Search Results (2,976)

Background: As the United States population becomes increasingly diverse, the representation of minorities in health professions is critical to addressing health disparities. Few investigations have been conducted among students enrolled in the first semester of the nursing program, a vulnerable and adjustment period for most nursing majors. Thus, this study examined the association between reading comprehension and science aptitude on student retention and standardized test scores. Method: A cross-sectional repeated measures study was conducted to investigate the outcomes from a compendium of programmatic interventions implemented among n = 80 nursing students enrolled in the first semester of a pre-licensure baccalaureate nursing program in one Hispanic-serving institution. These interventions included the Weaver™ reading online program, case studies, NCLEX-type practice tests, test-taking skills, and peer-mentoring. Data collection was conducted in Spring 2024. Multivariate statistical analysis was used to determine predictors associated with student retention and standardized test scores. An independent t-test was used to examine any significant difference in the reading comprehension level among the cohort’s participants. A qualitative investigation using thematic analysis was conducted to understand students’ experiences with the programmatic interventions. Results: Students’ baseline reding comprehension level was significantly associated with failure in the first semester of the nursing program (β = −0.815; SE = 0.349; Wald = 5.444; p < 0.05). End-of-term reading comprehension level was significantly associated with end-of-course HESI score in the Foundations in Nursing course (β = 26.768; SE = 10.049; Beta = 0.445; p < 0.05) while science GPA was significantly associated with end-of-course HESI score for Health Assessment (β = 3.022; SE = 1.315; Beta = 0.434; p < 0.05. Cohort retention was 75%. The independent t-test result indicated a significant difference in reading level was found between those who dropped out from the cohort (M = 4.23, SE = 0.173 and those who did not (M = 5.15, SE = 0.188), t (68) = −3.037, p < 0.01. A reading level of grade 10 and above was associated with student progression to the next semester (M = 10.16, SE = 0.375, t (70) = −0.560, p < 0.05. Although the participants found the reading comprehension modules tedious, test-taking strategies, applying the nursing process in case studies, and the expertise of a nurse educator, who understood the learning needs of first-semester students, were perceived as critical to academic success. Conclusions: Reading comprehension and science aptitude are essential to students’ early success in the nursing program. Addressing gaps in reading comprehension and science aptitude before admission to a nursing program would increase chances of success in the early stages of a nursing major. Full article

Background/Objectives: Schizophrenia is associated with cognitive deficits that may compromise everyday functioning, including driving. This review systematically examined recent original research (2015–2025) on driving performance in individuals with schizophrenia with a focus on neuropsychological factors, applying a narrative synthesis given the heterogeneity of designs and outcomes, while no quantitative meta-analysis was feasible. Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a structured search of PubMed and Scopus was conducted on 4 May 2025. The inclusion criteria were original studies involving individuals diagnosed with schizophrenia, published between 2015 and 2025. Studies on animals, other psychiatric or neurological conditions, and healthy populations were also excluded. Critical appraisal was performed using the Joanna Briggs Institute (JBI) tools. Extracted data included sample demographics, cognitive deficits, neuropsychological assessments, brain imaging, and the main findings. A narrative synthesis was then performed. Results: Six high-quality studies met the inclusion criteria. Findings were grouped into three categories: (1) driving behavior: fitness to drive varied widely across individuals, (2) cognitive deficits and brain activity: poorer driving-related performance was consistently associated with specific impairments in cognition and brain structure, and (3) medication effects: individuals taking certain atypical antipsychotics demonstrated better driving performance compared to those on other types of medication, while extrapyramidal symptoms negatively influenced driving fitness. Conclusions: Driving in schizophrenia is shaped by cognitive, clinical, and pharmacological factors. These findings highlight the clinical relevance of individualized evaluations, integration into personalized care and targeted rehabilitation to promote driving autonomy and community inclusion. This area remains under-researched, as only six studies met the inclusion criteria, which restricts the robustness and generalizability of the conclusions. Funding: This review received no funding from any external sources. Registration: The review protocol was submitted to PROSPERO (International Prospective Register of Systematic Reviews) under registration number CRD420251060580. Full article

