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Background: The Obesity Policy Engagement Network (OPEN)-EU manifesto, led by the European Association for the Study of Obesity (EASO), underscores the urgent need for enhanced, evidence-based education for healthcare professionals (HCPs) involved in obesity care. This scoping review aims to identify and profile relevant literature that reports on obesity-related competencies for HCPs and to synthesise identified competencies into obesity competency domains and subdomains to inform HCP education. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute and PRISMA guidelines, including a comprehensive search strategy targeting PubMed, CINAHL Plus and ERIC databases (2014–2024). Based on clear inclusion criteria, full-text articles which focused on obesity-related competencies in HCP education were identified. Thematic analysis of all reported competencies was conducted to generate obesity-related competency domains and subdomains. Results: Twenty-two studies were included in the scoping review (out of 1286 unique records resulting from database searches) with a diversity of HCP disciplines represented. Multiple obesity competencies were identified, spanning eleven key domains: Obesity Background, Clinical Assessment, Clinical Management, Evidence-Based Practice, Communication, Professionalism/ethical standards, Patient Centred Care, Advocacy/influencing, HCP Education, Public Health/Health promotion and Health Systems. The most frequently reported competencies fell within the domains of Clinical Assessment and Clinical Management. Conclusion: This scoping review identified and synthesised obesity related competencies from HCPs education and professionalisation literature into eleven key domains and related subdomains. These findings highlight the multifaceted nature of obesity management, postulating the usefulness of comprehensive, competency-based training for HCPs. © The Author(s) 2025.

Objective: To construct precise learner personas for medical students by integrating social sensing data with the Entrustable Professional Activities (EPAs) framework, thereby informing targeted pedagogical strategies. The study aims to address the gap in integrating behavioral data with competency assessment for multidimensional learner characterization. Methods: Purposive sampling was employed to recruit 45 clinical interns (June–December 2024) based on data saturation principles. Data collection combined semi-structured interviews, social sensing technology (multimodal data from medical forums and clinical sensor arrays with AES-256 encryption for privacy protection), and EPA-based clinical observations. Thematic analysis via NVivo 12 Plus was used to extract features, with manual coding validating theoretical saturation after 45 interviews. Results: A four-dimensional persona framework (learning attitude, clinical competence, social interaction, self-improvement awareness) was discovered, yielding five archetypes: Proactive Achievers (28.89%), Skilled Practitioners (20.00%), Social Collaborators (17.78%), Passive Followers (24.44%), and Ambiguous Improvers (8.89%). Intergroup differences in EPA-assessed clinical skills were significant (ANOVA, p < 0.05 for all dimensions). Conclusion: The multimodal framework enables data-driven learner characterization, providing evidence for personalized medical education. Future work will validate persona utility in educational interventions. © The Author(s) 2025.

Objective: This study was to understand the experiences of nursing students in vocational colleges whose clinical nursing procedures were refused by patients, providing reference for the management of nursing students. Methods: Using purposive sampling, nursing students and patients were recruited at a certain tertiary hospital in Xiangyang City from June 2023 to April 2024. Data were collected through in-depth face-to-face interviews and analyzed using Colaizzi’s seven-step analysis. Results: A total of 37 interviews were conducted in this study, and by the time the 35rd interview was conducted, the data reached saturation. Finally, 17 nursing students and 16 patients were included. A total of 3 themes and 10 subthemes were identified: educational background (educational discrimination; educational duration restrictions), patient factors (psychological shadow; stereotypical thinking about interns; patient’s emotional state; severity of the patient’s condition; fear of invasive procedures), and nursing student factors (low professional identity; lack of proficiency in procedures; poor coping skills). Conclusion: The refusal of patients to allow nursing students to perform procedures was influenced by a variety of factors. It is necessary to analyze the causes, explore solutions, and take measures to improve the efficiency of nursing students’ clinical internships. © The Author(s) 2025.

