Search Results (1,347)

Background: Healthcare policy in the United Kingdom recognizes that teenagers and young adults (TYAs: 16–24 years at diagnosis) require specialist care. In England, Principal Treatment Centers (PTCs) exist, delivering enhanced care exclusively within the PTC or as ‘joint care’ with designated hospitals (DHs). Central to this is the TYA multidisciplinary team (MDT) and an outreach model coordinating care between hospitals. We previously reported similar outcomes regardless of care location. Aims: To compare TYA experiences of care with healthcare professionals’ perspectives of the service they deliver. Methods: Mixed methods across England and Wales were used. The TYA-MDT identified TYAs who then received a postal invite to a cross-sectional survey capturing experiences of places of care, treatment, healthcare professional support (HCP), mental health, sexuality/fertility, clinical trials and care coordination. Comparisons were made based on exposure to care in a specialist TYA environment within 6 months of diagnosis: all-TYA-PTC (all care in the TYA-PTC, n = 70, 28%), no-TYA-PTC (no care in the TYA-PTC (n = 87, 35%): care delivered in a children/adult unit only), and joint care (care in a TYA-PTC and in a children’s/adult unit, n = 91, 36%). HCP perspectives were captured by rapid ethnography. Results: A total of 250/1056 (24%) TYAs participated. Overall, 200 (80%) rated their teams as excellent/good for helping them prepare for treatment. No evidence of significant differences existed between categories of care for proportions receiving support from key TYA-related professionals: TYA cancer nurse specialists (all-TYA-PTC n = 58, 91%; joint care n = 71, 88%; no-TYA-PTC n = 64, 82%) and social workers (all-TYA-PTC n = 30, 55%; joint care n = 36, 48%; no-TYA-PTC n = 28, 38%). A trend of diminishing support from youth support co-coordinators existed (all-TYA-PTC 63%; joint care 49%; no-TYA-PTC 40%, p = 0.069). This may explain why few differences in patient experiences existed across categories of care. Forty-nine HCPs participated. They were more critical in their interpretation of care, highlighting inequity in resources and challenges in some pathways and coordination. Conclusions: Similar access to age-appropriate support across care settings is likely to reflect recruitment methods. When TYAs are known to the MDT, age-appropriate care can be mobilized beyond TYA units, which could explain the equitable outcomes observed across different care locations in young people who responded to the survey. Nevertheless, gaps persist in communication and coordination, particularly within joint care models, and in the involvement of allied health professionals such as dieticians and physiotherapists, whose input is essential for rehabilitation and return to normal life. Strengthening these areas will require continued investment in workforce capacity and digital infrastructure to support genuinely coordinated, developmentally appropriate TYA cancer care. Full article

Background: In 2022, the German healthcare system generated 400,000 tons of waste. Reducing this number could lower greenhouse gas emissions. The waste management plan at the University Medical Center Regensburg, and those of other comparable German facilities, require that glass, cardboard/paper, residual waste, and other non-hazardous materials are collected separately. Objectives: To assess the personal interest, proficiency, opinion, and awareness of waste management among German dermatology staff to develop customized, resource-saving process optimization and training programs. Methods: An online cross-sectional survey was conducted among German dermatology healthcare professionals between 27 February and 4 October 2024. Out of the 100 responses, 84 were complete and subsequently analyzed. Respondents included staff at dermatology wards, outpatient units, and private practices. Data were analyzed descriptively; comparisons were made between clinics and outpatient units, and correlations were identified among the items. Results: Most respondents perceived the amount of waste generated during wound dressing changes as high; more than 60% expressed an interest in receiving further training on sustainability and waste reduction. Although many respondents reported having a good understanding of waste separation, they identified time pressure and stress as the two main obstacles to consistent implementation. Higher self-reported knowledge did not correspond with greater confidence in recycling as an effective waste reduction measure. Conclusions: The findings suggest a discrepancy between awareness and practice regarding sustainable waste management in dermatology. Combining structural and organizational measures with targeted training and workflow optimization could promote more sustainable clinical practices. Full article