Sustainable economic development requires transparent and consistent institutional communication from monetary authorities to maintain long-term financial stability and public trust. This study investigates the latent authorial structure and stylistic heterogeneity of central bank communications by applying stylometric analysis and unsupervised machine learning to official announcements of the Central Bank of the Republic of Turkey (CBRT). Using a dataset of 557 press releases from 2006 to 2017, we extract a range of linguistic features at both sentence and document levels—including sentence length, punctuation density, word length, and type–token ratios. These features are reduced using Principal Component Analysis (PCA) and clustered via Hierarchical Clustering on Principal Components (HCPC), revealing three distinct authorial groups within the CBRT’s communications. The robustness of these clusters is validated using multidimensional scaling (MDS) on character-level and word-level n-gram distances. The analysis finds consistent stylistic differences between clusters, with implications for authorship attribution, tone variation, and communication strategy. Notably, sentiment analysis indicates that one authorial cluster tends to exhibit more negative tonal features, suggesting potential bias or divergence in internal communication style. These findings challenge the conventional assumption of institutional homogeneity and highlight the presence of distinct communicative voices within the central bank. Furthermore, the results suggest that stylistic variation—though often subtle—may convey unintended policy signals to markets, especially in contexts where linguistic shifts are closely scrutinized. This research contributes to the emerging intersection of natural language processing, monetary economics, and institutional transparency. It demonstrates the efficacy of stylometric techniques in revealing the hidden structure of policy discourse and suggests that linguistic analytics can offer valuable insights into the internal dynamics, credibility, and effectiveness of monetary authorities. These findings contribute to sustainable financial governance by demonstrating how AI-driven analysis can enhance institutional transparency, promote consistent policy communication, and support long-term economic stability—key pillars of sustainable development. Full article

Previous research has placed social innovation as a static outcome or single concept, thereby not effectively capturing the dynamism of innovation over time and changes in its purpose. This study attempts to develop an analytical framework which adopts dual axes of pathways of institutional change and levels of innovation for multidimensional analysis of social innovation. Drawing on this dual-axis framework, this study examined 121 social businesses in developing countries. These businesses were operated by social innovators who had been recognized as Ashoka Fellows between 2006 and 2025. Analysis of the cases revealed that the most prevalent type of early-stage social innovation was the peripheral-user type, inducing change at the user level from the periphery of the system. Moreover, the most frequently observed type of transition was from the peripheral-user type to the integrated-service wherein the innovation became partially integrated into the system and changes at the service level. What these findings suggest is that social innovations start at the user level, expand into services, and, in some cases, reach the system level. They move step by step into deeper forms of institutional integration. This study develops a conceptually grounded typology and empirically examines dynamic patterns of this process. Full article

Background/Objectives: Understanding prescribing patterns for type 2 diabetes mellitus, a complex condition affecting over 10% of the global adult population, can optimise prescribing practices, guide policymakers in promoting evidence-based medicine, and help tailor first-line treatments to individual characteristics or specific subgroups, improving patient outcomes. This study aimed to identify factors influencing the prescription and non-prescription of metformin, the recommended first-line therapy in Western guidelines, and to evaluate whether these prescribing patterns align with evidence-based recommendations. It also explores factors associated with initial combination therapy, a more recent and controversial approach compared to stepwise therapy. Methods: We conducted a systematic search in PubMed, Scopus, and Web of Science on 25 August 2023, without language or time restrictions, to identify observational analytical studies assessing factors associated with the initiation of metformin or combination therapy in adults with type 2 diabetes mellitus who were naïve to antidiabetic medications. Studies involving pregnant or breastfeeding women were excluded. A narrative synthesis was conducted. Study quality was assessed using the Joanna Briggs Institute critical appraisal checklists (PROSPERO registration number CRD42023438313). Results: Thirty studies were included, evaluating 105 variables, most of which (62%) were assessed in one study. The 25 variables using combination therapy as the outcome were mostly (72%) evaluated also in one study. Initial metformin prescription was strongly and positively associated with younger age, lower glycated haemoglobin levels, higher body mass index, and absence of renal impairment. Initial combination therapy was associated with higher HbA1c levels and a lower burden of comorbidities. Findings also highlighted a discrepancy between clinical practice and evidence-based recommendations. However, concerns were raised regarding both the internal and external validity of the included studies. Conclusions: Our systematic review, which offers insights into real-world clinical practices, indicated that there is a misalignment between clinical practices and evidence-based recommendations, supporting the need for interventions in this field. Full article

