Collaborative Research Network Research Articles

Identifying Risk of Stillbirth Using Machine Learning

(Am J Obstet Gynecol. 2023;229:327:e1–16) A tool that could help identify women at risk for stillbirth would be a welcome addition to clinical practice. Machine learning models, which can look at relationships between variables in large data sets, was investigated in this article. This study’s aim was to refine a machine learning model to predict stillbirth using data available prior to the gestational age of viability (22 to 24 wk). The researchers performed a secondary analysis of data in the Stillbirth Collaborative Research Network (SCRN), a study database of 982 stillbirths and 3000 representative live births from 2006 to 2009. The study included patients who delivered a live or stillborn fetus at >18 weeks’ gestation from 59 hospitals in 5 states (Georgia, Massachusetts, Rhode Island, Texas, and Utah). The data set included 6000 measures collected from interviews with the mother, postmortem pathological exam, cause of death analysis, and medical record Abstractsion. Subsequently 101 risk factor variables were identified and used in the model. These included maternal and biological father demographics, family history, maternal health history, prenatal lab data, fetal genetics, second-trimester screen, prenatal care history, ultrasound, and social determinants of health.

Harmonizing data on correlates of sleep in children within and across neurodevelopmental disorders: lessons learned from an Ontario Brain Institute cross-program collaboration

There is an increasing desire to study neurodevelopmental disorders (NDDs) together to understand commonalities to develop generic health promotion strategies and improve clinical treatment. Common data elements (CDEs) collected across studies involving children with NDDs afford an opportunity to answer clinically meaningful questions. We undertook a retrospective, secondary analysis of data pertaining to sleep in children with different NDDs collected through various research studies. The objective of this paper is to share lessons learned for data management, collation, and harmonization from a sleep study in children within and across NDDs from large, collaborative research networks in the Ontario Brain Institute (OBI). Three collaborative research networks contributed demographic data and data pertaining to sleep, internalizing symptoms, health-related quality of life, and severity of disorder for children with six different NDDs: autism spectrum disorder; attention deficit/hyperactivity disorder; obsessive compulsive disorder; intellectual disability; cerebral palsy; and epilepsy. Procedures for data harmonization, derivations, and merging were shared and examples pertaining to severity of disorder and sleep disturbances were described in detail. Important lessons emerged from data harmonizing procedures: prioritizing the collection of CDEs to ensure data completeness; ensuring unprocessed data are uploaded for harmonization in order to facilitate timely analytic procedures; the value of maintaining variable naming that is consistent with data dictionaries at time of project validation; and the value of regular meetings with the research networks to discuss and overcome challenges with data harmonization. Buy-in from all research networks involved at study inception and oversight from a centralized infrastructure (OBI) identified the importance of collaboration to collect CDEs and facilitate data harmonization to improve outcomes for children with NDDs.

Enthesitis in a European registry-based cohort of patients with psoriatic arthritis treated with tumour necrosis factor inhibitors: clinical burden, patient-reported outcomes, and treatment response

Objective To explore the registration of enthesitis among biologic-naïve patients with psoriatic arthritis (PsA) initiating tumour necrosis factor inhibitor (TNFi) treatment across 12 European registries, compare the disease burden and patient-reported outcomes (PROs) between patients with and without enthesitis, and assess the enthesitis treatment response. Method Demographics, clinical characteristics, and PROs at first TNFi (TNFi-1) initiation (baseline) were assessed in patients with PsA, diagnosed by a rheumatologist, with versus without assessment of entheses and between those with versus without enthesitis. Enthesitis scores and resolution frequency were identified at follow-up. Results Of 10 547 patients in the European Spondyloarthritis (EuroSpA) Research Collaboration Network initiating TNFi, 1357 underwent evaluation for enthesitis. Eight registries included a validated scoring system for enthesitis. At baseline, 874 patients underwent entheses assessment [Maastricht Ankylosing Spondylitis Enthesitis Score (MASES) 485 patients, Spondyloarthritis Research Consortium of Canada (SPARCC) 389 patients]. Enthesitis was detected by MASES in 170/485 (35%, mean score ± sd 3.1 ± 2.4) and by SPARCC in 236/389 (61%, 4 ± 3.4). Achilles enthesitis was most frequent, by both MASES (unilateral/bilateral 28%/9%) and SPARCC (48%/18%). MASES/SPARCC baseline and follow-up scores for TNFi-1 were available for 100/105 patients. Of these, 63 patients (63%) (MASES) and 46 (43.8%) (SPARCC) achieved resolution of enthesitis. The site-specific enthesitis resolution was overall lower at SPARCC sites (peripheral; 63–80%) than at MASES sites (mainly axial; 82–100%) following TNFi-1. Disease activity and PROs were worse in patients with versus without enthesitis. Conclusion Entheseal assessments are only registered in a minority of patients with PsA in routine care. When assessed, enthesitis was common, and a substantial proportion demonstrated resolution following treatment with TNFi-1.

