Search Results (502)

Background: Point-of-care ultrasound (POCUS) is gaining recognition as a valuable diagnostic tool in various fields of medicine, including pediatrics. Its application at the point of care enables real-time clinical decision-making, which is particularly advantageous in pediatric settings. Although global interest in POCUS is growing, many European countries—including Poland—still lack formal training programs for POCUS at both the undergraduate and postgraduate levels. Nevertheless, the number of pediatricians incorporating POCUS into their daily clinical practice in Poland is increasing. However, the extent of its use and perceived value among pediatricians remains largely unknown. This study aimed to evaluate the current level of POCUS utilization in pediatric care in Poland, focusing on pediatricians’ self-assessed competencies, perceptions of its clinical utility, and key barriers to its implementation in daily practice. Methods: This cross-sectional study was conducted between July and August 2024 using an anonymous online survey distributed to pediatricians throughout Poland via national professional networks, with a response rate of 7.3%. Categorical variables were analyzed using the chi-square test of independence to assess the associations between key variables. Quantitative data were analyzed using descriptive statistics, and qualitative data from open-ended responses were subjected to a thematic analysis. Results: A total of 210 pediatricians responded. Among them, 149 (71%) reported access to ultrasound equipment at their workplace, and 89 (42.4%) reported having participated in some form of POCUS training. Only 46 respondents (21.9%) reported frequently using POCUS in their clinical routine. The self-assessed POCUS competence was rated as low or very low by 136 respondents (64.8%). While POCUS was generally perceived as a helpful tool in facilitating and accelerating clinical decisions, the main barriers to implementation were a lack of formal training and limited institutional support. Conclusions: Although POCUS is perceived as clinically valuable by the surveyed pediatricians in Poland, its routine use remains limited due to training and systemic barriers. Future efforts should prioritize the development of a validated, competency-based training framework and the implementation of a larger, representative national study to guide the structured integration of POCUS into pediatric care. Full article

Background/Objectives: The aim of this study was to evaluate the level of awareness among dental students and practitioners regarding the utilization of endocrowns in clinical settings, along with any differences in knowledge based on gender, educational level, and workplace. Methods: A cross-sectional online survey-based study was conducted, including 1154 participants from various dental institutions across Saudi Arabia. The questionnaire included demographic data and closed-ended questions focused on knowledge and awareness of endocrowns. Data was analyzed using statistical tests, including chi-square, to see any significant differences. Results: Most participants (81%) had knowledge about endocrowns, mainly from their colleagues. Knowledge levels and preferences (like the use of lithium disilicate and adhesive resin cement) differed based on gender, educational level, and workplace. Male participants and undergraduates showed better awareness in some areas. Faculty members mostly depend on college training, while private practitioners obtain most of their information from workshops. Conclusions: Males showed significant superiority in knowledge about endocrown usage. Colleges were the most prevalent source of information regarding endocrown restorations. Significant molar tooth loss and restricted inter-arch space were the most common reasons for utilizing endocrowns. Moreover, endocrowns were considered a viable alternative to traditional post and core. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

In the Hexaflex model of Acceptance and Commitment Therapy (ACT), psychological flexibility refers to the ability to openly embrace difficult thoughts and emotions while acting in alignment with personal values. In contrast, psychological inflexibility involves rigid avoidance and control strategies that hinder adaptive functioning. Although previously studied, more culturally relevant evidence is needed to inform interventions that promote well-being and mental health among Latin American students. This study explored manifestations of psychological flexibility and inflexibility in 15 undergraduate students from the University of Magdalena in Colombia (mean age = 20.13 years; 53.33% female) through semi-structured, face-to-face interviews (~45 min each). Data were analyzed using Interpretative Phenomenological Analysis (IPA), focusing on how participants described and made sense of their experiences. A total of 25 emergent themes were identified and grouped into 12 subordinate themes, mapped onto the 6 core ACT processes. The participants reported efforts to control or avoid distressing internal experiences, often resulting in difficulty acting in accordance with their values. The findings highlight a recurring ambivalence between avoidance and acceptance, and barriers to committed action, underscoring the dynamic interplay between flexibility and inflexibility. These results support the relevance of ACT-based interventions, such as structured group sessions that foster acceptance, mindfulness, and values-based behavior. Integrating this training into counseling and academic support services could enhance students’ well-being and performance. Future research should examine these dynamics longitudinally and across diverse contexts. Full article