Cultural organizations have traditionally been viewed as resistant to change, often bound by legacy structures, public dependency, and non-commercial missions. However, recent advances in digital technologies—ranging from AI and VR to IoT and big data—are reshaping the operational and strategic landscape of these institutions. Despite this shift, academic literature has yet to comprehensively map how technological innovation transforms cultural organizations into practice. This paper addresses this gap by introducing the concept of the Cultural Organizational System (COS)—a holistic framework that captures the multi-component structure of cultural entities, including space, tools, performance, management, and networks. Using a PRISMA-based scoping review methodology, we analyze over 90 sources to identify the types, functions, and strategic roles of technological innovations across COS components. The findings reveal a taxonomy of innovation use cases, a mapping to Oslo innovation categories, and a quadrant model of enablers and barriers unique to the cultural sector. By offering an integrated view of digital transformation in cultural settings, this study advances innovation theory and provides practical guidance for cultural leaders and policymakers seeking to balance mission-driven goals with sustainability and modernization imperatives. Full article

Background: Bone metastases are a common complication in patients with advanced cancer. These patients often experience a decline in physical function and autonomy, particularly in the ability to perform Activities of Daily Living, and structured movement-based interventions may represent an important supportive strategy. The aim of this study is to describe the available evidence regarding the impact of physical activity and exercise interventions on functional status and ADL performance in patients with bone metastases. Methods: A systematic literature review was conducted in PubMed, Scopus, Embase, Web of Science, and CINAHL database up to March 2025 and reported according to PRISMA guidelines. Eligible studies included adults (≥18 years) with confirmed bone metastases who underwent physical activity interventions designed to enhance functional status and ADLs. Studies’ methodological quality was assessed using the Joanna Briggs Institute critical appraisal tools, selected according to study design. Results: Eleven studies were included: four randomized controlled trials, four quasi-experimental studies, one randomized feasibility trial, one cross-sectional observational study, and one case report. Despite heterogeneity in intervention type, duration, and outcome measures, most studies reported improvements in physical function, including mobility, muscle strength, walking capacity, and endurance, as well as enhanced performance in ADLs and reductions in fatigue. No serious adverse events were reported. Conclusions: Structured physical activity appears safe and may improve function and independence in patients with bone metastases. These findings support the integration of individualized exercise programs into multidisciplinary supportive care. Full article

This study takes the environmental protection tax (EPT) implemented in China in 2018 as the policy background and systematically examines the impact mechanism and boundary conditions of EPT on the market value of listed companies in the polluting industries. The results indicate that EPT significantly inhibits Tobin’s Q of polluting companies. A one-unit increase in EPT leads to a 0.274-unit decrease in Tobin’s Q. The heterogeneity test reveals that the EPT shock exhibits a spatial gradient effect of “Eastern > Central > Western > Northeastern”. The rigidity of the tax system is stronger than that of the pollution discharge fee, and the effect on non-heavily polluting industries is stronger than that on heavily polluting industries. Mechanism analysis shows that while corporate financial flexibility can buffer against short-term EPT shocks, R&D investment and patent quality expose an “innovation trap” characterized by high investment but low conversion efficiency, largely determined by the type of innovation pursued. By elucidating the multiple moderating and mediating mechanisms at play, this study constructs an integrated “institutional pressure-resource constraints-market feedback” model, thereby providing a new analytical framework for environmental economics in emerging markets. Full article

