Search Results (75)

Hypertension remains a leading modifiable risk factor for cardiovascular morbidity and mortality. Nonetheless, blood pressure control rates remain suboptimal despite established treatment guidelines and effective pharmacologic therapies. In parallel, artificial intelligence (AI) has rapidly expanded within cardiovascular medicine, demonstrating promising capabilities in disease detection, risk prediction, and clinical decision support. However, most AI applications in hypertension have focused primarily on algorithmic performance rather than real-world implementation or measurable improvements in patient outcomes. This review examines artificial intelligence-driven hypertension management through the lens of quality improvement and prevention of end-organ damage. We summarize current applications of machine learning, deep learning, natural language processing, and imaging analytics in hypertension detection and risk stratification, and critically evaluate their integration into clinical workflows. Particular emphasis is placed on therapeutic inertia, primary care-centered implementation, and the use of AI to support continuous quality improvement frameworks. Beyond blood pressure reduction alone, we explore the potential of AI to identify patients at risk for hypertensive heart disease, heart failure, aortic pathology, renal dysfunction, and cerebrovascular events. We discuss implementation challenges, including external validation, algorithmic bias, workflow integration, and regulatory considerations, which must be addressed to ensure safe and equitable deployment. Artificial intelligence offers the opportunity to transform hypertension management from reactive blood pressure control to proactive organ protection. Critically, AI-driven quality improvement interventions must be evaluated against established non-AI strategies, including pharmacist-led management and team-based care, which provide the benchmarks for demonstrating added clinical value. Achieving this shift will require embedding predictive analytics within structured, outcome-oriented systems of care and rigorously evaluating their impact on cardiovascular morbidity and mortality. Full article

Higher education institutions are expected to cultivate graduates capable of addressing sustainability challenges through innovation, collaboration, and digital competence. However, many business programs struggle to integrate experiential authenticity, intelligent technologies, and collaborative learning into coherent instructional models, limiting students’ intrinsic motivation and sustainability-oriented competence development. This study aims to examine how experiential learning, artificial intelligence-assisted collaborative learning, and team-based learning operate within the Conceive–Design–Implement–Operate instructional framework to influence learning interest and learning satisfaction in a sustainability-oriented business course. Survey data from 217 undergraduate students were analyzed using confirmatory factor analysis, structural equation modeling, and moderated regression analysis. The results indicate that both experiential and AI-supported collaborative learning positively enhance students’ learning interest, which partially mediates their effects on learning satisfaction. Team-based learning strengthens the experiential pathway but does not significantly moderate the AI-assisted pathway. These findings clarify differentiated motivational mechanisms within structured instructional systems and provide theoretical support for designing digitally enhanced sustainability education. Full article

Background/Objectives: Dutch legislation sets requirements for the safe reporting of and learning from incidents. It also specifies the required competence of nurses in using medical technology. However, not all certified homecare nurses are adequately trained in patient safety. Patient safety management is reflected at different levels within homecare organisations. This study aimed to report on initial consensus among homecare nurses on responsibilities in quality and safety management at organisational, team and individual levels. It also explored nurses’ educational needs related to the use of advanced medical technologies (AMTs) in homecare. Methods: An exploratory qualitative study using consensus-oriented member checking was conducted. Building on research into incidents and safety management practices of AMTs, two semi-structured group interviews were conducted online with 11 homecare nurses from across the Netherlands. In a second round, feedback and comments were solicited on the resulting conclusions and statements in writing. Results: Distinguishing between high-risk and low-risk incident reports enhances the efficiency and effectiveness of safety management for AMTs in homecare. Team-based discussions increase the likelihood of incident reporting. Nurses advocate for periodic, mandatory assessments for technical homecare teams, conducted by an external body. They also emphasise individual responsibility for maintaining up-to-date knowledge and skills and taking action accordingly. Conclusions: In this study, key statements on which Dutch technical homecare nurses reached consensus are presented. The results underscore the importance of a safe organisational and team culture for incident reporting, as well as the need for an effective and efficient incident management system at a team level. An effective learning organisation contributes to enhancing patient safety. Full article

