Exploration problem-based learning in mathematics learning in higher education: A bibliometric review

To identify quality-improvement opportunities from the experiences of Black and Latina severe maternal morbidity (SMM) survivors and their families. This study explored the experiences of Black and Latina survivors of SMM through qualitative interviews. A Community Advisory Board of SMM survivors and community representatives guided the study design, recruitment, and analysis. We recruited participants through community outreach and used a trauma-informed approach to interviews. Recruitment concluded after 17 survivors when the team determined through analytic discussion that subsequent interviews reinforced rather than expanded the existing thematic structure. We used reflexive thematic analysis to identify key themes related to prenatal, intrapartum, and postpartum care experiences. The overarching theme of wanting to be seen and heard as a whole person emerged across interviews. Five subthemes characterized the struggles participants faced during and after SMM events: 1) If I Don't Appear a Certain Way, I Won't Get Adequate Care, reflecting experiences of bias and racialized expectations; 2) What Happens Now and What Happens Next?, describing poor communication and uncertainty during care transitions; 3) Advocacy: If I Don't Speak Up, Who Will? If I Do Speak Up, Who Will Hear Me?, highlighting the burden of self-advocacy in clinical settings; 4) Having Another Child at What Cost?, capturing fear and trauma shaping future reproductive decision making; and 5) Long-term Consequences for Mental and Emotional Health, describing persistent psychological effects. Through iterative interpretation and prioritization with the Community Advisory Board, the themes informed multilevel quality-improvement recommendations. These included policy changes such as insurance coverage for doulas and improved parental leave; organizational and clinician-level strategies such as extended perinatal visits, workforce diversity, and training in bias and trauma-informed care; and patient-level supports emphasizing advocacy resources, education, and relationship-centered care. Experiences of SMM survivors and their support persons revealed systemic barriers and a strong desire to be seen and treated as whole persons, with attention to physical, emotional, and mental well-being. Participants highlighted issues such as racial marginalization, clinician biases, and insufficient support and education. These findings align with Community Advisory Board members' experiences and existing research. We offer recommendations, co-developed with the Community Advisory Board, based on these findings to improve care at the policy, organizational, clinician, and patient levels.

Mapping emerging trends in hydrogen fuel cell technology for sustainable transportation: Insights from bibliometric and topic modeling analyses

This study mapped the global intellectual and thematic structure of nursing leadership research by integrating three often separate domains: governance, succession, and equity. It examined how these domains are connected in the literature across nursing education and practice. We conducted a bibliometric analysis of Web of Science Core Collection records (1970-2025) using a tri-lens search strategy, yielding 315 peer-reviewed articles. We reported publication and citation trends (including total citations and H-index), then performed co-citation and co-word network analyses in VOSviewer (association-strength normalization). Thematic mapping was conducted in Biblioshiny (bibliometrix, R) using Louvain clustering and Callon centrality-density to classify themes as motor, basic, niche, or emerging/declining. The dataset accrued 4,402 citations (H-index = 31), with publication growth accelerating after 2015. Co-citation analysis identified four intellectual pillars: (1) leadership capacity building, (2) equity-focused leadership, (3) transition and workforce development, and (4) policy-driven leadership preparation. Co-word analysis also produced four thematic clusters: academic leadership, simulation-based preparation, equity/racism in leadership, and staff development across education-practice-research contexts. Across both maps, governance-, succession-, and equity-related topics were adjacent but largely concentrated in separate cluster communities, with limited cross-cluster connectors. Nursing leadership research is expanding but remains structurally fragmented across governance, succession, and equity domains. The key contribution of this study is the tri-lens evidence that these domains are conceptually related yet weakly integrated in empirical knowledge structures. Findings support the need to align governance design, leadership pipeline development, and equity mechanisms in nursing education and leadership planning.

Research linking pediatric craniofacial growth, airway physiology, and sleep-disordered breathing has expanded rapidly in recent years. However, a structured overview of global research trends in this interdisciplinary field remains limited. This study aimed to map publication patterns, international collaboration networks, and evolving thematic structures in pediatric craniofacial growth and airway research between 2020 and 2024. A bibliometric analysis was conducted using records retrieved from the Web of Science Core Collection. Original research articles and reviews published between 2020 and 2024 were included. Annual publication trends, international collaboration networks, keyword co-occurrence, and thematic evolution were analyzed using Bibliometrix and VOSviewer. A total of 1214 publications were included. Annual output showed a positive but non-significant upward trend over time. China, Italy, and the United States were the most productive countries, with the United States also occupying a central position in the international collaboration network. Keyword mapping revealed major thematic clusters related to airway function and OSA, craniofacial growth, congenital anomalies, surgical adaptation, and three-dimensional imaging. Thematic evolution analysis demonstrated a shift from broadly anatomical growth-focused research toward clinically oriented and disease-specific topics in the later years of the study period. Contemporary pediatric craniofacial research is characterized by expanding global collaboration and a progressive shift toward integrative physiologic and clinically focused frameworks linking dentofacial development with respiratory function. These findings highlight clinical priorities and may inform future interdisciplinary research directions in pediatric airway management and growth-related orthodontics.