In this paper, we provide a thorough review of novel machine learning (ML) models for anomalous sound detection (ASD). We focus on deploying models to highly constrained, embedded systems and tiny ML, and using single-channel sound as the data input. The survey includes only the works published in 2020 and later. Researchers address the anomaly detection task in various ways, borrowing models and techniques from such fields as speech processing, audio generation, and even computer vision. However, it is not clear which of these are suitable for embedded systems, meeting their constraints such as memory or compute. To address that, we provide a deep analysis of these models and optimization techniques applied to meet the design criteria for embedded platforms. We consider both deep learning and classical ML methods. We define categories for the anomaly detection methods depending on the approach taken to provide a structure and simplify the comparison of methods. We aim to provide a guideline on how to develop ASD systems and how to efficiently deploy the models on the embedded platforms. Full article

Airborne gravity survey serves as a rapid remote sensing technique for mapping subsurface mineral target and geological structure over large areas. The raw gravity data contains significant noise corrupted by airflow and the flight platform’s attitude. The Kalman Filter (KF) is an effective method for airborne gravity data denoising, but its processing accuracy is highly dependent on the empirical parameters. The multi-scale CNN-LSTM-attention adaptive Kalman Filter (MSC-LA-AKF) method is proposed to obtain high precision gravity data, which combines the multi-scale CNN (MSC), bidirectional long short-term memory (Bi-LSTM) and attention mechanism for adaptively estimating the parameters of KF. The multi-scale CNN uses convolution kernel of varying sizes to extract signal features at different scales. The Bi-LSTM combines two LSTM layers in opposite directions to extract the signal features at bidirectional time series, and can effectively identify time-varying noise signals. A multi-head attention mechanism with four attention heads ($H=4$) is incorporated into the output feature layer of the Bi-LSTM to adaptively calculate weights for different features and optimize the parameters of the KF. The simulated data tests demonstrate that the MSC-LA-AKF achieves notably higher denoising accuracy than both the finite impulse response (FIR) and wavelet filters, with detailed quantitative comparisons provided in the experimental section. The proposed method is applied to real airborne gravity data, and effectively removes noise signals and enhances the geological interpretation of gravity maps. Full article

Background and objective: Adverse drug reactions (ADRs) cause substantial harm, and a considerable proportion may be preventable, but under-reporting persists and weakens pharmacovigilance. Spontaneous reporting depends on clinicians, yet under-reporting persists and weakens pharmacovigilance. To map barriers to adverse drug reaction reporting among physicians, a comparison of nurses and pharmacists in single-country studies was carried out between high-income countries (HICs) and low- and middle-income countries (LMICs). Methods: A scoping review was conducted following PRISMA-ScR guidance. PubMed and Web of Science were searched for studies published from 2016 onward. Eligible studies were single-country primary empirical studies including physicians, nurses, or pharmacists and examining ADR reporting. Only barriers that were measured or explicitly explored and reported as extractable results were included. Barriers were coded into 12 domains and summarised by income group and profession. Results: A total of 44 studies were included, with 18 from HICs and 26 from LMICs. Survey designs were most common. Pharmacists were the most frequently studied cadre. Knowledge and training barriers were reported in all studies in both income groups. Fear of legal or punitive concerns was reported in 13/18 (72.2%) HIC studies and 17/26 (65.4%) LMIC studies. Time and workload barriers were reported in 10/18 (55.6%) HIC studies and 11/26 (42.3%) LMIC studies. Access barriers to tools, forms, and information technology showed the clearest income group difference: these were reported in 5/18 (27.8%) HIC studies versus 16/26 (61.5%) LMIC studies. Lack of feedback or acknowledgement was reported in 8/18 (44.4%) HIC studies and 10/26 (38.5%) LMIC studies. Conclusions: Barriers extend beyond individual knowledge in all settings. The main income group difference was the greater prominence of reporting system access barriers in LMICs compared with workflow and time pressure barriers in HICs. Addressing fear and building a supportive non-punitive reporting culture remains a cross-cutting priority because these were common issues in both income groups and can limit reporting even when infrastructure and training exist. Full article