(1) Background: The complexity of today’s healthcare system requires the formation of highly cohesive work teams that guarantee safe and high-quality care. Clinical simulation has become established as a pedagogical strategy capable of promoting the collaborative skills of teams of students and healthcare professionals. The objective of this study was to analyze the influence of learning through clinical simulation on group cohesion in nursing student teams. (2) Methods: A pre–post quasi-experimental study without a control group was conducted with final-year nursing students using the short Spanish version of the Group Environment Questionnaire, validated for nursing students. This questionnaire was administered twice, before and after participation in clinical simulation sessions. (3) Results: Clinical simulation significantly increased group cohesion in most items and in all dimensions with moderate to large effect sizes (r > 0.5). The Group Integration-Task (GI-T) dimension showed the greatest improvement after clinical simulation. Although causal relationships cannot be established, the results suggest an association between exposure to clinical simulation and increased group cohesion. (4) Conclusions: Clinical simulation was associated with significant improvements in both task-oriented and social dimensions of group cohesion among nursing students. These findings suggest that clinical simulation may enhance collaboration, communication, and commitment to shared goals within student teams. Future studies including control groups are needed to confirm these associations and further explore the impact of clinical simulation on team performance in both student and healthcare professional contexts. Full article

Background: Rare cancers combine low incidence with high biological heterogeneity and multi-institutional care trajectories. These features make single-center learning structurally incomplete and render pathway fragmentation a dominant driver of preventable harm, variability, and waste. In this context, care quality is best understood as a property of pathway integrity across routing, diagnostics (imaging/biopsy planning), multidisciplinary intent-setting, definitive treatment, and surveillance—rather than as a department-level attribute. Objective: To define a pragmatic, transferable operating blueprint for a rare-cancer Learning Health System (LHS) that turns routine care into continuous, auditable learning under explicit governance, while maintaining claims discipline and protecting measurement validity. Approach: We synthesize an implementation-oriented operating model using the Swiss Sarcoma Network (SSN) as an exemplar. The blueprint couples clinical governance (Integrated Practice Unit logic, hub-and-spoke routing, auditable multidisciplinary team decision systems) with an interoperable real-world-time data backbone designed for benchmarking, pathway mapping, and feedback. The operating logic is expressed as a closed-loop control cycle: capture → harmonize → benchmark → learn → implement → re-measure, with explicit owners, minimum requirements, and failure modes. Results/Blueprint: (i) The model specifies a minimal set of data primitives—time-stamped and traceable decision points covering baseline and tumor characteristics, pathway timing, treatment exposure, outcomes and complications, and feasible longitudinal PROMs and PREMs; (ii) a VBHC-ready, multi-domain measurement backbone spanning outcomes, harms, timeliness, function, process fidelity, and resource stewardship; and (iii) two non-negotiable validity guardrails: explicit applicability (“N/A”) rules and mandatory case-mix/complexity stratification. Implementation is treated as a governed step with defined workflow levers, fidelity criteria, balancing measures, and escalation thresholds to prevent “dashboard medicine” and surrogate-driven optimization. Conclusions: This perspective contributes an operating model—not a platform or single intervention—that enables credible improvement science and establishes prerequisites for downstream causal learning and minimum viable digital twins. By distinguishing enabling infrastructure from the governed clinical system as the primary intervention, the blueprint supports scalable, learnable excellence in rare-cancer care while protecting against gaming, inequity, and inference drift. Distinct from generic LHS or VBHC frameworks, this blueprint specifies validity gates required for rare-cancer benchmarking—explicit applicability (“N/A”) rules, denominator integrity/capture completeness disclosure, anti-gaming safeguards, and escalation governance. These elements are critical in rare cancers because small denominators, high heterogeneity, and multi-institutional pathways otherwise make benchmarking prone to artifacts and unsafe inferences. Full article

