that understanding research methods is essential to respiratory therapy practice. The most frequently used resources for clinical decision-making were personal experience (67.3%), expert opinion (65.5%), and national or international guidelines (65.5%). Awareness of core EBP concepts was moderate; approximately 30% of participants reported a good understanding of terms such as “systematic review,” “quality of evidence,” and “risk of bias.” Several barriers to EBP implementation were identified, most commonly limited access to resources (25.2%), insufficient research knowledge and skills (23.8%), and lack of interest (21.0%). Conclusions: RTs in Saudi Arabia generally support EBP principles and use evidence-based resources in clinical decision-making. However, gaps in training, access to resources, and research competency limit full EBP implementation. Targeted strategies, including integrating mandatory EBP education, expanding professional development, and enhancing access to research resources, are recommended. Full article

Health systems face pressure to strengthen resilience against supply chain disruptions while maintaining cost-effective service delivery. This mixed-methods study describes a pilot project that integrated 3D printing services into a Canadian provincial health authority. Quantitative data were derived from internal clinical engineering work orders, where a scenario-based economic analysis compared original equipment manufacturer (OEM) procurement with modelled 3D-printed parts. Using conservative assumptions, selected non-electronic structural parts were assigned a fixed unit cost. Qualitative data were collected from two focus groups with clinical engineers and other end-users. Results from an exploratory scenario-based economic analysis suggest that substituting selected structurally simple clinical engineering parts with 3D-printed alternatives would be associated with modelled cost impacts ranging from a 67.4% net increase (OEM prices halved and 3D-printing costs doubled) to a 69.6% cost reduction (OEM prices increased by 10% and 3D-printing costs decreased by 20%). Demand changes affected absolute savings but not the percent difference (58.1% under ±50% quantity changes), and a pessimistic procurement scenario (OEM prices decreased by 30% and 3D-printing costs increased by 50%) reduced savings to 10.3%. Focus groups highlighted perceived benefits and implementation challenges associated with integrating additive manufacturing. Implementation was facilitated through an outsourcing model, which was perceived to shift certain responsibilities and risk-management functions to the vendor. Long-term adoption will require clearer communication and targeted education. This pilot study suggests that, under constrained regulatory scope and scenario-based assumptions, additive manufacturing may contribute to supply chain resilience and may be associated with modelled cost advantages for selected low-risk components. Full article

The growing emphasis on inclusive education highlights teachers’ attitudes and self-efficacy as interrelated yet distinct correlates of inclusive teaching. Building on prior literature that underscores their conceptual proximity, this study aimed to examine how teachers’ views on inclusion relate to their self-reported intentions and perceived self-efficacy for inclusive teaching. Given the cross-sectional, self-report design, the study addresses associations among attitudes, perceived self-efficacy, and intentions, rather than enacted inclusive practice. A cross-sectional survey was conducted with 323 Greek secondary special education teachers using three validated and culturally adapted instruments: the Attitudes toward Inclusive Education Scale (AIS), the Inclusive Classroom Teaching Intentions Scale (ITICS), and the Teacher Efficacy for Inclusive Practices Scale (TEIP). Pearson correlation analyses revealed strong within-instrument associations, indicating good internal coherence, and moderate cross-instrument associations, suggesting meaningful but not redundant relationships between attitudes, intentions, and self-efficacy. To further explore the latent structure, an Exploratory Factor Analysis (EFA) of AIS, ITICS, and TEIP items yielded a four-factor solution explaining 56.14% of the variance: Attitudes toward Inclusive Education, Intentions to Teach in Inclusive Classrooms, Self-efficacy for Behavior Management, and Self-efficacy for Collaboration and Professional Support. This study advances the field by clarifying how teachers’ attitudes, self-efficacy, and intentions covary, thereby informing the development of more targeted and theoretically grounded interventions. Full article

