Search Results (9,365)

Background: Statins are among the most frequently prescribed medications worldwide, with proven benefits in reducing all-cause and cardiovascular mortality, preventing major adverse cardiovascular events (MACEs), and lowering healthcare costs. Despite their well-established safety and effectiveness, discontinuation of statin therapy remains a common problem in both primary and secondary prevention. Methods: A systematic literature review was conducted in accordance with PRISMA guidelines and registered in the PROSPERO database (CRD420261295172). Original studies published since 1 January 2014 were identified through searches of PubMed (MEDLINE) and Google Scholar using predefined keywords. Methodological quality and risk of bias of the included observational studies were evaluated using the Newcastle-–Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) Critical Appraisal Tools. Results: Synthesized data from 29 included studies indicate that up to half of patients discontinue statin therapy within the first year (discontinuation rates ranging from 27.1% to 47.0% in primary prevention and 18.5% to 32.4% in secondary prevention), with rates increasing over time. Major factors contributing to non-adherence include fear of side effects, particularly statin-associated muscle symptoms (SAMSs), misinformation, limited patient–physician communication, socioeconomic barriers, and polypharmacy. Discontinuation is associated with significantly higher all-cause and cardiovascular mortality (Hazard Ratios ranging from 1.30 to 4.65), higher rates of cardiovascular and cerebrovascular events, worsening metabolic outcomes, reduced quality of life, and greater healthcare expenditures. Conclusions: Improving adherence requires better patient education, addressing misconceptions, strengthening patient–physician relationships, and optimising treatment regimens. A multidisciplinary approach is needed to prevent unjustified discontinuation and improve long-term clinical outcomes. Full article

The transition from high school to university is a critical developmental period marked by substantial academic, social, and lifestyle changes that may increase vulnerability to academic difficulties, disengagement, and dropout. Given the importance of academic achievement for student retention and long-term success and the growing recognition of sleep as a modifiable determinant of academic performance, this scoping review examined how the relationship between sleep and academic achievement has been investigated among first-year university students. Following PRISMA guidelines, a systematic search identified 20 records representing 21 studies published between 2013 and 2026. Sleep duration and sleep quality were the most frequently examined domains, although findings were heterogeneous. Nevertheless, shorter sleep duration, particularly below 6–7 h per night, was generally associated with poorer academic achievement. Poor sleep quality was also linked to lower academic performance in some studies, with affective factors influencing this relationship. Sleep problems, including chronic sleep deprivation and risk of sleep disorders, showed consistent associations with poorer academic outcomes. Similarly, an evening chronotype was generally associated with poorer academic performance and adjustment. These findings emphasize sleep as an essential target for future research and initiatives aimed at promoting academic success and student retention during the transition to higher education. Full article

Background and Objectives: Rising malpractice litigation and the strengthening of patient-rights legislation have changed the way hospital staff approach informed consent and legal risk. This study aimed to (i) assess the distribution of informed-consent knowledge, malpractice anxiety, and defensive practice across professional and departmental groups; (ii) identify independent predictors of high defensive practice; and (iii) evaluate experience-related moderation of the legal-literacy–anxiety association and predictor consistency across defensive-practice severity. Methods: We conducted a cross-sectional survey of 146 healthcare workers (physicians, nurses, midwives, and allied health professionals) from four departments of a tertiary academic hospital network, using a 46-item pilot-tested instrument measuring informed-consent knowledge (0–20), malpractice anxiety (0–100), and defensive-practice behaviors. Results: Physicians showed higher informed-consent knowledge than nurses (14.1 vs. 12.0 points, p < 0.001) but also higher malpractice anxiety (63.4 vs. 57.6, p = 0.015). High defensive practice was associated with a prior malpractice claim (adjusted odds ratio 3.24), surgical specialty (2.47), low consent literacy (2.21), physician role (2.10), and knowing a sued colleague (1.88). Anxiety was highest in emergency medicine; predictors also operated across ordered defensive-practice severity, and the legal-literacy–anxiety association was stronger at lower experience (interaction p = 0.023). Conclusions: Knowledge, anxiety, and defensive practice were unevenly distributed; defensive practice reflected professional context and direct or vicarious litigation exposure, while the legal-literacy–anxiety association varied with experience. Medico-legal education may therefore be best paired with structured consent procedures and experience-sensitive support; larger multi-center studies are needed. Full article