College websites are a primary source of information for prospective students. As increasing numbers of autistic students head to college, we wanted to capture whether and how college websites were presenting themselves as autism-friendly or autism-aware environments. This is a descriptive study of how college websites from liberal arts institutions in the U.S. talk about autism. The top 50 liberal arts schools, as ranked by the US World and News Report from 2023, were searched for the following terms: “autism”, “autistic”, “ASD”, “neurodiversity”, “neurodivergent”, and “neurodivergence.” Five website areas where these terms may appear, or where prospective students may look for them, were identified: admissions, accessibility, counseling/mental health, faculty resources, and student life. Overall, the occurrence of any searched terms was extremely low across all areas. This lack of terminology representation likely reflects the reality of autism-related services on these campuses. On some websites, mentions of autism did not reflect a deeper cultural understanding of the term. The lack of representation of and information about autism and neurodiversity on college websites should be a call to these types of institutions that there are a number of students whose identities are not being recognized by these academic spaces. Full article

Background: Anastomotic leakage (AL) is a major complication after esophago-gastric surgery, with incidence rates of 11–21% and mortality up to 14%. Early intervention is essential to reduce morbidity. Endoscopic treatments have advanced, with self-expandable metal stents (SEMSs) as the traditional standard (success ~90%), but they carry risks like migration, stenosis, and need for drainage. Endoscopic vacuum therapy (EVT), applying negative pressure to drain secretions and promote healing, has shown success rates of 66–100%. Limited comparative data exists from small retrospective studies. This study compares SEMS and EVT for safety and efficacy in AL management. Methods: A retrospective case–control study from a prospective database at our institution was performed (March 2012–2025). We included patients with AL post-esophageal/gastric surgery treated endoscopically (SEMS or EVT). We excluded patients treated with conservative or surgical management. Demographics, comorbidities, oncology, surgery type, leak details, treatments, and outcomes were collected. Primary outcome was complete healing of the leak, while secondary outcomes were time to success, number of procedures needed, hospital stay, complications, mortality. Results: From 592 resections, we extracted 68 AL (11.5%), 45 of which met the inclusion criteria (22 SEMS, 23 EVT). Groups were similar demographically, but SEMS had more respiratory issues (43% vs. 8.7%, p = 0.018). SEMS were used more after esophagectomy (86.4% vs. 56.5%, p = 0.004); EVT was performed mostly after gastrectomy (34.7% vs. 9.1%, p = 0.009). Success rate was 86.4% for SEMS vs. 95.6% for EVT (p = 1.000). Complications were significantly lower in EVT (8.3% vs. 50%, p = 0.001; SEMS: 36.4% migrations, 18.2% stenoses). Leak onset time, modality of diagnosis, and leak size were comparable among the groups. Need for jejunostomy was higher in EVT (43.5% vs. 9.1%, p = 0.015), while chest drains in SEMS (63.7% vs. 13.1%, p < 0.001). Hospital stays (33–38 days, p = 0.864) and mortality (22.7% vs. 8.7%, p = 0.225) were similar. No differences were observed in terms of long-term mortality (log-rank p = 0.815). Conclusions: SEMS and EVT are both effective for AL after esophago-gastric surgery. EVT offers fewer complications and shorter treatment, so it is favored especially for esophago-jejunal leaks. Full article