Generative artificial intelligence (AI) is changing higher education. Understanding students’ perceptions, usage behaviour and ethical concerns is crucial for the responsible and sustainable use of AI in the academic environment. The aim of this study was to explore the perceptions, experiences and challenges of health sciences students in relation to the use of generative AI in their academic learning. A descriptive cross-sectional survey was conducted with 397 students enrolled in four undergraduate health-related degree programmes in Slovenia, including nursing, physiotherapy, dietetics and applied kinesiology. The data was collected using a validated 27-point scale. Students were generally favourable towards AI, especially in terms of its perceived usefulness, integration into their daily study routine and ethical considerations. Regression analyses revealed that frequency of AI use, duration of use, self-reported skill level and confidence in using AI significantly predicted perceived usefulness. Gender differences were found, with male students reporting higher perceived usefulness and fewer concerns. Students recognised the potential of generative AI but emphasised the importance of ethical guidance, digital literacy and equal access. Institutions should prioritise structured training and inclusive strategies to ensure meaningful, sustainable and responsible integration of AI into health education. Full article

Background/Objectives: Psychological safety is essential for effective learning in high-fidelity simulation (HFS); however, no validated Japanese instrument currently exists to measure psychological safety among nursing students. This study aimed to translate the Psychological Safety in High-Fidelity Simulation (PS-HFS) scale into Japanese (PS-HFS-J) and evaluate its psychometric properties. Methods: Following COSMIN guidelines, the PS-HFS was translated through forward and back translation, reviewed by an expert panel, and tested for face validity via pilot testing. The scale’s reliability and validity were subsequently examined in 263 undergraduate nursing students using confirmatory factor analysis (CFA), Cronbach’s alpha, and intraclass correlation coefficients (ICC). Results: CFA confirmed a good fit of the original four-factor model (CFI = 0.990, TLI = 0.988, RMSEA = 0.026). The scale demonstrated excellent internal consistency (Cronbach’s α = 0.906 overall) and strong test-retest reliability (ICC range: 0.859–0.914). Content validity indices were also high (I-CVI = 0.80–1.00, S-CVI/Ave = 0.94). Conclusions: The PS-HFS-J is a reliable, valid, and culturally adapted instrument for assessing psychological safety in Japanese nursing education. It can support educational research, curriculum development, and faculty training, contributing to safer and more effective simulation-based education. Future studies should examine its applicability across diverse educational levels and clinical contexts. Full article

The growing urgency of the climate crisis has heightened the importance of integrating sustainability into health education. Allied health professionals are well positioned to lead sustainable healthcare efforts, yet evidence suggests a persistent gap between student awareness and formal training. This study explored the perspectives, knowledge, and attitudes of Portuguese allied health students regarding sustainability. An online and anonymous cross-sectional survey was conducted among undergraduate and graduate students across multiple allied health disciplines. The questionnaire assessed general knowledge, perceptions of curricular integration, and attitudes toward sustainable clinical practice. A total of 247 (response rate of 8.23%) students participated, with the majority expressing high concern about climate change and strong support for environmentally responsible healthcare. However, the results revealed inconsistent awareness of healthcare’s environmental footprint and a limited exposure to structured sustainability education. Friedman tests indicated significant variability in students’ knowledge, perceived responsibility, and curricular experiences. Students identified priority themes for curricular inclusion—such as the environmental impact of the health system—and recognized their alignment with the UN Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health) and SDG 13 (Climate Action). The findings highlight the need for the systematic, competency-based integration of sustainability into allied health curricula to support a climate-resilient and ecologically responsible future healthcare workforce. Full article