Arabic-speaking populations face disproportionate cybersecurity risks due to the predominantly English-centric design of existing awareness materials, which fail to accommodate Arabic dialectal diversity, script complexity, and culturally embedded communication patterns. These deficiencies impair users’ ability to interpret phishing messages, authentication requests, and security alerts, increasing susceptibility to social engineering, identity theft, and data breaches. This paper presents SECURE-A²RC, a rubric-constrained, Arabic-aware large language model framework designed to deliver scalable, interpretable, and culturally relevant cybersecurity education. The framework comprises two coupled components. The first, the Arabic-Aware Secure Communication Encoder (A-SCE), employs an instruction-tuned LLM to produce multidimensional encodings that capture three learner competencies: security intent comprehension; linguistic deception cue recognition encompassing urgency, authority impersonation, and incentive framing; and action-critical translation fidelity across Arabic dialectal registers and Arabic–English bilingual contexts. The second, the Rubric-Constrained Adaptive Feedback Generator (RCAFG), translates A-SCE encodings into personalized, expert-aligned instructional feedback and proficiency-calibrated adaptive tasks, ensuring pedagogical consistency, security correctness, and dialect awareness throughout the learning cycle. The framework is evaluated on three domain-relevant corpora: the English–Arabic Parallel Phishing Email Corpus, the Open MalSec dataset, and the Arabic Spam and Ham Tweets dataset. SECURE-A²RC achieves a 31% improvement in phishing identification accuracy and a 26% reduction in action-critical translation errors compared to conventional awareness materials. A comparative evaluation against SERENA, a Multi-Agent LLM, and the Arabic Multitask Learning Model confirms consistent superiority across detection accuracy, F1-score, dialectal robustness, and educational effectiveness metrics, affirming rubric-constrained LLM integration as a viable approach to equitable multilingual cybersecurity education. Full article

Background: School violence is a major public health concern, with bullying alone affecting up to 50% of adolescents worldwide. Life skills-based programs have been proposed as a promising preventive approach, yet evidence for their effectiveness in secondary education remains limited. This systematic review and meta-analysis aims to synthesize the existing evidence on the effectiveness of life skills-based violence prevention programs among adolescents aged 12–18. Methods: A systematic literature search was conducted across five databases (PubMed, Scopus, ERIC, CINAHL, and PsycInfo) in accordance with PRISMA 2020 guidelines (INPLASY202650168). Interventional studies published between 2005 and 2025 that targeted secondary school students were eligible. Risk of bias was assessed using the Cochrane RoB2 (for RCTs/cRCTs) and ROBINS-I tools. A three-level random-effects meta-analytic model with Robust Variance Estimation was employed to pool Hedges’ g effect sizes. Results: Nineteen studies met the eligibility criteria, with 18 contributing 56 effect sizes to the meta-analysis. The pooled effect size was statistically significant (g = −0.2652, 95% CI [−0.4879, −0.0425], p = 0.0196), indicating an overall small reduction in violent behaviors. However, a high degree of variation in effects was observed across studies (Q(55) = 2263.58, p < 0.001; I² = 99.23%). None of the examined moderators—including outcome type, study design, and risk-of-bias tier—significantly explained this heterogeneity. The sensitivity analysis, excluding one highly influential study, yielded a smaller pooled effect (g = −0.1422, 95% CI [−0.2246, −0.00598]) while maintaining high heterogeneity (I² = 92.82%). Conclusions: Although life skills-based programs demonstrate a statistically significant overall average effect in reducing school violence among adolescents, this finding must be interpreted with extreme caution given the high degree of variation in effect sizes across contexts and the fact that prediction intervals span across zero. Because moderator analyses revealed no significant differences across intervention types, study designs, or outcome categories, no specific program type can be identified as consistently more effective. Future primary research must prioritize prospectively registered trials with multi-informant assessments to establish true intervention effectiveness. Full article