Background: Myelodysplastic/myeloproliferative neoplasms (MDS/MPNs) are rare hematopoietic disorders that exhibit overlapping pathological and molecular features of both MDS and MPN. This study aimed to investigate the mutational profiles and prognostic implications of MDS/MPN subtypes in Korean patients. Methods: We retrospectively reviewed 53 patients with MDS/MPN who underwent bone marrow examination and next-generation sequencing panel testing. Overall survival was analyzed with 3-year censoring. The cohort included chronic myelomonocytic leukemia (CMML; N = 30); MDS/MPN with neutrophilia (N = 6); MDS/MPN with SF3B1 mutation and thrombocytosis (N = 4); and MDS/MPN, not otherwise specified (MDS/MPN-NOS; N = 13). Results: The most frequently mutated gene was ASXL1 (52.8%), followed by TET2 (39.6%) and U2AF1 (18.9%), in total MDS/MPN. U2AF1 mutations were particularly frequent in myelodysplastic CMML (33.3%) and MDS/MPN-NOS (30.8%). In CMML, ASXL1 and TET2 mutations were associated with a trend toward better prognosis compared with wild-type (HR 0.21, p = 0.052; HR 0.25, p = 0.057, respectively), while U2AF1 mutations were associated with adverse prognosis in univariate analysis with borderline significance (HR 12.20, p = 0.050). Clinical/Molecular CMML-Specific Prognostic Scoring System and Mayo Molecular Model showed stepwise survival patterns across risk groups without statistical significance. In univariate analysis, transfusion dependency was associated with poor prognosis (HR 7.78, p = 0.013). Conclusions: This study provides the first single-institution analysis in Korean patients with MDS/MPN and identified U2AF1 mutations as a potentially significant prognostic factor, enhancing the molecular understanding of MDS/MPN. Full article

The suspension system can adapt to different road excitations by adjusting its own stiffness or damping, or outputting active driving force, thereby improving the comprehensive dynamic performance of the vehicle, including ride comfort and vehicle handling. As the automotive industry’s requirements for “intelligence, comfort, and safety” continue to increase, the intelligence of suspension systems has become a research hotspot for scientific research institutions and enterprises, with broad development prospects. This article reviews the current development status of automotive suspensions and introduces the working principles and research status of different types of suspension systems, such as passive suspensions, semi-active suspensions, active suspensions, and electromagnetic suspensions. In addition, it summarizes the control methods of vehicle intelligent suspensions, including classical control, modern control, and intelligent control, and expounds the advantages and disadvantages of each control strategy. Finally, it summarizes the challenges and development trends faced by suspension systems. This review can provide technical reference for researchers engaged in the study of intelligent suspension under the modern chassis architecture and offer direction guidance for the development of key suspension technologies. Full article

Background: Numerous healthcare services have been affected by the COVID-19 pandemic worldwide. Specialized healthcare services were postponed or canceled, potentially compromising regular services for hemato-oncology patients. The current study aimed to analyze the impact of the COVID-19 pandemic on access to hemato-oncology services in Almaty, the largest city in Kazakhstan. Methods: We retrospectively analyzed the socio-demographic characteristics of patients admitted to two large tertiary centers rendering hemato-oncology services, the City Clinical Hospital 7 (H7) and the Kazakh Institute of Oncology and Radiology (KazIOR). All data were retrieved for the period spanning from 1 March 2019 to 28 February 2022. The retrieved variables included age, gender, type of residence, hospitalization rate, treatment outcomes (discharged/deceased), bed days, diagnoses according to International Classification of Diseases (ICD-10) (acute leukemia and hematopoietic depression, lymphoproliferative diseases, and myeloproliferative diseases), and referral sources (ambulance, another hospital, consultative and diagnostic assistance, primary healthcare, self-referral, and referrals from hematologists’ offices). Results: In the 2019–2022 period, 6763 hemato-oncology hospitalizations were registered: 3583 in H7 and 3180 in KazIOR. The mean age at hospitalization was 55.04 (SD = 16.07) for females and 51.2 (SD = 16.7) for males. The proportion of hospitalized urban and rural patients differed significantly: 6191 (92%) and 571 (8,4%), respectively (χ² = 13.8, p = 0.001). In the 2020–2021 period, fewer patients were discharged (n = 2047) compared to 2019–2020 (n = 2387) and 2021–2022 (n = 2081) (χ² = 20.09, p = 0.003). However, the proportion of deaths in the 2020–2021 period (3.5%) was higher than in the 2019–2020 (3.2%) and 2021–2022 periods (2.6%) (χ² = 20.09, p = 0.003). A total of 403 (19%) hospital admissions were carried out by ambulance (emergency cases) in the 2020–2021 period, 368 (14.8%) in 2019–2020, and 394 (18.3%) in 2021–2022 (χ² = 2231, p < 0.001). The number of patients transferred from other hospitals to H7 and KazIOR increased by 12.4% in the 2020–2021 period. Conclusions: Our findings indicate a negative impact of the COVID-19 pandemic on access to hemato-oncology services, leading to increased mortality. Further studies are warranted to explore factors underlying the trends in hospitalizations and mortality of hemato-oncology patients during healthcare crises. Full article