Background: Emergency radiology often demands rapid integration of clinical cues, biochemical markers, and imaging findings to support time-critical diagnostic reasoning. However, educational resources that explicitly structure this interdisciplinary integration particularly between radiology and laboratory medicine remain limited. Objective: Our objective was to develop an Integrated Radiology–Biochemistry Diagnostic Flow Framework as a simulation-based methodological proof-of-concept and to document its structure, logic pathways, and internal consistency across common emergency presentations. Methods: We designed an algorithmic framework combining (i) clinical triggers, (ii) targeted biochemical markers with predefined threshold and trajectory rules, (iii) imaging indication and modality selection (US/CTA/MRI/NCCT), and (iv) key radiologic patterns linked to escalation pathways. No patient data or human participants were included. Instead, forty fully synthetic emergency scenarios were generated to populate the framework and to examine logical completeness, branching coherence, and red-flag escalation routes. Results: The framework yielded scenario-specific diagnostic flowcharts that systematically connect biochemical escalation cues with imaging selection and expected imaging findings. The synthetic scenario library demonstrated consistent branching logic across conditions and enabled transparent visualization of imaging-centered decision pathways suitable for simulation-based teaching and structured case discussion. Conclusions: This study reports a reproducible methodological proof-of-concept framework and a synthetic emergency scenario library. Further learner-based studies are required to evaluate usability, perceived realism, and educational effectiveness in authentic training settings. Full article

Background: Intimate partner violence (IPV) represents a major public health problem in Europe, with significant physical, psychological, and social consequences. Nurses are often the first professionals capable of detecting early signs of IPV, yet they lack validated instruments to assess their clinical competency in detection, evaluation, documentation, and intervention. This study aimed to develop and validate the Intimate Partner Violence Nursing Competency Scale (IPVNCS), aligned with the Nursing Intervention Classification (NIC 6403). Methods: A cross-sectional psychometric study was conducted among registered nurses in the Community of Madrid. A 30-item Likert-type self-administered instrument (1–5 scale) was developed based on NANDA, NIC 6403, and NOC frameworks. A total of 202 nurses participated. Reliability was assessed through Cronbach’s alpha. Construct validity was examined using exploratory factor analysis (EFA) with Promax rotation and confirmatory factor analysis (CFA) using AMOS 26. Ethical approval was obtained (CEU San Pablo, code 843/24/104). Results: After item refinement, 26 items remained across four dimensions: (1) Intervention and Referral, (2) Detection and Assessment, (3) Documentation and Recording-keeping, (4) Psychosocial Support. The instrument showed excellent reliability ($\alpha$ = 0.97). KMO was 0.947 and Bartlett’s test was significant (p < 0.001). CFA demonstrated satisfactory fit: ${\chi }^2$/df = 2.066, RMSEA = 0.073, CFI = 0.92, TLI = 0.91, NFI = 0.86. The final model adequately represented the latent structure. After debugging, its psychometric properties were significantly improved. Four redundant items were eliminated, achieving internal consistency ($\alpha$ = 0.97), a KMO value of 0.947 and a significant Bartlett’s test of sphericity. It showed a better fit, according to ${\chi }^2$/df = (2.066); Parsimony = (720.736); RMR (0.0529; RMSEA (0.073); NFI (0.860); TLI (0.910) and CFI (0.920). The final model provides an adequate representation of the latent structure of the data. This study provides initial evidence of construct validity and internal consistency reliability of the IPVNCS. Conclusions: The IPVNCS is a valid and reliable tool to assess nursing competencies for clinical management of IPV. It supports structured evaluation across four core nursing domains, enabling improved educational planning, clinical decision-making, and quality of care for victims. The scale fills a gap in clinical nursing assessment tools and can support protocol development in emergency, primary care, and hospital settings. Full article

Researching teachers’ 21st-century competences is critical for developing a sustainable, quality educational environment and accomplishing the objective of quality education. A lifelong learning philosophy ensures teacher development, paving the way for quality education (SDG4). In this study, a valid and reliable scale was established to provide the target group of middle school teachers with 21st-century abilities to enhance their quality teaching process and long-term professional growth. In this context, the developed scale has 33 items. The factor analysis results revealed that the scale is three-dimensional and accounts for 63.66% of the overall variation. Furthermore, second-order confirmatory factor analysis confirmed that the proposed model satisfied the acceptable fit criteria. Positive correlations between factors were observed, and reliability analysis revealed a high internal consistency (α = 0.947), thereby validating the scale’s reliability, validity, and practical utility. In conclusion, the scale developed is a valuable assessment tool for assessing teachers’ 21st-century skills, and the data gathered from it can help improve secondary teacher quality and create professional development programs. In this regard, contributions will be made to the development of long-term policies. Teacher development should be considered critical to achieving “quality education”, which is one of the Sustainable Development Goals. Full article

