Search Results (582)

Medical errors in veterinary practice have a significant impact on veterinary staff, but the emotional experiences of pet owners remain largely unexplored. A total of 23 German pet owners participated in this qualitative study, which explored the impact of medical errors on their expectations of veterinary surgeons through semi-structured online interviews conducted between September and November 2024. The interviews followed a pretested questionnaire and were subsequently subjected to qualitative analysis. They reported emotional distress when faced with a medical error, characterised by anxiety, worry and helplessness. This led to increased scepticism and caution towards other veterinary surgeons, as well as a decline in trust and satisfaction with veterinary care. Pet owners emphasised the importance of veterinary surgeons being open and honest about errors, communicating openly and working together to prevent similar incidents. Pet owners are concerned about inadequate communication, lack of transparency and insufficient empathy from veterinary surgeons in the event of an error. Based on that, enhancing empathetic communication and providing comprehensive information could minimise the potential for conflict. Ensuring that pet owners feel acknowledged and respected is essential for fostering trust and long-term professional relationships. Full article

Background and Objectives: Clinical ethical judgments are often elicited through scenario-based (vignette-based) dilemmas that guide interpretation, reasoning, and moral judgment. Despite its importance, little is known about how healthcare professionals and students respond to such scenario-based dilemmas in Eastern European settings. This study explored differences in ethical decision-making between senior medical/dental students and practicing clinicians in Romania, focusing on how scenarios-based dilemmas influence conditional versus categorical responses. Materials and Methods: A cross-sectional survey was conducted with 244 participants (51 senior students; 193 practitioners). Respondents completed a validated 35-item questionnaire presenting hypothetical ethical scenarios across seven domains: informed consent, confidentiality, medical errors, public health duties, end-of-life decisions, professional boundaries, and crisis ethics. Each scenario used a Yes/No/It depends response structure. Group comparisons were analyzed using chi-square and non-parametric tests (α = 0.05). Results: Scenario-based dilemmas elicited frequent conditional reasoning, with “It depends” emerging as the most common response (47.8%). Strong consensus appeared in rejecting concealment of harmful errors and in treating unvaccinated families, reflecting robust professional norms. Divergences arose in areas where scenario-based dilemmas emphasized system-level duties: students more often supported annual influenza vaccination (52.9% vs. 32.6%, p = 0.028) and organ purchase authorization (76.47% vs. 62. 18%, p = 0.043), while practitioners more frequently endorsed higher insurance contributions for unhealthy lifestyles (48.7% vs. 23.5%, p = 0.003). Conclusions: Scenario-based dilemmas strongly shape moral decision-making in healthcare. While students tended toward principle-driven transparency, practitioners showed pragmatic orientations linked to experience and system stewardship. To promote high-quality clinical work and align decision-making with best practice and health policy, our findings support institutional protocols for transparent error disclosure, continuing professional development in ethical communication, the possible adoption of annual influenza vaccination policies for healthcare personnel as policy options rather than categorical imperatives, and structured triage frameworks during crisis situations. These proposals highlight how scenario-based ethics training can strengthen both individual reasoning and systemic resilience. Full article

This study reports on a Design-Based Research (DBR) project that implemented Project-Based Learning (PjBL) in an undergraduate psychology course on Human Resource Development (HRD). The purpose was to move beyond lecture-based instruction and explore how open pedagogy can create authentic, student-centered learning experiences that bridge theory and practice. Over two course iterations (n = 31), students co-designed, implemented, and evaluated HRD interventions for their peers, supported by peer and instructor feedback and complemented by a co-created open-book exam. Quantitative pre- and post-tests revealed significant improvements in students’ knowledge of HRD methods, learning theories, and application competencies, as well as enhanced confidence in their professional qualifications. Students valued the openness of the design, its practical orientation, and the error-friendly learning environment, though challenges emerged regarding workload, communication, and intrinsic motivation. Educators reported a transformation of their role from knowledge transmitter to facilitator and co-learner, while also identifying opportunities to use AI for generating authentic case tasks. The findings suggest that PjBL, combined with open pedagogy, fosters self-directed learning, transparency, and collaboration, thereby contributing to cultural change in higher education toward openness, participation, and innovation. Full article