Bias and fairness issues in artificial intelligence (AI) algorithms are major concerns, as people do not want to use software they cannot trust. Because these issues are intrinsically subjective and context-dependent, creating trustworthy software requires human input and feedback. (1) Introduction: This work introduces an interactive method for mitigating the bias introduced by machine learning models by allowing the user to adjust bias and fairness metrics iteratively to make the model more fair in the context of undergraduate student admissions. (2) Related Work: The social implications of bias in AI systems used in education are nuanced and can affect university reputation and student retention rates motivating a need for the development of fair AI systems. (3) Methods and Dataset: Admissions data over six years from a large urban research university was used to create AI models to predict admissions decisions. These AI models were analyzed to detect biases they may carry with respect to three variables chosen to represent sensitive populations: gender, race, and first-generation college students. We then describe a method for bias mitigation that uses a combination of machine learning and user interaction. (4) Results and Discussion: We use three scenarios to demonstrate that this interactive bias mitigation approach can successfully decrease the biases towards sensitive populations. (5) Conclusion: Our approach allows the user to examine a model and then iteratively and incrementally adjust bias and fairness metrics to change the training dataset and generate a modified AI model that is more fair, according to the user’s own determination of fairness. Full article

Classroom management is an essential yet frequently under-practiced competency in undergraduate teacher education, with important implications for sustainable teacher preparation. This study investigated whether pre-service teachers who feel more capable of managing classrooms also engage more deeply with simulation-based training. Fifty-seven Korean pre-service teachers (15 men, 42 women), all undergraduate students enrolled in a secondary teacher education program at a college of education, completed a five-item classroom-management-efficacy scale, then experienced a 15 min branching simulation that required choosing recognition, punishment, or aggression strategies in response to a disrespectful virtual student. Interest was assessed immediately afterwards with a 24-item instrument covering the four phases of the interest-development model (triggered situational, maintained situational, emerging individual, and well-developed individual). A post-test comparative design and MANOVA revealed that efficacy level had a significant multivariate effect on overall interest (Wilks Λ = 0.78, p = 0.029, partial η² = 0.12). Scheffe contrasts showed that high-efficacy participants outscored their low-efficacy peers on maintained situational and emerging individual interest, p < 0.05, and surpassed the middle-efficacy group in three of the four phases. Repeated measures ANOVA confirmed a general decline from situational to individual interest across all groups (F (3, 52) = 9.23, p < 0.01), underscoring the difficulty of converting short-term curiosity into lasting commitment. These findings position classroom-management efficacy as a key moderator of engagement and support the use of adaptive simulations as sustainable tools for teacher education. By tailoring challenge levels and feedback to participants’ efficacy, guided simulations can foster deeper engagement and promote individualized growth—helping build resilient and well-prepared educators. Full article

The rapid development of science and technology enables technological innovations to change the way of English oral learning. Based on the use of a large language model (LLM), we developed a novel dynamic evaluation system for oral English, LLM-DAELSL, which combines daily oral habits and a textbook outline. The model integrates commonly used vocabulary from everyday social speech and authoritative prior knowledge, such as oral language textbooks. It also combines traditional large-scale semantic models with probabilistic algorithms to serve as an oral assessment tool for undergraduate students majoring in English-related fields in universities. The model provides corrective feedback to effectively enhance the proficiency of English learners through guided training at any time and place. The technological principle of the model involves inputting prior template knowledge into the language model for reverse guidance and utilizing the textbooks provided by China’s Ministry of Education. The model facilitates the practice and evaluation of pronunciation, grammar, vocabulary, and fluency. The six-month tracking results showed that the oral proficiency of the system learners was significantly improved in the four aspects, which provides a reference for other language learning method developments. Full article

Biomedical research training initiatives need rigorous evaluation to achieve national goals of supporting a robust workforce in the biomedical sciences. Higher science self-efficacy is associated with the likelihood of pursuing a science-related research career, but we know little about the psychometric properties of this construct. In this study, we report on a comprehensive validation study of the Science Self-Efficacy Scale using a robust sample of 10,029 undergraduates enrolled across 11 higher education institutions that were part of a biomedical training initiative funded by the National Institutes of Health in the United States. We found the scale to be unidimensional with an Omega hierarchical (ω_h) reliability coefficient of 0.86 and a marginal reliability of 0.91. Within the item response theory framework, we did not detect variation in item parameters across undergraduates’ race/ethnicity; however, one item had parameters that varied across gender identity. We determined that the Science Self-Efficacy Scale can be employed across undergraduates enrolled in science, and researchers can use the scale across a diverse group of students. Implications include ensuring that the scale functions consistently across diverse populations, enhancing the validity of conclusions that can be drawn from survey data analysis. Validating this construct with item response theory models strengthens its use for future research. Full article