Background and Aim: Large language models (LLMs) demonstrate significant potential in assisting with medical image interpretation. However, the diagnostic accuracy of general-purpose LLMs on image-based internal medicine cases and the added value of brief clinical history remain unclear. This study evaluated three general-purpose LLMs (ChatGPT, Gemini, and DeepSeek) on expert-curated cases to quantify diagnostic accuracy with image-only input versus image plus brief clinical context. Methods: We conducted a comparative evaluation using 138 expert-curated cases from Harrison’s Visual Case Challenge. Each case was presented to the models in two distinct phases: Phase 1 (image only) and Phase 2 (image plus a brief clinical history). The primary endpoint was top-1 diagnostic accuracy for the textbook diagnosis, comparing performance with versus without a brief clinical history. Secondary/Exploratory analyses compared models and assessed agreement between model-generated differential lists and the textbook differential. Statistical analysis included Wilson 95% confidence intervals, McNemar’s tests, Cochran’s Q with Benjamini–Hochberg correction, and Wilcoxon signed-rank tests. Results: The inclusion of clinical history substantially improved diagnostic accuracy for all models. ChatGPT’s accuracy increased from 50.7% in Phase 1 to 80.4% in Phase 2. Gemini’s accuracy improved from 39.9% to 72.5%, and DeepSeek’s accuracy rose from 30.4% to 75.4%. In Phase 2, diagnostic accuracy reached at least 65% across most disease nature and organ system categories. However, agreement with the reference differential diagnoses remained modest, with average overlap rates of 6.99% for ChatGPT, 36.39% for Gemini, and 32.74% for DeepSeek. Conclusions: The provision of brief clinical history significantly enhances the diagnostic accuracy of large language models on visual internal medicine cases. In this benchmark, performance differences between models were smaller in Phase 2 than in Phase 1. While diagnostic precision improves markedly, the models’ ability to generate comprehensive differential diagnoses that align with expert consensus is still limited. These findings underscore the utility of context-aware, multimodal LLMs for educational support and structured diagnostic practice in supervised settings while also highlighting the need for more sophisticated, semantics-sensitive benchmarks for evaluating diagnostic reasoning. Full article

The natural polypeptide drug hirudin, a direct thrombin inhibitor, exhibits potent anticoagulant, anti-myocardial fibrotic, and anti-inflammatory effects in the treatment of cardiovascular diseases (CVD), but its clinical application remains limited by its low bioavailability, insufficient targeting capability, and bleeding risk. In recent years, the development of nanotechnology has enabled peptide drug delivery systems to demonstrate substantial promise in medical practice. Significant progress has been made in overcoming limitations and enhancing therapeutic efficacy against CVD through the use of Hirudin-based drug delivery systems by addressing drug stability in vivo, improving targeting ability, and ultimately achieving responsive release. This paper systematically reviews the mechanisms of action, clinical applications, and novel delivery strategies of the peptide drug hirudin in the treatment of CVD, with a particular focus on recent advances in hirudin-based drug delivery systems, and it also looks forward to future research directions for hirudin delivery systems, including the development of scalable intelligent carriers, the construction of real-time feedback systems, and the establishment of standardized in vitro and in vivo evaluation systems, aiming to present novel strategies for safe and efficient treatment of CVD. Full article

This study examines the systemic integration of entrepreneurship education and the culture of self employment within higher education as a component of sustainable institutional reform. Using a comparative analytical approach, it analyzes international practices across five higher education systems. Finland, the United States, Canada, the United Kingdom, and South Korea were selected to represent diverse yet mature models of entrepreneurship education integration. The findings reveal significant variation in the depth and coherence of integration across national contexts. Rather than identifying a single transferable model, the study shows that effective integration depends on the interaction of key institutional dimensions, including policy alignment, curricular embedding, faculty capacity, infrastructure, external partnerships, and impact evaluation. Finland demonstrates the most coherent configuration, while other systems exhibit partial or fragmented integration shaped by contextual factors. The study concludes that entrepreneurship education is most sustainable when embedded as a system-level institutional strategy rather than implemented through isolated initiatives. It offers an analytical framework, supported by an adapted ADKAR change model, to guide context-sensitive reform. For Arab higher education systems, the primary implication is diagnostic, emphasizing contextual adaptation over direct replication. Full article