Background/Objectives: The digital transformation of dental practice is positioning artificial intelligence (AI) as a key tool for both clinical support and administrative optimization. While clinical uses of AI are well documented, there is limited evidence on managerial perspectives. This study explored how dental clinic managers view digital workflow transformation and AI implementation. Methods: A cross-sectional questionnaire-based study was conducted among 200 managers of dental clinics from urban and rural areas in Bucharest, Romania. The survey evaluated perceived difficulty and availability related to digitalization, current use of digital tools, demographic characteristics (age, professional experience, practice environment), and attitudinal dimensions reflecting digital pragmatism and efficiency versus human impac. Results: Managers demonstrated moderate digital pragmatism (median 2.84, IQR 2.29–3.44), embracing AI mainly when linked to efficiency, operational control, and economic sustainability. Lower perceived difficulty was associated with higher availability, current use of digital tools, younger age, and fewer years of managerial experience. Urban managers were more likely than rural managers to report higher availability and current use of digital tools, although this comparison should be interpreted cautiously given the small rural subgroup. Efficiency considerations outweighed human-impact concerns (median 3.9, IQR 3.46–4.2), yet caution persisted toward solutions requiring major organizational restructuring or potentially affecting clinician–patient interaction. This study is a pilot, exploratory investigation aimed at generating preliminary insights into the phenomenon of interest and refining the methodological approach and hypotheses for subsequent, larger-scale research. Conclusions: Dental clinic managers approach AI adoption through an efficiency-driven and risk-aware framework, favoring incremental digital integration over disruptive transformation. The results underline the need for context-sensitive implementation strategies, managerial training, and targeted support, to ensure that AI-enhanced workflows improve efficiency while preserving organizational stability and patient-centered care. Full article

Transient-source detection without relying on difference images still faces challenges in achieving high accuracy, especially under practical space-based astronomical survey conditions where the data volume is enormous, on-orbit transmission bandwidth is limited, and real-time response is required for rapid follow-up observations. To address these issues, this paper proposes a lightweight detection network that integrates multi-scale feature fusion with contextual feature extraction, enabling efficient real-time processing on resource-constrained edge devices. The proposed model enhances robustness to point-spread-function variations across observation conditions and to complex background environments, while simultaneously improving detection accuracy. To evaluate performance comprehensively, lightweight VGG and lightweight ResNet architectures and other baseline models—commonly used as baselines for transient-source detection—are adopted for comparison. Experimental results show that under the condition that the models have approximately the same number of parameters, the proposed network achieves the best accuracy, obtaining nearly 1% improvement compared with the best-performing baseline model. Based on this design, an ultra-lightweight version with only 7k parameters is further developed by incorporating a compact multi-scale module, improving accuracy by 1% over the version without the multi-scale structure. Moreover, through heterogeneous knowledge distillation and adaptive iterative training, the accuracy of the ultra-lightweight model is further increased from 93.3% to 94.0%. Finally, the model is deployed and validated on an AI hardware acceleration platform. The results demonstrate that the proposed method substantially improves inference throughput while maintaining high accuracy, providing a practical solution for real-time, low-latency, on-device transient-source detection under large data volume and limited transmission conditions. Specifically, the proposed models are trained offline on a high-performance GPU and subsequently deployed on the Fudan Microelectronics 7100 AI board to evaluate their real-world inference efficiency on resource-constrained edge devices. Full article

Background: Lifestyle behaviours and medication adherence are interrelated components of cardiovascular secondary prevention, yet their co-occurrence in Middle Eastern post-percutaneous coronary intervention (PCI) populations remains poorly characterised. This study described smoking status and physical activity patterns, assessed antiplatelet medication adherence, and explored associations between lifestyle factors and adherence among Saudi patients following PCI. Methods: A cross-sectional survey was conducted among 236 Saudi adults who had undergone PCI within the preceding 12 months at two tertiary cardiac centres in Riyadh, Saudi Arabia. Data were collected on smoking status, cigarette consumption, self-reported physical activity frequency (defined as the frequency of engagement in regular exercise such as walking, swimming, or other structured physical activity), and self-reported medication adherence measured via the Morisky Medication Adherence Scale-8 (MMAS-8). Descriptive statistics characterised lifestyle and adherence patterns. Bivariate analyses (chi-square tests) and multivariate binary logistic regression were used to explore associations between lifestyle factors and adherence, adjusting for comorbidities including hypertension, diabetes mellitus, arthritis, and heart disease. Results: Participants were predominantly male (73.7%) and older adults (83.9% aged >50 years). Smoking prevalence was 23.3% (n = 55 of 236 participants), and physical inactivity was highly prevalent, with 57.2% of the sample (n = 135) reporting never engaging in regular exercise. Adherence was suboptimal, with 55.4% of participants (n = 129) classified as having low adherence (self-reported, measured via the MMAS-8). In multivariate analysis, arthritis was the only statistically significant predictor of adherence (adjusted odds ratio [AOR] = 2.81, 95% confidence interval [CI]: 1.01–7.84, p = 0.048; note, however, that this finding does not survive Bonferroni correction for multiple comparisons and should be interpreted as hypothesis-generating). Smoking (AOR = 0.52, 95% CI: 0.19–1.45, p = 0.213) and physical inactivity (AOR = 0.45, 95% CI: 0.09–2.25, p = 0.332) showed inverse but statistically non-significant trends with adherence. Conclusions: Unhealthy lifestyle behaviours and low medication adherence were each highly prevalent and co-occurred in this post-PCI population, though associations between lifestyle factors and adherence were not statistically confirmed except for arthritis. These descriptive findings are hypothesis-generating and provide a rationale for future adequately powered prospective studies and trials evaluating integrated nursing interventions that simultaneously address smoking, physical inactivity, and medication non-adherence in Saudi cardiac care settings. Full article