Background: Violence against healthcare professionals is a growing public health concern. In Spain, the National Observatory of Aggressions recorded 16,866 cases in 2024, marking a 103.06% increase since 2017. This phenomenon has intensified in recent years, with serious repercussions for both the physical and psychological well-being of healthcare workers, as well as for the quality of care provided. Objectives: This descriptive study examines the knowledge, perceptions, and experiences of workplace aggression among undergraduate students at the University School of Nursing of the Nuestra Señora de Candelaria University Hospital. Materials and Methods: A self-administered ad hoc questionnaire was distributed to 266 students across all academic years to assess their knowledge and to explore their perceptions and experiences of aggression witnessed or experienced during clinical placements. This study was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: The findings revealed significant educational gaps among students regarding how to manage aggressive situations, as well as high levels of concern and an aggression exposure rate exceeding 30%. A statistically significant association was also observed in relation to the academic year. Conclusions: This study provides a foundation for the development of specific training programmes tailored to the needs identified and for enhancing occupational safety in healthcare settings. Full article

Graduate Teaching Assistants (GTAs) play a pivotal role in supporting and advancing the educational mission of universities globally. They are fundamental to a university’s instructional workforce and their roles are critical to the undergraduate student experience. This study examines the experiences and perceptions of GTAs (n = 74) at an R2 institution in the Midwest, U.S. Survey results reveal that the majority of surveyed GTAs have been at the institution for at least one year, teach in face-to-face formats with classes typically ranging from 12 to 30, and allocate 11–20 h/week to their instructional duties, although 30% of respondents report >20 h/week. Survey respondents reported a need for more teaching-focused onboarding, discipline-specific training, and more opportunities for feedback on their teaching practices, while almost 50% reported never engaging with discipline-based education research (DBER) literature. Although departmental and institutional training programs were acknowledged, so too was the perception of their lack of accessibility or relevance. Potential strategies for supporting GTAs, particularly early in their careers, include shadowing opportunities, sustained formal classroom management, and pedagogical training that includes an introduction to (and discussion of) the DBER literature, and a reduced teaching load in the first semester. Universities should prioritize and design GTA professional development using a cognitive apprenticeship framework. This would invest in the undergraduate student experience and directly support an institution’s educational mission. It is also highly effective in preparing highly skilled graduates to enter an increasingly connected global workforce and could positively contribute to an engaged alumni base. Full article

Disparities in the participation of individuals from historically excluded groups in science careers persist, particularly at advanced career stages. In response to this challenge, the National Institutes of Health developed the BUilding Infrastructure Leading to Diversity (BUILD) initiative, aimed at undergraduate institutions to examine evidence-based strategies to engage and retain students across science-related fields. In this longitudinal study, we used propensity score matching and mixed-effects logistic regression models to examine the effects of BUILD on undergraduates’ intentions to pursue science-related research careers. The results indicate that students who participated in BUILD are four times more likely to pursue a science-related research career in comparison to their non-BUILD counterparts. We also discuss and present the need to incorporate research training and mentorship to promote a diverse scientific workforce. Full article

A persistent challenge in training future philology educators is engaging students in deep textual analysis across historical periods—especially in large classes where limited resources, feedback, and assessment tools hinder the teaching of complex linguistic and contextual features. These constraints often lead to superficial learning, decreased motivation, and inequitable outcomes, particularly when traditional methods lack interactive and scalable support. As digital technologies evolve, there is increasing interest in how Artificial Intelligence (AI) can address such instructional gaps. This study explores the potential of conversational AI chatbots to provide scalable, pedagogically grounded support in philology education. Using a mixed-methods case study, twenty-six (n = 26) undergraduate students completed structured tasks using one of three AI chatbots (ChatGPT, Gemini, or DeepSeek). Quantitative and qualitative data were collected via usability scales, AI literacy surveys, and semi-structured interviews. The results showed strong usability across all platforms, with DeepSeek rated highest in intuitiveness. Students reported confidence in using AI for efficiency and decision-making but desired greater support in evaluating multiple AI-generated outputs. The AI-enhanced environment promoted motivation, autonomy, and conceptual understanding, despite some onboarding and clarity challenges. Implications include reducing instructor workload, enhancing student-centered learning, and informing curriculum development in philology, particularly for instructional designers and educational technologists. Full article