Background/Objectives: Primary care faces transformation due to workforce shortages and reform. Italy’s Decree 77/2022 promotes Community Centers and extended care, while postgraduate training in general practice involves early clinical responsibility. In South Tyrol, trainees assume significant patient care duties early in a three-year program. This review examines traditional apprenticeship-based training and explores system-based supervision and AI as strategies for improving quality and safety. Methods: A narrative review synthesized the literature and policy on postgraduate general practice education, supervised autonomy, and AI tools in primary care. Searches used the PubMed and Consensus platforms, focusing on Italian primary care reform and South Tyrol. Evidence was analyzed using SANRA guidance. Results: Evidence consistently indicates that training quality depends less on individual supervisors and more on structured, system-based supervision frameworks, clear entrustment criteria, and supportive organizational contexts. Early supervised clinical autonomy in community-based primary care settings can accelerate competency development without compromising the quality of care when robust supervision and team structures are in place. AI-supported educational tools have the potential to augment feedback, assessment, and learning analytics, especially in settings with limited supervisory capacity; however, current evidence supports their use only as adjuncts to human supervision. Conclusions: Evidence supports system-based, competency-oriented supervision models over traditional apprenticeships in settings characterized by workforce constraints and distributed training sites. Integrated general-practitioner-led primary care settings offer favorable learning environments for postgraduate training, while service-oriented community hubs need careful governance as training sites. Though AI may support supervision, professional oversight remains essential for quality and safety. Full article

Eye tracking has become a central method in human–computer interaction (HCI), supported by advances in sensing technologies and AI-based gaze analysis. Despite this rapid growth, a comprehensive and up-to-date overview of eye-tracking research across the broader HCI landscape remains lacking. This study combines records from Web of Science (WoS) and Scopus to analyse 1033 publications on eye tracking in HCI published between 2020 and 2025. After merging and deduplicating the datasets, we conducted bibliometric network analyses (keyword co-occurrence, co-citation, co-authorship, and source mapping) using VOSviewer and performed a qualitative content analysis of the 50 most-cited papers. The literature is dominated by journal articles and conference papers produced by small- to medium-sized research teams (mean: 3.9 authors per paper; h-index: 29). Keyword and overlay visualisations reveal four principal research axes: deep-learning-based gaze estimation; XR-related interaction paradigms within HCI; cognitive load and human factors; and usability- and accessibility-oriented interface design. The most-cited studies focus on gaze interaction in immersive environments, deep learning for gaze estimation, multimodal interaction, and physiological approaches to assessing cognitive load. Overall, the findings indicate that eye tracking in HCI is evolving from a measurement-oriented technique into a core enabling technology that supports interaction design, cognitive assessment, accessibility, and ethical considerations such as privacy. This review identifies research gaps and outlines future directions for benchmarking practices, real-world deployments, and privacy-preserving gaze analytics in HCI. Full article

This article describes a problem-based learning (PBL) intervention enhanced by a smart classroom environment, which supported online interactions and class activities. The academic experience was centered on the United Nations Sustainable Development Goals (SDGs). Multidisciplinary teams of first-year students worked with private companies on briefs explicitly mapped to the SDGs, where instruction combined coaching sessions, peer feedback, and short videos that scaffolded problem analysis, value proposition design, business-model development, and Minimum Viable Product (MVP) prototyping. Once the student teams completed the activity, a qualitative survey using the Bipolar Laddering (BLA) tool was administered to analyze the suitability of the PBL methodology for the activity. BLA elicits respondent-generated positive and negative poles and associated justifications through open questions; unlike structured questionnaires, it does not condition answers and foregrounds the students’ own categories of meaning. Findings are reported as observed patterns across teams and briefs rather than as claims of impact. The analysis attends to the role of technological scaffolds for first-year university students. The contribution of this research is twofold: (1) providing a replicable course design that situates sustainability and the SDGs in a real-world context, positioning early-stage undergraduates to practice design thinking and entrepreneurial action within an active learning approach; and (2) preserving students’ voices through the BLA tool in an activity that links PBL implementation to SDG-oriented outcomes. Full article