Background: Sleep problems are prevalent among student populations worldwide. Medical students, facing heavy academic workloads and intense pressure, are particularly susceptible to sleep disorders. While sleep quality among Chinese university students has been consistently declining, research focusing on medical students in tropical island provinces like Hainan remains insufficient. This study aims to address this geographical gap by analyzing the sleep quality status and influencing factors among medical students in Hainan Province. Objective: To investigate the current status of sleep quality and its associated factors among medical students in Hainan Province, providing a scientific basis for developing targeted interventions. Methods: A cross-sectional survey was conducted in April 2024 using purposive sampling to recruit undergraduate students from a medical university in Hainan. The Self-Rating Scale of Sleep (SRSS) developed by Li Jianming was administered, and 551 valid questionnaires were collected anonymously. Data were analyzed using univariate analysis and pairwise comparisons to assess sleep quality and associated factors, with demographic variables as independent variables. Results: Among participants, 40.1% reported sleep problems (31.2% mild, 8.2% moderate, 0.7% severe). The mean total SRSS score was 21.78 ± 5.73. Compared to the national norm, medical students showed significantly higher scores in sleep quality, insufficient arousal, and post-insomnia responses (p < 0.05). Academic major was identified as a significant influencing factor (p = 0.012), with clinical medicine students demonstrating significantly poorer sleep quality than health management majors (p = 0.010). No significant differences were found for gender or academic year. Conclusions: Sleep problems are prominent among medical students in Hainan, with clinical medicine students at higher risk due to academic and professional pressures. Recommendations include optimizing curriculum schedules, strengthening psychological support systems, and developing targeted interventions for clinical majors. Full article

This article contributes to current debates around the ethics of using AI in K-12 education by extending an ethical framework based on the constructs of wellbeing, autonomy and justice to examine how AI may differentially impact specific stakeholders. Data about K-12 building and district leaders’ perceptions of AI risks were collected during the 2023–24 school year in Western New York as part of an exploratory sequential mixed methods study, which included semi-structured interviews with a diverse group of 36 K-12 leaders, followed by a survey (n = 160). Survey findings confirm K-12 leaders’ widespread recognition, although at varying levels of concern, of AI risks related to (a) students cheating, (b) students’ other questionable AI uses, (c) educators’ questionable AI uses, (d) increasing inequities due to AI, (e) cybersecurity and privacy breaches, and to a much lesser extent, the (f) potential for job replacement. The ethical analysis reveals major differences in the implications of each of these six kinds of AI risk for the wellbeing, autonomy, and justice of K-12 educators, K-12 students, and society, respectively, as well as tensions between competing needs and values, which in turn call for risk-specific strategies as well as inevitable tradeoffs. A comparison with a study of musicians’ perceptions of AI using the same ethical framework reveals interesting similarities and differences in ethical concerns about AI in different fields, suggesting the value of more cross-disciplinary studies. Full article