This study investigates the utilisation of AI tools, including Grammarly Free, QuillBot Free, Canva Free Individual, and others, to enhance learning outcomes for 180 s-year telecommunications engineering students at Universidad Politécnica de Madrid. This research incorporates teaching methods like problem-based learning, experiential learning, task-based learning, and content–language integrated learning, with English as the medium of instruction. These tools were strategically used to enhance language skills, foster computational thinking, and promote critical problem-solving. A control group comprising 120 students who did not receive AI support was included in the study for comparative analysis. The control group’s role was essential in evaluating the impact of AI tools on learning outcomes by providing a baseline for comparison. The results indicated that the pilot group, utilising AI tools, demonstrated superior performance compared to the control group in listening comprehension (98.79% vs. 90.22%) and conceptual understanding (95.82% vs. 84.23%). These findings underscore the significance of these skills in enhancing communication and problem-solving abilities within the field of engineering. The assessment of the pilot course’s forum revealed a progression from initially error-prone and brief responses to refined, evidence-based reflections in participants. This evolution in responses significantly contributed to the high success rate of 87% in conducting complex contextual analyses by pilot course participants. Subsequent to these results, a project for educational innovation aims to implement the AI-PBL-CLIL model at Universidad Politécnica de Madrid from 2025 to 2026. Future research should look into adaptive AI systems for personalised learning and study the long-term effects of AI integration in higher education. Furthermore, collaborating with industry partners can significantly enhance the practical application of AI-based methods in engineering education. These strategies facilitate benchmarking against international standards, provide structured support for skill development, and ensure the sustained retention of professional competencies, ultimately elevating the international recognition of Spain’s engineering education. Full article

Background/Objectives: In Japan, the human papillomavirus (HPV) vaccine introduction process is unique, and no HPV knowledge scale with established reliability and validity currently exists. This study aimed to develop a new HPV knowledge scale and evaluate its reliability and validity for practical use. Methods: With permission from the original authors of the HPV Knowledge Scale (Jo Waller et al.), we created a Japanese version incorporating the original two subscales and adding new items. The translation process involved multiple researchers, back-translation by a professional agency, and expert review to ensure linguistic and contextual accuracy. The study was approved by the Clinical Research Ethics Review Board of the researchers’ affiliated universities and conducted between April and August 2024. Results: Reliability and validity were assessed using data from 793 parents of junior high school students, including both boys and girls. Confirmatory factor analysis showed a good model fit (Goodness-of-Fit Index [GFI] = 0.934, Adjusted GFI [AGFI] = 0.907, Comparative Fit Index [CFI] = 0.928, Root Mean Square Error of Approximation [RMSEA] = 0.063). Cronbach’s alpha ranged from 0.688 to 0.845 and item-total correlations ranged from 0.393 to 0.584. Test–retest reliability, assessed with Spearman’s rank correlation, was r = 0.791 (p < 0.001). The final scale, named the Japan HPV Knowledge Scale (J-HPV-KS), includes 17 items across five factors. Conclusions: The J-HPV-KS covers HPV-related diseases, transmission routes, natural history, and vaccines. It demonstrated sufficient reliability and validity for use in Japan and is a useful tool for assessing HPV-related knowledge among Japanese parents and guardians. Full article

Retrofitting existing buildings is regarded as a main driver of decarbonization, yet retrofitting activities are lagging behind their ambitious goals. This study explores 86 German construction practitioners’ perceptions of organizational, policy, and social challenges to sustainable retrofitting and how those perceptions relate to age, attitude, and their interaction. The primary analyses used OLS moderation models with HC3-robust standard errors and ordered-logit models, which served as robustness checks. Across outcomes, more pro-environment attitudes were associated with fewer perceived challenges, and older practitioners (41–56+) reported higher barrier perception. The attitude × age interaction results indicate that the protective link of attitude was weaker among older respondents, which was significant for policy and social challenges but only marginal for organizational challenges. The model fit was reasonable, at an Adj. R² between ≈0.56 and 0.72 with acceptable diagnostics. Our results suggest that even motivated professionals can feel constrained, especially among older, senior staff. Practical implications include early tenant engagement to enhance acceptance and foster internal organizational sustainability capacities. Policy instruments such as adult education programmes need to be leveraged to enhance sustainable construction capabilities and reinforce attitudes and behaviours toward sustainable retrofitting. More salient policy communications and guidance can contribute to increasing sustainability orientation and reducing perceived trade-offs with economic goals. Full article