Dogs increasingly function as relational beings, shaping their guardians’ emotional well-being and daily routines. Consequently, dog owner education has expanded beyond behaviour-focused training toward integrative approaches that address the emotional, relational, and cognitive dimensions of the human–dog relationship. Despite this shift, international comparative research on the organisation and institutionalisation of dog owner education remains limited. The study applies a qualitative exploratory comparative case study to examine systems in the United States, the United Kingdom, Germany, Japan, and Australia, identifying national patterns and shared components to inform context-appropriate frameworks, particularly in South Korea. The study examines legal and policy documents, institutional guidelines, and standardised education programmes that function as national or de facto standards using document and content analysis. It integrates within- and cross-case comparisons and interprets findings through a framework drawing on human–animal interaction, attachment, canine behaviour, and cognitive–behavioural coaching theories. The analysis reveals five shared components of behaviour change: guardian responsibility and animal welfare, science-based positive reinforcement, early socialisation and prevention, a balance between standardisation and individualisation, and guardians’ emotional and relational engagement. These findings suggest that dog owner education functions as an integrated system that supports responsible guardianship and stable human–dog relationships across sociocultural contexts. Full article

Teacher education represents a global strategic priority for improving educational systems and fostering inclusive, high-quality processes. Recent studies highlight the need for systematic and replicable education models capable of addressing the challenges of contemporary complexity and bridging the gap between theory and practice. Teaching professionalism is increasingly recognized as a key driver of change, requiring a balance of pedagogical, relational, and technological competences, along with strong reflective capacity. Within this framework, practicum programs play a crucial role for the development of professional identity and authentic teaching skills. Methods: This contribution adopts a theoretical–argumentative approach grounded in a critical analysis of the international scientific literature on teacher education, with specific focus on the role of practicums. The aim is to present the model implemented by Pegaso University in the context of practicum activities within initial teacher education programs to outline an interpretative framework and provide pedagogical reflections in light of the results arising from critical reflection and systematic monitoring (not covered in this specific contribution) of the effectiveness of the model implemented in the first two training cycles (academic years 23–24 and 24–25), with the involvement of 5 regions and a total of 2834 teachers in the first cycle and 10 regions and a total of 5551 teachers in the second cycle. Convenience sampling based on a non-probabilistic method was adopted, using the entire sample of teachers admitted to the training program who met the requirements of Article 7 of the Decree of the President of the Council of Ministers (DPCM). Results: This paper outlines the theoretical and methodological trajectories of the model, offering interpretative frameworks and pedagogical reflections in light of the outcomes achieved during the initial implementation phase. Conclusions: In accordance with recent national and European regulatory frameworks, the Pegaso teaching model is presented as an example of good practice for initial teacher education. It aims to foster a reflective, situated, and responsible teaching professionalism, moving beyond traditional approaches toward a continuous and transformative learning process. Full article

This article introduces a framework for scientific and professional language training tailored for STEM (Science, Technology, Engineering and Mathematics) specialists, emphasising the integration of digital technologies and artificial intelligence (AI) in language education. The framework aims to develop students’ research communication skills and digital competencies, which are essential for effective participation in both national and international scientific discourse. The article discusses contemporary trends in STEM education, emphasising the importance of interdisciplinary approaches, project-based learning, and the utilisation of digital tools to boost language skills and scientific literacy. The article outlines the development and deployment of a digital platform aimed at supporting personalised and adaptive learning experiences, integrating various educational technologies and approaches. Empirical research conducted through a pedagogical experiment demonstrates the effectiveness of the framework, showing significant improvements in students’ academic and linguistic competencies across multiple modules. The findings highlight the importance of combining language training with STEM education to equip future engineers for the challenges of a globalised and digitalised professional world. This work reports on the “Enhancing Scientific and Professional Language Learning for Engineering Students in Kazakhstan through Digital Technologies” project conducted at Saginov Technical University (STU) in Kazakhstan and funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19678460). The research contributes to the ongoing discussion on improving language teaching in STEM fields, offering a framework that aligns with current educational demands and technological progress. Full article

This study diagnoses the level and profile of university lecturers’ digital competence at a Chilean higher education institution, drawing on the DigCompEdu and OpenEdu frameworks. A non-experimental correlational design was used, based on a self-perception questionnaire adapted from the DigCompEdu Check-In tool and administered to 569 lecturers through the Qualtrics platform. The instrument underwent external expert validation and demonstrated excellent internal consistency (Cronbach’s α = 0.96). Results indicate that 44% of lecturers position themselves at the “Integrator” level, 22% at the “Explorer” level, and 19% at the “Expert” level, with three clearly differentiated competence profiles. These findings informed the development of a structured training programme centred on three components: the pedagogical use of digital technologies, the incorporation of open educational practices aligned with OpenEdu, and the strengthening of students’ digital competence. The programme includes modular workshops, mentoring led by high-competence lecturers, and the creation of open educational resources. Overall, the study provides empirical evidence to guide institutional policies and to foster a reflective, ethical, and pedagogically grounded integration of digital technologies in university teaching. Full article