Background: Sustaining long-term lifestyle change remains a major challenge in preventive health. Epigenetic clocks offer a dynamic, modifiable measure of biological ageing that may enhance motivation when returned to individuals. Objectives: This study had two aims: (1) to evaluate whether personalised health reports integrating epigenetic age, polygenic cancer risk scores, and lifestyle metrics could motivate sustained behavioural change; and (2) to examine variability across epigenetic clock generations to inform the selection of a suitable model for participant feedback. Methods: A total of 178 adults were recruited via the Graham Fulford Charitable Trust community testing programme, and 91 completed a one-year follow-up survey assessing behavioural, psychological, and knowledge-related outcomes. DNA methylation data from 140 samples were used to compare 14 epigenetic clocks across four generations. Results: Most participants reported positive lifestyle changes, including feeling healthier (72.5%), increased physical activity (60.4%), and improved diet (47.3%). Gains were also observed in health knowledge (63.7%) and psychological well-being (31.9%). Epigenetic clock comparisons revealed substantial heterogeneity across models. Zhang2019-BLUP was selected as a stable and interpretable measure of biological age that can be readily communicated to participants, supporting empowerment and improved health literacy, rather than serving only as a risk prediction metric. Conclusions: Personalised biomarker feedback including epigenetic age combined with lifestyle and wearable data can support self-reported improvements in health-related behaviours. Community-based delivery through trusted local networks proved effective. The marked variation between epigenetic clocks highlights the importance of selecting models designed for clear communication when used in public-facing health interventions. Full article

Randomized response is a widely used survey technique for measuring stigmatized populations, but it may provide limited information in small samples. This paper introduces a method of elicitation through perfectly correlated questions, showing that correlation can substantially improve statistical performance and allow a dominant-strategy mechanism when either the interviewer or respondents hold symmetric beliefs. The framework also allows the interviewer to possess private information about the distribution of questions, further relaxing incentive constraints. Building on an existing survey design game framework, the paper introduces a novel efficiency-normalized comparison that holds statistical performance constant across mechanisms, enabling a direct comparison of incentives. The analysis characterizes incentive properties and estimation under correlated questions and randomized response, and identifies when it is optimal to ask respondents directly, use randomized response, or correlate questions. Full article

Objective: Dental professionals are routinely exposed to infectious agents through contact with blood, saliva, and aerosols. This cross-sectional survey aimed to evaluate and compare knowledge, attitudes, and self-reported practices related to infectious diseases among dental students and practicing dentists in the post-COVID era. Methods: This web-based cross-sectional survey was conducted between January and March 2024 at a single dental faculty. Fourth- and fifth-year dental students and practicing dentists were invited to participate. A 30-item questionnaire assessed knowledge of infectious disease transmission and immunological markers (Questions Q1–Q19), as well as attitudes and self-reported practices toward patients with infectious diseases (Q20–Q30). Descriptive statistics were calculated, and comparisons between groups were performed using Pearson’s chi-square or Fisher’s exact tests (α = 0.05). Internal consistency of the questionnaire was acceptable (Cronbach’s alpha: 0.81 for knowledge items and 0.88 for attitude/practice items). Results: A total of 221 dental students and 33 dentists were included in the final analysis. Both groups demonstrated high awareness of respiratory transmission routes for COVID-19 and influenza. In contrast, recognition of bloodborne transmission pathways was limited, with approximately half of participants identifying blood contact and blood-contaminated instruments as potential sources of infection. Significant differences were observed between students and dentists in the interpretation of SARS-CoV-2 IgG antibodies, with dentists more frequently associating IgG positivity with prior infection (p = 0.009) and immunity (p < 0.001). Cautious behavior toward treating patients with infectious diseases was common in both groups, whereas reluctance to provide treatment and lower self-perceived knowledge were more frequently reported among students. Conclusions: Despite adequate awareness of respiratory infection transmission, important deficiencies persist in bloodborne pathogen knowledge, serological interpretation, and confidence in managing infected patients, particularly among dental students. These findings underscore the need for targeted, practice-oriented infection control education that integrates immunological principles and hands-on training to enhance clinical preparedness in the post-COVID era. Full article