Archaeological sites are fragile, non-renewable heritage environments where visitors’ inappropriate behavior may cause irreversible damage. This study designed and evaluated a VR serious game, Guarding the Terracotta Warriors, to promote visitors’ responsible visiting behavior intention at archaeological sites. Examining the Terracotta Warriors Museum as a case study, this study identified conservation needs through literature and case analysis, expert interviews, and preliminary visitor interviews, and translated them into four design requirements: path guidance for visiting boundaries, reflection on visiting order, contextualized risk decisions, and concrete feedback on behavioral consequences. Based on the MDA framework, these requirements were further transformed into interactive game mechanisms. A within-subject experiment with 46 participants compared the VR serious game with conservation-content-matched video instruction, followed by semi-structured interviews with 20 participants. Quantitative results showed that the VR serious game produced significantly higher scores than video instruction in presence, experience satisfaction, conservation-related attitude, awareness of consequences, personal norms, and responsible visiting behavior intention. Task load was slightly higher in the VR condition, but its mean score remained below the midpoint of the seven-point scale, indicating a relatively modest level of perceived task load. Qualitative findings further indicated that embodied exploration, safe-to-fail risk decisions, visitor-order feedback, and irreversible restoration feedback helped participants understand conservation boundaries and behavioral consequences. This study provides a design framework and empirical evidence for using VR serious games to support responsible visitor education at archaeological sites. Full article

Higher education institutions operate complex digital environments that combine administrative services, research infrastructures, learning platforms, identity systems, and heterogeneous departmental IT. In the European Union, the NIS2 Directive increases the need for structured cybersecurity governance, while ISO/IEC 27001:2022 provides a mature information security management system standard that can support implementation. This paper proposes a design science artefact for aligning NIS2 obligations with ISO/IEC 27001:2022 clauses and Annex A controls in the context of higher education institutions. The framework organizes cybersecurity governance, asset and service scoping, risk management, incident handling, business continuity, supplier and cloud dependencies, access control, awareness, monitoring, and continual improvement into a staged maturity model. The artefact is instantiated for a Romanian public university context and assessed through internal traceability analysis, including mappings between NIS2 Articles 20, 21, and 23, Romanian NIS2 transposition requirements, and ISO/IEC 27001:2022 control areas. The institutional illustration identifies candidate assessment domains and evidence requirements but does not assign maturity levels because the internal records required by the scoring protocol were unavailable; it therefore does not constitute an audit, verified institutional measurement, or empirical validation. The contribution is therefore a structured and reusable compliance design artefact, together with a transparent mapping method that can support future expert validation, institutional pilots, and audit-oriented refinement. Full article

The rapid adoption of Generative Artificial Intelligence (GenAI) is transforming higher education by reshaping learning experiences, student engagement, and creativity. However, little is known about the mechanisms through which GenAI enhances creativity, particularly within tourism and hospitality education. Unlike prior studies that primarily examine students’ intention to adopt GenAI, this study explains how GenAI adoption translates into creativity through enhanced learning and learning engagement while accounting for ethical risks. Drawing upon contemporary learning and creativity literature, this study examined how students’ adoption of GenAI influences creativity through the mediating roles of enhanced learning and learning engagement, while also investigating the moderating effect of perceived ethical risks associated with GenAI use. Data were collected from 420 students enrolled in tourism and hospitality faculties and institutes across Egypt. The proposed research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that enhanced learning and learning engagement are the principal mechanisms through which GenAI adoption improves students’ creativity, whereas perceived ethical risks significantly weaken these positive relationships. This study contributed to the emerging GenAI literature by moving beyond technology adoption perspectives to explain how GenAI shapes creativity outcomes in higher education. It further extends tourism and hospitality education research by providing one of the first empirical examinations of the mechanisms through which GenAI enhances student creativity while accounting for ethical concerns. The findings provide practical guidance for higher education institutions seeking to integrate GenAI responsibly while fostering creativity, engagement, and innovative learning environments. Full article