Teachers’ and leaders’ gendered beliefs and practices shape students’ learning experiences, yet Estonian schools lack systematic approaches to address these dynamics. This study explored teachers’ and school leadership team members’ gender beliefs and gender-related practices. The framework was developed based on gender belief system theory, which was adapted to suit the educational context and specific aims of this research. Focus group interviews with four teachers and four leadership team members from one school were conducted using a qualitative abductive research strategy and thematic analysis. The findings revealed themes on gender stereotypes, roles, transgender and gender-diverse students, sexual orientation, students’ interests, and gender-related practices in schools. Teachers and leaders held varying and sometimes contradictory gender beliefs, exhibiting both stereotypical views and awareness of biases. Moreover, they were open to dialogue, with some willing to adjust their views. While perceiving their schools as gender-supportive, they acknowledged broader gender inequality issues and practices. Full article

In response to persistent gaps in pain management competencies among nurses in Saudi Arabian teaching hospitals and similar healthcare settings globally, this manuscript presents a developed and validated action plan designed to support the effective transfer of pain management competencies into clinical practice. The action plan was developed to address the critical need for structured, practical strategies that enhance nurses’ ability to apply pain management knowledge in diverse interdisciplinary environments. The action plan was validated through a rigorous three-round e-Delphi technique involving 12 expert panel members, achieving a 75% consensus on its content and structure. The final validated plan includes clear action statements, implementation methods, designated responsibilities, and defined timeframes. The core action statements focus on the following: (i) motivating nurses to pursue further study; (ii) equipping nursing teams with appropriate pain management tools; (iii) developing content-specific, practice-oriented short training programs; (iv) tailoring training to accommodate different learning styles; (v) using diverse teaching methods; (vi) creating strategies to encourage participation in training; and (vii) promoting the application of acquired knowledge in clinical settings. Adoption and implementation of this action plan by nursing leadership are anticipated to significantly enhance the transfer of pain management competencies, ultimately improving patient outcomes. The plan is adaptable for use in similar healthcare settings worldwide, offering a replicable model for strengthening nursing practice through targeted competency development. Full article

This study investigates the key success factors of IT project management in an emerging, innovation-oriented economy using evidence from Kazakhstan. Drawing on expert interviews and an anonymous enterprise survey, we rank 59 processes across the project life cycle and test three hypotheses concerning the roles of human factors and professional governance. The results confirm broad alignment with success factors commonly reported in mature economies yet reveal a distinctive pattern at earlier maturity stages: team composition, communication, and collaboration have a stronger impact on project success than formal controlling and detailed financial governance. We also identify a substantial gap between the declared importance of success factors and their actual implementation—particularly in integration-stage budgeting, acceptance testing and quality assurance, and lessons-learned practices—highlighting how limited practical experience constrains the adoption of governance routines. The findings refine contingency perspectives on project success by positioning key success factors along a development trajectory in which people-centric capabilities serve as prerequisites for the subsequent effectiveness of “hard” project-management methods. The study advances understanding of the role of IT project management in countries at an early stage of developing an innovation-driven economy. Full article

This study examined the relationship between perceived mother- and father-initiated motivational climate and grit in youth male team sports players. A total of 336 players from five team sports (basketball, football, handball, volleyball, and water polo) completed the Parent-Initiated Motivational Climate Questionnaire-2 and the Short Grit Scale. Multiple linear regressions showed that parental motivational climates explained between 8% and 16% of the variance in grit dimensions (R² = 0.08–0.16, p < 0.001). Specifically, ego-oriented climates (worry-conducive and success-without-effort) was positively associated with consistency of interests (β = 0.20–0.27, p < 0.01), whereas mastery-oriented climates (learning/enjoyment) were negatively associated with this dimension (β = −0.09 to −0.26, p < 0.05). Conversely, both learning/enjoyment- and worry-conducive climates were positively associated with perseverance of effort (β = 0.26–0.37, p < 0.001), while success-without-effort climates had negative associations (β = −0.16, p < 0.01). When analyses were performed by sport, significant models were found for basketball, football, and volleyball (R² = 0.07–0.34, p < 0.05), but not for handball or water polo. These findings underscore the differentiated and context-dependent associations of mothers’ and fathers’ motivational climates on the two dimensions of grit, providing evidence-based insights for parents, coaches, and sport organizations aiming to promote perseverance and long-term engagement in youth sport. By fostering appropriate motivational climates, stakeholder efforts towards more adaptive motivational climates may be tentatively associated with higher grit indicators, thereby contributing to developmental and psychological outcomes relevant to sustained participation in sport. Full article