Background/Objectives: In the context of nursing research and interventions, caregiver preparedness emerges as a pivotal concept. Informal caregivers play a central role in providing older adults with the vital nursing and social support they require. The present study evaluated the psychometric performance of the Caregiver Preparedness Scale (CPS) and tested the hypothesis that CPS scores differentiate between theoretically relevant known groups, including caregiving exposure and relationship-based indicators. Methods: A cross-sectional, face-to-face survey was conducted in June 2025 among the general population of Czechia. A total of 1024 interviews were included in the analysis. The sample was randomly split for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The internal consistency of the scale was assessed using Cronbach’s α and McDonald’s ω, while inter-item associations were evaluated with Kendall’s tau-b. The known-groups validity was assessed through nonparametric group comparisons across caregiving exposure, relationship indicators within the caregiver–senior dyad, caregivers’ self-rated health, and their life satisfaction. Results: The CPS demonstrated high internal consistency (Cronbach’s α = 0.944; McDonald’s ω = 0.944), robust item–total correlations (0.730–0.863), and acceptable floor and ceiling effects. The EFA supported a dominant one-factor solution (eigenvalue = 5.749), which explained 71.9% of the variance and had strong loadings (0.750–0.894). The CFA demonstrated a good fit (RMSEA = 0.069, SRMR = 0.0155, CFI = 0.990, and TLI = 0.980) after allowing for a limited number of conceptually justified residual covariances. Known-groups analysis supported the sensitivity of the scale when the CPS scores were higher among primary (M = 25.30) and secondary (M = 22.73) caregivers in comparison to non-caregivers (M = 18.38). Moreover, statistically significant differences were observed among those who provided care during the past five years (M = 24.30) compared to those without such experience (M = 18.12). CPS scores also exhibited variation in relationship-focused indicators in the anticipated directions, and were lower among respondents reporting poorer health and lower life satisfaction. Conclusions: The study provided consistent evidence that CPS is a reliable, unidimensional measure with robust known-groups validity. The CPS can be regarded as a suitable research instrument for nursing research and for evaluating interventions aimed at supporting informal caregivers. Full article

Background: Sustainability-oriented higher education research has increasingly foregrounded staff wellbeing, motivational practice, and instructional continuity as central to long-term educational effectiveness. However, empirical evidence remains limited for university English language teaching (ELT) instructors operating within fragile, post-conflict, and regionally uneven systems such as Libya. In particular, little is known about whether job satisfaction is translated into motivational teaching behaviour through teacher self-efficacy, or how such relationships vary across demographic and institutional contexts. Addressing this gap is critical for understanding human-capital sustainability in higher education systems facing structural instability. Methods: A quantitative cross-sectional online survey was conducted using Google Forms and regionally stratified convenience sampling across Libya’s Western, Eastern, Central, and Southern regions. The final sample comprised 385 eligible university ELT instructors, including both full-time and part-time staff. Data were collected using three validated instruments: an adapted Teacher Job Satisfaction Questionnaire (21 items), a teacher self-efficacy scale (12 items), and a motivational teaching strategies scale (18 items). All measures demonstrated satisfactory internal consistency. Data analysis was performed using IBM SPSS Statistics v29, applying descriptive statistics, Pearson correlation analysis, regression-based mediation analysis with bootstrapping, and group comparisons using independent-samples t-tests and one-way ANOVA. Results: The sample included 57.14% male and 42.86% female instructors, with 62.86% employed full-time and the majority reporting 6–10 years of teaching experience (51.95%). Mean scores indicated moderate levels of job satisfaction (M = 3.32, SD = 0.94) and teacher self-efficacy (M = 3.03, SD = 0.68), alongside high levels of motivational teaching strategies (M = 4.15, SD = 0.87). Job satisfaction was positively associated with motivational teaching strategies (r = 0.61, p < 0.001) and teacher self-efficacy (r = 0.49, p < 0.001), while teacher self-efficacy was also positively related to motivational strategies (r = 0.53, p < 0.001). Mediation analysis revealed a significant partial mediating effect of teacher self-efficacy (indirect effect = 0.19, 95% CI [0.12, 0.28]). Significant differences were observed across demographic variables (age, gender, teaching experience) and institutional characteristics (employment status and university region). Conclusions: The findings indicate that sustainable teaching practice in Libyan higher education has been jointly shaped by organisational satisfaction and teachers’ capability beliefs. These results underscore the importance of context-sensitive institutional policies that support both structural working conditions and psychological resources. Future research could extend this evidence through longitudinal and mixed-methods designs to deepen understanding of sustainability-oriented teaching dynamics in fragile higher education systems. Full article