The overall prevalence of dyslipidemia among adults continues to rise. However, limited attention has been devoted to the association between free sugar intake and dyslipidemia. This study aimed to explore the association between free sugar intake and dyslipidemia, as well as its subtypes, in Chinese adults. A total of 38,656 adults from the Chinese Food Consumption Survey (CFCS) and 3974 from the China Health and Nutrition Survey (CHNS) were included in the final analysis. Dietary intake data were collected by 24 h dietary recalls and the weighing of household foods and condiments. For the CHNS, multivariable Cox proportional hazards regression models were used to examine the association between free sugar intake and the risk of dyslipidemia and its subtypes. Restricted cubic spline (RCS) regression was used to evaluate the nonlinear relationship between free sugar intake and dyslipidemia. Stratified analyses and interaction tests were performed across key covariates to explore potential effect modifiers of the association between free sugar intake and dyslipidemia risk. For the CFCS, the mean free sugar intake among Chinese adults was 6.4 g/d. For the CHNS, a total of 1052 individuals were diagnosed with dyslipidemia, corresponding to an incidence rate of 26.5% during a total of 24,531 person-years of follow-up (median follow-up, 6.0 years) in the CHNS cohort. After multivariable adjustment, the risk of dyslipidemia was increased by 38% with >20 g/d free sugar intake (HR = 1.38, 95% CI: 1.04–1.84, p for trend = 0.006), with <5 g/d free sugar intake as a reference. For different subtypes of dyslipidemia, with <5 g/d free sugar intake as a reference, the risk of hypo-HDL-cholesterolemia and hyper-LDL-cholesterolemia was increased by 91% (HR = 1.91, 95% CI: 1.34–2.74, p for trend < 0.001) and 52% (HR = 1.52, 95% CI: 1.01–2.29, p for trend = 0.004) with > 20g/d free sugar intake, respectively. Stratified analyses demonstrated that the impact of high free sugar intake on the development of hypo-HDL-cholesterolemia and hyper-LDL-cholesterolemia was significantly amplified among urban residents and those with insufficient physical activity. While linear dose–response associations were observed between free sugar intake and the risk of dyslipidemia (p for nonlinearity > 0.05), a nonlinear, inverted U-shaped association emerged for hyper-LDL-cholesterolemia (p for nonlinearity = 0.007). Our study demonstrates that free sugar intake levels in Chinese adults were relatively low compared to the recommended intake level (<50 g/d) in the Chinese Dietary Guidelines 2022. Nevertheless, increased free sugar intake was positively associated with a higher risk of incident dyslipidemia, as well as incident hypo-HDL-cholesterolemia and hyper-LDL-cholesterolemia. Targeted nutrition education is recommended to promote balanced dietary patterns and enhance overall dietary quality, thereby effectively reducing the risk of dyslipidemia. Full article

Background/Objectives: Older adults residing in long-term care facilities (LTCFs) are at increased risk of poor oral health because of functional dependence and limited access to professional oral healthcare. Although oral healthcare education programs for care workers improve knowledge and performance, evidence of their effects on residents’ biological oral health outcomes remains limited. This study evaluated the effects of a care worker-centered oral healthcare program on oral inflammatory status in LTCF residents using salivary interleukin-1 beta (IL-1β) as an objective biomarker. Methods: A single-group pretest–posttest quasi-experimental study was conducted in two LTCFs in the Republic of Korea. Forty care workers completed a structured oral healthcare education program and provided daily oral healthcare to residents for 4 weeks. Saliva samples were collected before and after the intervention, and salivary IL-1β concentrations were measured using enzyme-linked immunosorbent assay. Changes in IL-1β concentrations were analyzed using the Wilcoxon signed-rank, Mann–Whitney U, and Kruskal–Wallis tests. Results: Thirty-seven residents completed the study. Median salivary IL-1β concentrations significantly decreased from 19.33 pg/mL (interquartile range [IQR], 11.49–34.66) at baseline to 10.78 pg/mL (IQR, 0.65–33.64) after the intervention (Z = −3.764, p = 0.001). Greater reductions were observed among residents with greater functional dependence, whereas limited communication ability or oral care refusal was associated with minimal improvement. Conclusions: A care worker-centered oral healthcare program significantly reduced salivary IL-1β concentrations among older adults residing in LTCFs. Findings support care worker training and highlight the use of salivary IL-1β as an objective biomarker for evaluating oral healthcare interventions. Full article