Global Research Trends in Cancer-Associated Atrial Fibrillation: A Bibliometric Analysis of the Cardio-Oncology Interface.

Ontologies are essential for structuring biomedical knowledge, supporting semantic integration, reasoning, and data interoperability. In vaccinology, ontology population is particularly critical, as vaccines span diverse domains. A well-defined Vaccine Ontology (VO) enables consistent knowledge representation, integration across datasets, and supports applications such as decision support, literature mining, and semantic search. However, manual ontology population is tedious, time-consuming, and difficult to maintain in this dynamically evolving domain, underscoring the need for automated or semi-automated population approaches. We present a semi-automated pipeline that uses Bidirectional Encoder Representations from Transformers and Topic Modeling (BERTopic) to extract ontology-relevant concepts from biomedical text. To evaluate the effectiveness of this automated approach, the method is applied to Plotkin's Vaccines corpus, a leading reference text in vaccinology that synthesizes scientific, clinical, and policy perspectives on vaccines. The workflow integrates multiple natural language processing (NLP) components: document preprocessing with spaCy part-of-speech tagging and vectorization, sentence embeddings generated by a lightweight transformer model (all-MiniLM-L6-v2), dimensionality reduction with Uniform Manifold Approximation and Projection (UMAP), clustering with Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), and topic representation via Class-based Term Frequency - Inverse Document Frequency (c-TF-IDF). To guide topic discovery toward vaccine-relevant concepts and filter irrelevant terms, the pipeline incorporates a curated set of vaccine-focused terms derived from an existing vaccine ontology as seed words to influence topic representations, while preserving the unsupervised nature of the clustering process. To enhance interpretability, the pipeline employs Keyword extraction using BERT embeddings (KeyBERT) for automatic keyword-based labeling, supplemented with disambiguated descriptive labels, and Bidirectional and Auto-Regressive Transformer (BART) summarization for topic-level summaries. The resulting hierarchical topic structures are further refined through a tree-merging module that unifies multiple topic hierarchies into a coherent ontology-like representation. The extracted topics are reviewed by the Subject Matter Experts (SMEs) to filter irrelevant terms and then mapped to Vaccine Ontology, a well-established ontology to assess their relevance and coverage, demonstrating how automated methods can reduce the labor-intensive effort required for manual ontology population. The script is customized to generate a varying number of topics and keywords. In this study, the top 50 topics with 10 keywords per topic were extracted for each chapter of Plotkin's vaccines. The pipeline produced coherent topic clusters representing key themes in vaccinology, including immune mechanisms, pathogen-specific vaccines, and vaccine types. The hierarchical tree-merging process is used to illustrate how semantically related concept groupings emerge and can suggest potential ontology subdivisions. This serves as a visualization of conceptual relationships derived from the data and is particularly helpful for SMEs to review, interpret, and validate candidate concepts. This study demonstrates the feasibility of BERTopic-driven, a semi-automated approach for extracting ontology-relevant concepts from biomedical texts. The method was evaluated using a foundational vaccinology corpus and assessed against an existing, well-developed vaccine ontology to determine the relevance and coverage of the extracted topics. Mapping the topics to the established ontology enabled identification of concept alignments and irrelevant terms, which were subsequently reviewed by SMEs. The results show that the proposed approach can effectively surface meaningful, ontology-relevant concepts while significantly reducing the time and effort for manual population, thereby providing a scalable strategy for supporting ontology maintenance and enrichment.