Through rigorous economic analysis, economists in the Federal Trade Commission’s Bureau of Economics support the FTC’s missions of protecting consumers and maintaining competition. This article first describes how tools from labor markets have informed research at the FTC on merger effects, as well as recent research on labor economics by FTC economists. The article then provides four examples of how FTC economists have applied economic analysis to their casework. The first example is of the economic analysis of harm to consumers who signed up for a training program based on misleading information. The second describes the economic analysis that was done in support of the litigation to block the Kroger-Albertson’s supermarket merger. The third describes a methodology that can be used to estimate the harm to workers who are deceived about the earning potential in the gig economy. The last is a discussion of the analysis of the anticompetitive effects of loyalty discounts offered by a platform in the Surescripts matter. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2025.

Clinical training preparedness is defined as the degree of competency of a veterinary student to work and learn at an expected level. The aim of this study was to quantitatively investigate the level of importance and agreement attached to each of 91 clinical training preparedness factors by practice-based clinical supervisors and faculty veterinary academics in three veterinary programmes with remote distributed models of workplace-based clinical training. The data was collected using an online questionnaire from academics and preceptors at the School of Veterinary Medicine, University of Surrey; the College of Veterinary Medicine, University of Arizona; and the College of Veterinary Medicine, Western University of Health Sciences. The participants were requested to rate each factor according to an ordinal five-point impact Likert scale. Impact was defined as how much effect a factor would have on a student being able to learn and participate. There were 115 preceptor and 44 academic responders. There was a high level of agreement between the preceptors and academics within, between and across each of the three schools for the factor rating mean, median and mode values. The impact on learning and engagement were all rated moderate or higher. The outcomes of this quantitative survey provide strong evidence that the student preparedness factors investigated were considered important by the preceptors and the academics. When adopting the preparedness framework within the curriculum it is important that academics, preceptors and students share a common understanding of what preparedness for clinical training means. © 2025 Elsevier Ltd

In STEM education, the development of thinking skills is increasingly viewed as essential for preparing students to navigate complex and uncertain futures. However, the field remains conceptually fragmented, with diverse and sometimes overlapping terminologies, definitions, and theoretical models. This study presents an LLM-powered systematic literature review, following the ENTREQ framework to ensure methodological transparency and rigor, aimed at identifying and mapping the thinking skills most frequently discussed in STEM higher education over the past decade. Using the AI tool Elicit, 170 peer-reviewed journal articles were analyzed. The review synthesizes definitions, conceptual frameworks, and interrelations among skills such as Critical, Systems, Computational, Mathematical, Spatial, Creative, Design, Reflective, Scientific, and Complexity Thinking. The results reveal eleven core thinking skills and highlight the conceptual overlaps and distinctions between them. AI use not only expedited literature screening and coding but also mitigated selection bias by systematically applying inclusion criteria, overcoming common limitations of manual reviews such as inconsistency and time lag. This overview contributes to greater clarity and consistency in the field and provides a foundation for future curriculum design and research, supporting a more coherent integration of thinking skills in STEM education. © The Author(s) 2025.

Civil engineers’ training requires developing competencies and skills that allow them to face the challenges of professional practice. In this context, this study explores the implementation of the Extreme Collaboration (XC) methodology in an integrative civil engineering project (Capstone project) to evaluate its impact on the development of professional competencies. By integrating the Building Information Modeling (BIM) methodology and applying Bloom’s Taxonomy, the aim is to determine whether XC contributes to bridging the gap between academic training and professional practice requirements, as established by frameworks such as ABET and CDIO. Through a detailed analysis of the collaborative processes and the results obtained, the present research demonstrated that XC represents an effective pedagogical strategy to foster complex skills, such as teamwork, problem-solving, and communication, essential in the training of civil engineers capable of facing the challenges of the 21st century. © The Author(s) 2025.