Soil electrical conductivity (EC) and water content are key indicators of soil health, influencing nutrient availability, salinity stress, and crop productivity. Monitoring these parameters is critical for precision agriculture. However, most existing measurement systems are costly, which restricts their use in practical field conditions. The aim of this study was to develop and validate a low-cost, portable system for simultaneous measurement of soil EC, water content, and temperature, while maintaining accuracy comparable to laboratory-grade instruments. The system was designed with four electrodes arranged in two pairs and employed an AC bipolar pulse method with a constant-current circuit, precision rectifier, and peak detector to minimize electrode polarization. Experiments were carried out in sandy loam soil at water contents of 13%, 18%, and 22% and KNO₃ concentrations of 0, 0.1, 0.2, and 0.4 M. Measurements from the developed system were benchmarked against a professional impedance analyzer (E4990A). The findings demonstrated that EC increased with both frequency and water content. At 100 Hz, the mean error compared with the analyzer was 8.95%, rising slightly to 9.98% at 10 kHz. A strong linear relationship was observed between EC and KNO₃ concentration at 100 Hz (R² = 0.9898), and for the same salt concentration (0.1 M KNO₃) at 100 Hz, EC increased from ~0.26 mS/cm at 13% water content to ~0.43 mS/cm at 22%. In conclusion, the developed system consistently achieved <10% error while maintaining a cost of ~€55, significantly lower than commercial devices. These results confirm its potential as an affordable and reliable tool for soil salinity and water content monitoring in precision agriculture. Full article

Decent work is essential for fostering workers’ professional and personal growth, as well as for guaranteeing social security and welfare through the enforcement of rules and regulations. Recently, the global labour market has been profoundly influenced by technological innovations, the growth of the services sector, and globalization. Consequently, the protection of fundamental workers’ rights has become increasingly important, establishing that decent employment is crucial for generating superior and higher-quality output. In the Gulf Cooperation Council countries, there is an increasing necessity to acknowledge the significance of decent work conditions for sustained economic development. This study aims to examine the influence of decent work determinants on sustained economic development from 1991 to 2022. The analysis employs panel data methodologies, specifically cross-sectionally Augmented Autoregressive Distributed Lag models, alongside robustness assessments utilising Driscoll–Kraay standard errors, Augmented Mean Group, and Common Correlated Effects Mean Group estimators, revealing that GDP per employee exerts a significant and consistent positive influence on economic growth. Conversely, other aspects of decent work, including unemployment, vulnerable employment, and self-employment, do not have statistically significant long-term consequences. The Westerlund ECM cointegration test verifies the lack of a long-term equilibrium link between decent work indices and economic development. The findings indicate that although labour market quality is significant, productivity is the primary catalyst for sustained growth in the GCC setting. Policymakers should prioritise productivity-enhancing changes within comprehensive employment and labour market strategies. Full article

Background and Objectives: Unlike previous studies that have examined telemedicine primarily in pandemic contexts, this research adopts a dual-crisis perspective, assessing perceptions during both pandemics and armed conflicts. Recent health crises, including the COVID-19 pandemic and armed conflicts, have exposed vulnerabilities in health systems and underscored the need for evidence-based strategies to enhance resilience. Telemedicine has emerged as an essential tool for ensuring continuity of care, mitigating workforce shortages, and improving access for vulnerable groups. This study examines healthcare professionals’ perceptions of telemedicine in Romania across two exceptional contexts—pandemics and armed conflict—focusing on applicability, systemic integration, and limitations. Methods: A cross-sectional descriptive survey was conducted among 409 healthcare professionals. Perceptions were analyzed using a SWOT framework and descriptive statistics (percentiles, median) to identify strengths, weaknesses, opportunities, and threats in both scenarios. Results: Perceptions of telemedicine were shaped by prior experience, with strong support for its use in both contexts. Strengths included adaptability and improved access, while weaknesses highlighted technical barriers, insufficient training, and the risk of clinical errors. Threats referred to poor coordination across facilities and cultural or language barriers. Opportunities highlighted the potential for digital infrastructure and integration into preparedness frameworks. Conclusions: Telemedicine is positioned as a strategic tool for strengthening national health resilience. Adaptive, context-sensitive policies, combined with investments in infrastructure and workforce capacity, are essential for integrating telemedicine into emergency preparedness and ensuring sustainable, inclusive responses to future crises. This dual-crisis approach represents the novelty of our study, demonstrating how telemedicine can serve as a strategic tool for resilience in both epidemiological and conflict-related emergencies. Full article