Soft skills are increasingly recognised as decisive factors for employability and career advancement in the global labour market. This study examines their role in the professional trajectories of university graduates in Ecuador, analysing both the competencies supplied by higher education and the structural demand of the labour market. Based on institutional surveys applied to 3358 graduates from the Salesian Polytechnic University (Cuenca campus), the results show that more than $90\%$ of graduates remain in operational positions, while only $5\%$ reach tactical or managerial levels. To address this phenomenon, five key soft skills—leadership, effective communication, teamwork, problem-solving, and adaptability—were evaluated through a structured questionnaire using Likert-type items. The findings reveal a persistent concentration of professionals in lower organisational levels and heterogeneous perceptions of the applicability of academic training. These outcomes highlight both individual skill gaps and structural limitations of the Ecuadorian labour market, such as the scarcity of managerial positions and the prevalence of family-based business structures. In response, the study proposes a sector-based curricular improvement strategy that systematically incorporates soft skills into university programmes, differentiated by economic sectors such as education, health, commerce, public administration, industry, and primary activities. Grounded in empirical evidence, this approach provides a practical framework to enhance graduates’ career progression, foster more equitable professional mobility, and strengthen the relevance of higher education. The model can be replicated across other Latin American universities facing similar challenges, while also aligning with international standards for competency-based education. Full article

This paper presents a digital approach for the identification of apple varieties bred in Kazakhstan using deep learning methods and transfer learning. The main objective of this study is to develop and evaluate an algorithm for automatic varietal classification of apples based on color images obtained under controlled conditions. Five representative cultivars were selected as research objects: Aport Alexander, Ainur, Sinap Almaty, Nursat, and Kazakhskij Yubilejnyj. The fruit samples were collected in the pomological garden of the Kazakh Research Institute of Fruit and Vegetable Growing, ensuring representativeness and taking into account the natural variability of the cultivars. Two convolutional neural network (CNN) architectures—GoogLeNet and SqueezeNet—were fine-tuned using transfer learning with different optimization settings. The data processing pipeline included preprocessing, training and validation set formation, and augmentation techniques to improve model generalization. Network performance was assessed using standard evaluation metrics such as accuracy, precision, and recall, complemented by confusion matrix analysis to reveal potential misclassifications. The results demonstrated high recognition efficiency: the classification accuracy exceeded 95% for most cultivars, while the Ainur variety achieved 100% recognition when tested with GoogLeNet. Interestingly, the Nursat variety achieved the best results with SqueezeNet, which highlights the importance of model selection for specific apple types. These findings confirm the applicability of CNN-based deep learning for varietal recognition of Kazakhstan apple cultivars. The novelty of this study lies in applying neural network models to local Kazakhstan apple varieties for the first time, which is of both scientific and practical importance. The practical contribution of the research is the potential integration of the developed method into industrial fruit-sorting systems, thereby increasing productivity, objectivity, and precision in post-harvest processing. The main limitation of this study is the relatively small dataset and the use of controlled laboratory image acquisition conditions. Future research will focus on expanding the dataset, testing the models under real production environments, and exploring more advanced deep learning architectures to further improve recognition performance. Full article