ABSTRACT Digital‐twin (DT) research has expanded rapidly across engineering and cyber‐physical systems, yet explicit adoption and consolidation of DT concepts in entomology remain limited and fragmented. This study addresses this imbalance through a two‐track synthesis. A Web of Science–based bibliometric analysis of the global DT domain from 2014 to 2025 establishes an external benchmark for growth dynamics, thematic structure, and prevailing implementation emphases. Because insect‐specific DT publications remain too sparse for stable bibliometric inference, entomological evidence is organized through a scale‐aware conceptual framework spanning individual, colony, and population or ecosystem levels, combined with a four‐level maturity scheme that distinguishes monitoring, shadowing, predictive, and intervening systems. The maturity lens clarifies that operational progress depends less on increasing model complexity than on strengthening data–model coupling and decision relevance. The transition from monitoring to shadowing requires explicit observation‐process models that map imperfect measurements to latent biological states while accounting for detection bias, missingness, and measurement error. The transition from shadowing to prediction is constrained by structural model error and uncertainty propagation under nonstationary environmental forcing. Movement toward intervention maturity requires an explicit decision layer that formalizes trade‐offs among effectiveness, cost, regulatory constraints, and ecological side effects. Representative case studies demonstrate how operational coherence can be achieved under scale‐specific constraints, while also revealing dominant bottlenecks including external validity at the individual scale, identifiability at the colony scale, and effort–abundance confounding at landscape scales. The resulting framework provides criteria for cumulative comparison and a roadmap for operationally coherent insect DTs that support risk‐aware decision making.

Artificial Intelligence-Based Thematic Analysis of Biomedical Literature for Precision Nutrition.

From LSA to LLM: Evolution and limitations of topic modelling methods for biodiversity conservation

Conversational companion robots have been studied as one approach to ameliorating loneliness in older people. Large language models (LLMs) can enable flexible conversational ability in companion robots, but acceptability and suitability remain uncertain. We explored older people's expectations and concerns regarding an LLM-supported companion robot for loneliness support, with a focus on acceptability rather than efficacy. We conducted a UK-Japan qualitative study comprising hands-on focus groups for community-dwelling older adults in London (n = 17) and a one-week in-home use with follow-up interviews in Osaka among outpatients with mild cognitive impairment (MCI; n = 8). Transcripts were analysed using reflexive thematic analysis; for cross-site reporting, Japan themes/codes were mapped onto the thematic structure generated from the larger UK dataset. Descriptive questionnaire measures and at-home conversational log metrics were collected to contextualise qualitative findings. Participants saw value of the companion robot as a support for older people with loneliness but emphasised that acceptability depends on interaction mechanics and user agency. Three cross-context themes were identified: (1) Practical use and functionality (response latency, turn-taking, desired features, and controllability in home use); (2) Emotional connection and engagement (social presence alongside perceived limits in conversational fit and depth); and (3) Ethical and societal reflections (privacy/data governance, access, and concerns about substituting for human contact). LLM-supported companion robots may provide acceptable low-intensity support for some older people, including those with MCI, provided that usability, user-adjustable control and ethical governance are prioritised. Longer deployments are needed to evaluate potential sustained benefit and burden.

This study aims to map the development of research on digital transformation in primary education through Learning Management Systems (LMS) published between 1989-2025 within the broader field of educational technology. The study focuses on four main aspects: (1) publication performance based on year, contributing countries, sources, and document types; (2) thematic structures, including dominant keywords, thematic evolution, and author collaboration networks; (3) intellectual structure analysis through co-citation, bibliographic coupling, and citation network mapping; and (4) the representation of adaptive learning within LMS-related research in primary or elementary education. The method used was bibliometrics utilising the Scopus database and analysed through RStudio (Bibliometrix/Biblioshiny), VOSviewer and Microsoft Excel. A total of 137 articles from 111 sources were included to generate comprehensive publication performance metrics and research network visualisations. The findings indicate that LMS research in primary education is gaining global attention, although publication growth remains relatively stable. Key themes include educational technology, digital literacy, gamification, adaptive learning and learning analytics. China and Indonesia emerge as major collaboration hubs, while Computers & Education dominates citation influence. The field is shifting from general e-learning towards adaptive and AI-supported LMS. This study contributes theoretically by clarifying the intellectual, conceptual, and collaborative structure of LMS research in primary education, providing a systematic foundation for understanding its evolution towards data-driven and personalised learning environments.

This study aims to analyze the development of global value chains (GVC) research within the fields of development and business economics using a bibliometric approach. Data were collected from the Scopus database and analyzed using VOSviewer to identify publication trends, influential articles, collaboration networks, and thematic structures. The results show a consistent increase in the number of publications, indicating growing academic interest in GVC. Citation analysis reveals that highly influential studies are dominated by themes related to digital transformation, sustainability, and global economic systems. Co-authorship analysis highlights the presence of key scholars who act as central connectors within research networks, although collaboration remains partially fragmented. Meanwhile, co-occurrence analysis demonstrates that recent research increasingly integrates topics such as sustainable development, circular economy, and innovation. Overall, the findings suggest that GVC research has evolved into a multidisciplinary field that combines economic, environmental, and technological perspectives. This study contributes to the literature by providing a comprehensive mapping of research trends and identifying future directions for GVC studies.