The rapid diffusion of generative artificial intelligence (GenAI) tools such as ChatGPT has unsettled established academic practices related to assessment, authorship, integrity, and disciplinary knowledge production. This qualitative repeated cross-sectional study examines how faculty and staff at a large public research university understood these changes in 2023 and 2024. The analysis draws on responses to the same open-ended survey question collected from independent respondent groups in 2023 (n = 104) and 2024 (n = 313). Responses were analyzed inductively through thematic analysis and subsequently interpreted using Disruptive Innovation Theory and Complex Adaptive Systems Theory. The analysis identified both continuity and change across the two datasets. Responses in 2023 emphasized uncertainty, threats to academic integrity, and defensive assessment redesign. Responses in 2024 more frequently described pedagogical experimentation, process-oriented assessment, and AI literacy as emerging academic and professional competencies. Concerns about authorship, equity, reliability, and inconsistent institutional guidance persisted across both years. The findings suggest that faculty and staff discourse shifted from primarily containing GenAI-related risks toward selectively integrating the technology into teaching and professional practice. However, because the study used independent cross-sectional samples, it does not establish individual change over time. The study contributes a theoretically informed account of institutional sensemaking during the first two years following ChatGPT’s public release and identifies strategies for balancing innovation, integrity, equity, and the human purposes of higher education. Full article

The diffusion of generative artificial intelligence has moved educational debate beyond access to new tools, placing teacher work, pedagogical mediation, assessment, and digital competence under renewed pressure. This article examines teachers’ perceptions, declared uses, and forms of engagement with generative AI in Gymnasien (academic-track secondary schools) and Gesamtschulen (comprehensive secondary schools) in North Rhine-Westphalia, Germany. The study is based on an anonymous and voluntary online questionnaire circulated through school leaderships. The operational database comprised 204 records, while the main analysis was based on 156 completed questionnaires. Closed-item responses were examined through descriptive statistics and interpreted through DigCompEdu and its AI-related supplement. The findings indicate an asymmetrical incorporation of generative AI across teachers’ work. Its presence is stronger in preparation, organisation, professional reflection, and risk awareness than in direct classroom mediation, process-oriented assessment, and institutionally supported student use. The strongest contrasts concern perceived student overreliance on AI-generated answers, the need to adapt assessment practices, limited school-level guidance, and weak use of AI-supported process monitoring. Rather than interpreting this imbalance as a simple delay in adoption, the article argues that teacher competence in relation to generative AI is produced through the interaction between professional judgement, pedagogical purposes, and institutional conditions. It therefore cannot be reduced to an individual technical attribute. Full article

Rapid innovation-driven transitions have, across successive eras, been associated with increased psychological distress, substance use, and suicide when social and economic change outpaces the adaptive capacity of individuals, communities, institutions, and governments. The early artificial intelligence (AI) economy is emerging at an unprecedented pace, reshaping education, employment, and social organization in ways that may intensify these risks, particularly among young people. This perspective argues that school-based mental health nursing, working collaboratively with school psychologists, counsellors, physicians, and other interdisciplinary professionals, represents a practical upstream response to AI-era disruption. Drawing on historical evidence from the Industrial Revolution, population mental health research, and the contemporary mental health nursing literature, the paper examines the mechanisms through which rapid socio-economic change may contribute to psychological distress and substance-use problems. It further distinguishes AI as both a source of socio-economic disruption and a clinical tool that can support—but not replace—relationship-based nursing practice. Strengthening school-based mental health nursing within interdisciplinary systems offers a practical, prevention-oriented strategy to promote resilience, facilitate early intervention, and mitigate downstream mental health and substance-use harms during the AI transition. Full article