The integration of project-based learning (PBL) in primary education has proven effective in fostering students’ critical thinking, creativity, collaboration, and problem-solving abilities. When implemented through eLearning platforms, PBL can be enhanced by digital environments that combine pedagogical and technological characteristics supporting interactive learning, personalization, and continuous formative assessment. This study aimed to evaluate the pedagogical-technological characteristics of e-learning platforms relevant to the implementation of PBL in Lithuanian primary education. A multi-stage Delphi study was conducted involving 22 primary school teachers experienced in applying educational technologies and project-based learning. In the initial stages, the research team developed and validated a PBL-oriented evaluation instrument, followed by an expert-based selection and in-depth assessment of eight e-learning platforms available for Lithuanian educational practice. The findings revealed substantial differences in how platforms support the main phases of the PBL process. The highest evaluations were given to LearnLab and SMART Lumio, which demonstrate a balanced integration of pedagogical and technological characteristics aligned with PBL logic, whereas content-oriented platforms such as Moodle showed limited adaptability. The final Delphi round generated expert-informed recommendations for enhancing platform design and pedagogical functionality. The study contributes to the understanding of how e-learning platforms can operationalize project-based learning principles and provides an empirically grounded framework for improving technology-enhanced PBL in primary education. Full article

This paper presents a concept for a Learning Factory (LF) designed for interdisciplinary engineering education. Learning factories are experiential learning environments that bridge the gap between theory and practice while supporting the demands of digital transformation. The proposed LF concept was developed using an integrated approach that assessed stakeholder needs and reviewed institutional infrastructure and capacity. These inputs were triangulated into a concept consisting of five core thematic components: Lean processes as an educational anchor, Enterprise Resource Planning (ERP) systems, Internet of Things (IoT)-based integration, simulation, and physical prototyping. Validation workshops with Small- and Medium-sized Enterprise (SME) managers, academic experts, and students confirmed the perceived relevance of this structure and its potential. The resulting concept focuses on practice-orientated, team-based learning methods that are in line with the principles of Education 4.0. The design sets goals in four key dimensions: educational integration, technological readiness, industrial relevance with SME orientation and flexibility and scalability. These design principles and practical insights can be utilized for future academic implementations of learning factories. Full article

Traditional teaching methods are often far from aligning with professional practice demands. Team-Based Learning (TBL), a variant of Problem-Based Learning, may foster motivation, autonomy, and deeper knowledge acquisition, especially in those educative contexts linked to practical knowledge. The objective of the present research was to explore the impact of a TBL program with digital support on Sport Sciences students’ psychological and learning outcomes. A quasi-experimental design with pre- and post-tests was applied to 68 fourth-year students (mean age = 21.45 ± 1.57 years). The intervention spanned 12 weeks, where the students had to solve specific case studies linked to the theoretical content of the subject and its applicability. Variables measured included motivational climate, satisfaction of basic psychological needs, intrinsic motivation, transversal competences, and academic performance. Significant improvements were observed in task- and ego-oriented climate, autonomy, competence, relatedness, knowledge scores, and competence in scientific searches and academic dissemination (p < 0.05). No significant changes were found in intrinsic motivation or audiovisual material competence. Sex influenced several outcomes, while project marks and prior transversal skills did not. TBL combined with digital tools enhanced learning outcomes and key psychological needs, though intrinsic motivation remained unchanged. Findings highlight the value of active methodologies in higher education, while underscoring the need for long-term, broader studies. Full article