Absolute linear encoders have emerged as a core technical enabler in the fields of high-end manufacturing and precision displacement measurement, owing to their inherent advantages such as the elimination of the need for homing operations and the retention of position data even upon power failure. However, there remains a notable scarcity of comprehensive review materials that can provide systematic guidance for practitioners engaged in the field of absolute linear encoder measurement technology. The present study aims to address this gap by offering a practical reference to professionals in this domain. In this research, we first systematically delineate the three fundamental categories of measurement principles underlying absolute linear encoders. Subsequently, we analyze the evolutionary trajectory of coding technologies, encompassing the design logics and application characteristics of quasi-absolute coding (including non-embedded and embedded variants) as well as absolute coding (covering multi-track and single-track configurations). Furthermore, we summarize the primary error sources that influence measurement accuracy and explore the operational mechanisms of various types of errors. This study clarifies the key technical pathways and existing challenges associated with absolute linear encoders, thereby providing practitioners in relevant fields with a decision-making guide for technology selection and insights into future development directions. Moving forward, efforts should focus on achieving breakthroughs in critical technologies such as high fault-tolerant coding design, integrated manufacturing, and error compensation, so as to advance the development of absolute linear encoders toward higher precision, miniaturization, cost reduction, and enhanced reliability. Full article

Introduction: Drug–drug interactions (DDI) are a major, preventable cause of patient harm, a challenge amplified in Jordan by rising polypharmacy and documented high rates of medication errors. To date, no study in Jordan has systematically compared hospital and community pharmacists. This study aimed to conduct the first national, comparative assessment of DDI management among these two cadres. Materials and Methods: A national, cross-sectional study was conducted with 380 licensed pharmacists (175 hospitals, 205 community) recruited via proportionate stratified random sampling. A validated online questionnaire assessed demographics, objective DDI knowledge, professional attitudes, practices, and barriers. Multivariable logistic regression was used to identify independent predictors of high knowledge and optimal practice. All collected data were coded, cleaned, and analyzed using the Statistical Package for the Social Sciences (SPSS V28.0). Results: Hospital pharmacists achieved significantly higher mean objective knowledge scores than community pharmacists (10.3 vs. 8.1 out of 15, p < 0.001), a gap particularly wide for interactions involving high-risk OTC medications. The primary barrier for community pharmacists was a lack of access to patient data (85.4%), contrasting with high workload and physician resistance in hospitals. Optimal practice was independently predicted by higher knowledge (AOR = 1.25), a hospital practice setting (AOR = 3.65), and was inhibited by perceived physician resistance (AOR = 0.45). Conclusions: Jordanian hospital and community pharmacists operate in distinct worlds of knowledge and practice. A tailored, dual-pronged national strategy is essential. For hospitals, interventions should target interprofessional dynamics. For community pharmacies, health policy reform to provide access to integrated patient data is the most urgent priority. These findings highlight a globally relevant challenge of practice-setting disparities, offering a model for other nations to develop tailored, context-specific interventions to improve medication safety. Full article

Accurate calculation of embodied carbon emissions in buildings (ECE) is crucial to achieving global carbon neutrality. However, fragmented data, inconsistent regional standards, and low computational efficiency have long hindered existing methods. This study innovatively integrates large language models (LLMs) with retrieval-enhanced generation (RAG) technology to establish a new intelligent accounting paradigm for embodied carbon in buildings. Through a systematic evaluation of three basic models—Kimi, Doubao, and DeepSeek-R1—in a five-level progressive input scenario, the study quantitatively reveals the “information sensitivity” patterns of LLMs. To address the illusion errors of general models in professional scenarios, an innovative three-stage closed-loop architecture of “knowledge retrieval—calculation embedding—trustworthy generation” is proposed. By dynamically invoking domain knowledge bases and embedded computing modules, zero-error verification of benchmark data is achieved. The core contributions include the following: (1) It has been clarified that the basic large model has application potential in calculating the implicit carbon emissions of buildings, but the reliability of the results is limited. (2) The influence of data elements on calculation accuracy is revealed. (3) The application path for integrating RAG with large models has been pioneered, and the results show that the RAG technology can enhance the performance of large models in calculating the implicit carbon emissions of buildings by approximately 25%. (4) The significant efficiency improvement of RAG technology is verified. (5) A supporting theoretical and application system is established. Full article