With the development of smart classrooms and digital learning platforms, multimodal learning behavior data provide a new sensing basis for understanding students’ cognitive states and psychological risk warnings. However, existing educational data mining methods mainly focus on performance prediction, dropout warning, or surface-level emotion recognition, while continuous and interpretable modeling of deeper cognitive biases and related psychological risks remains insufficient. To address this issue, we propose MLBS-Net, a multimodal learning behavior sensing network for teaching feedback that jointly models students’ textual expressions, behavioral sequences, classroom interactions, and psychological auxiliary signals. MLBS-Net integrates theory-guided textual cognitive bias encoding, temporal behavioral state modeling, and reliability-aware cross-modal fusion to capture psychologically interpretable cognitive patterns, characterize dynamic learning-state changes, and adaptively integrate multimodal information according to data quality and task contribution while providing interpretable feedback for teachers. Experimental results show that MLBS-Net achieves a Macro-F1 of 0.855 for cognitive bias recognition and an AUC of 0.891 for psychological risk warning, outperforming traditional machine learning, unimodal deep learning, and standard multimodal methods. Ablation results further support the effectiveness of theory-guided semantic encoding, temporal behavioral modeling, reliability estimation, and multitask learning. These findings demonstrate that MLBS-Net can jointly characterize cognitive biases and potential psychological risks from multisource learning behaviors, providing a feasible approach for learning-state sensing, risk warning, and interpretable teaching support in smart education. Full article

Background: The growing awareness of breast cancer’s molecular diversity has not changed the technical foundations of surgery itself, but it has profoundly reshaped how surgeons think about surgery. Rather than molecular biology prescribing specific surgery, it is the surgeon’s interpretation of biological behavior—tumor subtype, genomic risk, treatment responsiveness—that influences surgical timing, extent, and feasibility. This is particularly important in the developing world, where mastectomy continues to be the default surgery, not always because it is required, but because biological nuance is underutilized in surgical planning. This review integrates existing evidence, guidelines, and real-world clinical experience to show how a surgeon who understands tumor biology can meaningfully expand safe breast conservation, de-escalate axillary surgery, and align operative choices with systemic therapy. In essence, molecular biology becomes a lens through which surgeons can practice more personalized, precise, and less invasive surgery, without compromising oncologic safety. Recent findings: We present evidence-based algorithms focusing on Luminal A, Luminal B, HER2-positive, and triple-negative subtypes, while discussing the nuances of multifocal and multicentric disease, metaplastic histologies, and discordant lesion management. The review addresses axillary management in the molecular era, specifying the appropriateness of sentinel lymph node biopsy, targeted axillary dissection, or completion axillary dissection, and how subtype-specific nodal responses to neoadjuvant therapy can guide de-escalation strategies. Through clinical vignettes, we exemplify how molecular integration into surgical planning can modify clinical courses, enabling oncoplastic conservation in downstaged tumors and justifying definitive resection in chemo-resistant cases. We examine the implications of germline and somatic genetic testing on surgical decision-making, particularly in relation to BRCA1/2 and PALB2 mutation carriers, alongside ethical and practical counseling considerations. Additionally, we review emerging biomarkers—such as circulating tumor DNA and immune and radiomic signatures—and propose research priorities for their incorporation into surgical trials. Conclusions: Effective implementation necessitates enhanced surgeon education, standardized assays, and multidisciplinary coordination to promote equitable access, consistent utilization of biology-driven algorithms, and rigorous quality oversight. This review furnishes breast surgeons with a pragmatic framework for translating molecular knowledge into multidisciplinary, patient-centered care pathways that optimize oncological safety, aesthetic outcomes, and overall quality of life. Full article