Design thinking has emerged as a significant pedagogical approach in STEM (Science, Technology, Engineering, and Mathematics) education, promoting creativity, problem-solving, and innovation among learners. Despite its increasing relevance, the knowledge base surrounding design thinking in STEM education remains fragmented across disciplines. This study conducted a comprehensive science mapping analysis to examine the intellectual, conceptual, and thematic structure of the field. A total of 897 Scopus-indexed publications from 2010 to 2025 were analyzed using citation, co-citation, and co-word techniques through VOSviewer. Results showed a consistent growth in scholarly output, with the United States (US), China, and Australia identified as the top contributing countries. Citation analysis highlighted influential foundational works that anchor the field and shape ongoing research directions. Co-citation mapping revealed interconnected intellectual traditions related to engineering education, reflective practice, and pedagogical innovation. Co-word analysis further identified three dominant thematic clusters: design-oriented pedagogies, teacher professional development, and interdisciplinary applications of design thinking within STEM learning environments. Overlay visualization of keywords demonstrated an emerging shift toward contemporary priorities, including sustainability, artificial intelligence (AI), and inclusive education, indicating a broadening of the field’s pedagogical and societal relevance. These findings provide a structured understanding of how design thinking has evolved within STEM education, offering insights that can guide future scholarly inquiry. The study highlights the importance of transdisciplinary collaboration and context-responsive pedagogical models in strengthening the integration and long-term sustainability of design thinking in STEM education.

Strategic management is a key lens for understanding how public organizations respond to increasing performance demands, yet existing studies remain fragmented and lack systematic synthesis. This study maps the evolution of strategic management research in the public sector, identifies core and emerging themes, and examines shifts in research trajectories over time. Using the PRISMA protocol, 5,749 records were screened and reduced to 132 Scopus-indexed publications. Bibliometric analysis using Biblioshiny® identified publication patterns and influential contributors, while topic modeling using Latent Dirichlet Allocation (LDA) in Python uncovered latent thematic structures and changes in topic probabilities over time. The findings reveal ten topics grouped into four major domains: organizational learning, leadership, reform and change, and urban innovation. The literature shows a shift from a dominant focus on strategic planning and performance tools toward change resistance, leadership engagement, and adaptive learning capabilities. Leadership remains a central driver, while increasing attention to urban innovation reflects the growing importance of collaborative governance and digital transformation. Overall, this study provides a methodological contribution by integrating bibliometric analysis for the macro-mapping of research actors and Latent Dirichlet Allocation (LDA) topic modeling to extract latent thematic structures at a granular level.

Abstract The GCSE syllabus changes from 2014 introduced an element of medieval history across all examination boards. The content and structure of these new topics largely reinforces the traditional stereotypes of Key Stage 2 and 3 school history. Pressures of external examinations combined with insecure teacher specialist knowledge and few opportunities for training do not create a rich pupil experience. The government National Curriculum review (2025) includes recommendations for further use of oracy and Drama in schools as well as reducing content in the GCSE History syllabus. This article shows how the famous Old English poem Beowulf can be used as a teaching tool in History lessons to better inform pupil learning of early medieval England in relation to Key Stage 3 and to specific GCSE papers. It finds that using Beowulf in the classroom would draw upon the emotions and senses to connect landscape and memory, artefacts and conventional historic narratives in an innovative and creative way to deepen the hinterland of pupil knowledge and build upon those government recommendations. It suggests that we should reflect on how ‘history’ itself is constructed and how we could reimagine the past as scholars, teachers and students.

Research on caffeine biosynthesis in Coffea canephora has expanded across multiple disciplines, yet its global genetic research trends remain insufficiently mapped. This study aimed to analyze the development and thematic structure of genetic research on caffeine biosynthesis in C. canephora using a bibliometric approach. Data were retrieved from the Scopus database through keyword-based sampling and filtered based on relevance to genetic and biosynthetic aspects. Bibliometric analyses were conducted to examine publication trends, authorship patterns, country contributions, and keyword co-occurrence networks. The results show a significant increase in publications since the early 2000s, with dominant contributions from the United States, Brazil, and China. Keyword mapping reveals four major research clusters, including plant metabolism, clinical and nutritional studies, experimental models, and genetic variability. However, studies explicitly focusing on the genetic regulation of caffeine biosynthesis, particularly involving N-methyltransferase genes, remain relatively limited compared to broader multidisciplinary themes.These findings indicate that caffeine research in C. canephora is highly interdisciplinary but still lacks a strong emphasis on genetic mechanisms, highlighting the need for more targeted molecular and genomic studies to support coffee improvement and functional trait development.