Mathematics teaching is a social practice, shaped by distinct ways of recognizing, interpreting, and responding to situations that emerge in the classroom. This professional noticing, however, requires a kind of mathematical knowledge that is specific to teaching. This study aims to identify discussions have taken place in Brazil regarding the mathematical knowledge necessary for teaching the concept of area of plane surfaces in Basic Education, based on a literature review conducted through the CAPES Theses and Dissertations Catalog. The theoretical framework is grounded in Moreira’s distinctions between school mathematics and academic mathematics, as well as in the body of literature concerning the concept of professional noticing. The analysis of the 17 selected studies revealed, among other aspects, that by understanding area as a magnitude through the lens of the Game with Frames—originally developed by Douady and Perrin-Glorian in the 1980s and later expanded by Brazilian researchers—it is possible to infer mathematical knowledge relevant to teaching the area of plane surfaces in Basic Education. This perspective supports the development of professional noticing of students’ errors, difficulties, and misconceptions observed both in classrooms and in teacher education contexts. Some elements of this knowledge are discussed in the present article. Full article

Background/Objectives: With the rapid development of smart healthcare, medical records have shifted from a disease-centered to a patient-centered approach. However, traditional formats, such as narratives and tables, often make it challenging for physicians to quickly grasp a patient’s condition within a limited timeframe, potentially leading to diagnostic errors and a decline in the quality of care. Recently, advances in information visualization and 3D technology have led many medical institutions to employ charts and graphs or use 3D simulations of organs to support clinical practice and education. However, few have integrated 3D models into medical records for use during physician consultations. Methods: This study presents the development and evaluation of a novel web-based 3D EMR system that integrates real-time ICD-10 diagnostic code mapping with interactive 3D human body models, enabling physicians to visualize patient-specific anatomical and diagnostic information in a dynamic and context-aware manner. Results: We employed the System Usability Scale (SUS) to evaluate the system’s usability, conducting a satisfaction survey. Results from the survey indicate that participants rated the system highly in terms of ease of use, satisfaction, and efficiency, with an average SUS score of 70.42, reflecting usability between moderate and good. Comparative evaluations and future expansion plans are also discussed. Conclusions: These findings demonstrate that integrating a 3D human model into the medical record retrieval process significantly improves visualization and interactivity, meeting the needs of healthcare professionals and enhancing both their efficiency and patient satisfaction. Full article

Emergency departments worldwide face challenges in managing fluctuating patient demand, which is often inadequately addressed by traditional forecasting methods due to the inherent nonlinearities of data. The purpose of this study is to propose a short-term prediction model for daily attendance in a private emergency healthcare unit in southern Brazil. The study employed seven years of historical data to compare the performance of ARIMA, Artificial Neural Networks (ANNs), and the chaotic logistic map model to forecast next-day arrivals in two specialties, general clinic and pediatric. The errors for the general practitioner and the pediatricians of the ARIMA, ANN, and logistic map models were, respectively, [0.31%, 2.54%, 2.17%] and [32.72%, 10.11%, 7.85%], measured by MAPE (mean absolute percentage error). The logistic map ranked second and first place, respectively, providing acceptable results in both cases. The main innovation is the successful application of a chaotic model, specifically the logistic map, exclusively for one-day prediction variables in the management of health and medical services. In particular, for the pediatrician, a most irregular time series, the logistic map provided the better outcome. For professionals, the study offers an accurate tool for optimizing the allocation of human and material resources and supporting daily strategic decisions. For scholars, it opens research avenues, addressing a gap in the body of knowledge on chaotic models that have not yet been extensively explored in healthcare service demand one-day forecasting. Full article