This study explores the integration of the educational philosophy of Science, Technology, Engineering, Arts, and Mathematics (STEAM) with deep learning technologies for the development of high school English course resources. By introducing deep learning models, particularly the Transformer architecture, the study enables automatic generation and personalized delivery of instructional content, thereby enhancing the intelligence and relevance of course resources. An innovative Transformer-based framework incorporating STEAM-related semantic features is designed and implemented. The framework is trained on a large-scale, preprocessed English text dataset collected from 300 high school students participating in STEAM-integrated English learning tasks, with data from 150 students forming the core corpus for model training. The model employs an encoder-decoder architecture and is optimized using the Adam optimizer to support the generation of high-quality content tailored to diverse teaching objectives. Through on-site teaching experiments conducted with the 300 high school students, the results demonstrate that, the model’s performance is rigorously evaluated through metrics such as Bilingual Evaluation Understudy score (0.78), innovation index (0.75), and content diversity (0.70). Results reveal that the proposed model outperforms comparative models (Model A and Model B) in language generation accuracy, innovation, and content diversity, highlighting its superior capability in producing high-quality English teaching resources. Although the model demonstrates promising results, its implementation in resource-limited environments presents challenges, highlighting the need for further refinements. Nonetheless, these findings demonstrate the model’s potential to revolutionize English teaching by enhancing resource quality and offering a more efficient, innovative approach to course development. © The Author(s) 2025.

Although it is believed that letting learners explore mathematics within their cultural contexts is an effective way to teach and learn the subject and helps them understand its relevance in daily life, there is a limited understanding of the opportunities and challenges associated with using the ethnomathematics program as a pedagogical tool for mathematics education. Consequently, the purpose of this review was to provide evidence-based insights into the opportunities that learners have when utilizing the ethnomathematics program as a learning tool, as well as the challenges that mathematics teachers encounter when using it as a pedagogical tool. This review included 38 articles from Scopus, JSTOR, EBSCOhost, and ProQuest. Upon analysis, the articles revealed that the opportunities of using the ethnomathematics program as a learning tool include, among others, augmenting conceptual understanding, enhancing mathematics achievement, inculcating sustainable development skills, supporting income generation and poverty alleviation, instilling cultural values, and reinforcing change and transformation. Meanwhile, the challenges that mathematics teachers face include, among others, the scarcity of local instructional materials, unclear curriculum guidelines and teacher policies, their perceptions and knowledge, cultural authenticity and appropriation, and assessment and evaluation using cultural knowledge. The findings emphasize the need to incorporate the ethnomathematics program into mathematics education curricula and train mathematics teachers accordingly to utilize it as a pedagogical approach. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

Cognitive processes, including understanding, thinking, and interpretation, are necessary to influence safe behaviour in cyberspace. However, among Technical and Vocational Education and Training (TVET) youth, educational focus prioritises technical skills development over cognitive and digital skills. Furthermore, systematic and coherent approaches are lacking to provide students with consistent, quality learning experiences that enhance their understanding of cyber ethics. The research model integrates the cognitive appraisal components based on the Protection Motivation Theory (PMT) with three social learning strategies: cyber ethical digital games, lecturer reminders, and motivational impact of achievement certificates, to understand TVET youth ethical decision-making in cyberspace refers to PAPA model (privacy, accuracy, property, and accessibility). The research employed a quantitative approach using a survey method with questionnaire instruments for data collection, with a random sample of 340 respondents selected from six community colleges around Selangor. Partial least squares structural equation modelling (PLS-SEM) analysis through SmartPLS version 4 software was used to analyse hypotheses and validate the developed model. Hypothesis testing revealed that 12 out of 14 hypotheses were significant, with Perceived Severity (PS), Self-Efficacy (SE), and Response Efficacy (RE) suggesting relationships in TVET youth’s cyber ethical behaviour. The three social learning strategies also demonstrated significant relationships with cyber threats’ appraisal and response processes. The developed Cyber Ethical Behavioural (CEB) model enhances the understanding of TVET youth’s cyber ethical behaviour and promotes the coordination of cyber ethics knowledge enhancement in TVET institutional environments, aligning with new technological developments such as Artificial Intelligence (AI). © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).