Purpose The Independent Review of Greater Manchester Mental Health NHS Foundation Trust published in 2024 re-emphasised that the abuse of patients within psychiatric institutions continues to occur. The findings and recommendations of inquiries are often so specific to the individual context that general principles for application to other institutions cannot be drawn. To reduce the likelihood of patient abuse, it is imperative that such principles are identified. This study aims to identify the common themes contributing to patient abuse across institutions and construct a generalisable framework that enables analysis and mitigation of underlying causes by different health-care professionals. Design/methodology/approach Using thematic analysis, the authors qualitatively analysed inquiries into six psychiatric institutions. Inquiries were selected to represent a variety of types of institutions (learning disability, general psychiatric and forensic services) across a wide timescale. Findings The identified thematic structure comprised three levels at which processes relevant to the behaviour of concern operate (“Proximal”, “Organisational” and “System” Dynamic), with a fourth, cross-cutting theme of how concerns are responded to. Originality/value This study has enabled the development of a novel and generalisable framework to help understand the levels at which processes contributing to abuse occur. The framework can be used to assess and mitigate the incidence of abuse within psychiatric institutions, as well as educate and empower others to recognise when abuse may be occurring. It will benefit from further empirical testing to support its use.

Purpose This study aims to examine the incidence and contextual use of slang, profanity, expletives or vulgar language (SPEVL) in peer-reviewed scientific literature. Focusing specifically on the term “bullshit” (BS), it explores where and in what contexts such language appears and assesses whether ethical guidelines on respectful language in academic publishing are adequate. Design/methodology/approach A bibliometric analysis was carried out using the Scopus database on February 20, 2025. Publications containing the term BS in the title, abstract or keywords were identified, resulting in a dataset of 481 documents. Microsoft Excel and VOSviewer were used to examine temporal, disciplinary, institutional, geographic and citation patterns. A keyword co-occurrence analysis was conducted to explore the thematic structure of the literature. Findings The term BS was most frequently used in the arts, humanities and social sciences. Its usage has notably increased over the past decade. Most publications were in English and appeared in reputable journals, with a relatively high citation impact (FWCI = 2.5). Thematic clusters included psychological, sociocultural, educational, theoretical and organizational contexts. Research limitations/implications This study only considers records indexed in Scopus and does not include full-text content. Future research could explore other databases or conduct qualitative analyses to investigate the tone and purpose of SPEVL use in context. Additionally, clearer ethical guidance from publishers regarding language use is needed. Originality/value This paper is among the first to empirically identify SPEVL in the academic literature. It offers valuable insights for editors, publishers and those concerned with ethics regarding the boundaries of acceptable academic language and editorial responsibility.

Despite the rapid digitization of intangible cultural heritage (ICH), the complex mechanisms governing how users interact and co-create knowledge in digital spaces remain underexplored. Understanding the internal dynamics and engagement logic of these interactive environments is therefore essential to developing sustainable heritage knowledge ecosystems. Conceptualizing the Zhihu community as such an ecosystem, this study investigates ICH thematic structures, knowledge demands, and user participation. By employing an LLM-refined BERTopic framework, this study identified 36 core topics and mapped them onto a four-layer architecture (Cultural Resource Layer, Action Subject Layer, Social Support Layer, and External Interaction Layer) and five knowledge demand dimensions (Basic Knowledge, Cultural Experience, Professional Development, Protection and Inheritance, and Modern Application) through weighted semantic similarity and Spearman correlation analysis. The results reveal a structural configuration dominated by the External Interaction Layer. A dual-track demand mechanism was identified, comprising a professionalized ability-oriented pathway and an affective experience-driven mode. Furthermore, deep engagement was primarily catalyzed by topics that integrate technology, action, and narrative, rather than structural prominence alone. The ICH knowledge ecosystem was characterized by an outward-looking and emotion-driven orientation. This research study contributes an ecosystem framework to heritage information while providing insights for practitioners to optimize digital ICH information services through multi-dimensional semantic integration and public co-creation.