Abstract PO3-02-02: A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study

Abstract TIPS SABCS 2023 A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study Background: Clinical trials have been an invaluable tool in providing improvements in the discovery, treatment, and quality of life for various diseases and disorders including breast cancer, which impacts millions of people each year. The MammaPrint 70-gene assay along with BluePrint 80-gene subtype analysis are tools to provide such improvements in treatment planning. Historically, patient trial populations have not been racially diverse. Current efforts are focused on improving diversity and inclusion to promote efficacy and health equity across all races/ethnicities. Given recent publications supporting the ability of MammaPrint and BluePrint to identify genomic differences in outcomes of black women with breast cancer, the ongoing multi-center FLEX trial (NCT03053193) has proven to be an unparalleled source for improvement in breast cancer care. With a target of 30,000 enrolled patients, the collaborative research network within FLEX will use MammaPrint, BluePrint, full transcriptome, and clinical data to explore clinical and genomic differences in (sub)populations of interest to promote and advance precision medicine for patients with early-stage breast cancer. Methods: FLEX is the first of its kind to link clinical data with full transcriptome data. It is a prospective, observational trial that enrolls patients who are ≥ 18 years old with histologically proven stage I-III breast cancer with up to 3 positive lymph nodes. Patient eligibility for study enrollment include standard of care MammaPrint testing with or without BluePrint and consent to clinically annotated full transcriptome data collection. The study’s infrastructure facilitates the generation of hypotheses for targeted sub-studies that are important for breast cancer management. The FLEX network fosters collaboration with 99 active sites, including Canada, Greece, and Israel. All proposed substudies are vetted and approved by both internal and external research and scientific review committees. Since launching in April 2017, 13,547 patients have been enrolled including those who have been historically underrepresented in trials (Black n =1032; Latin n= 373; AAPI n =276), 43 investigator initiated sub-studies have been approved and are in progress on a varied number of approaches like MammaPrint/Blueprint clinical utilities, racial disparities, neoadjuvant treatment planning in ER+, and or HER2+ breast cancer with 31 abstracts accepted in national and international congresses. Five ongoing sub-studies within FLEX address differences in underlying biology and treatment response/management among Black, Latina, and Asian American patients with early-stage breast cancer. These studies provide a broader understanding of how differential gene expression patterns, identified with MammaPrint and BluePrint, are unique to racial/ethnic groups and can impact treatment outcomes. Overall, the FLEX study strives to use MammaPrint, BluePrint, and newly developed immune signature, ImPrint, along with full transcriptome data to improve precision medicine in early-stage breast cancer. Citation Format: JJ Alberty-Oller, Lee Riley, Laila Samiian, Sarah Thayer, Olexiy Aseyev, Karen Tedesco, Victoria Poillucci, William Audeh, Danijela Jelovac, Joyce O'Shaughnessy. A prospective, international, observational, real-world evidence database, and collaborative platform for Investigator-Initiated Studies in Early-Stage Breast Cancer tested with MammaPrint and BluePrint– the FLEX Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-02-02.

The Top 100 Cited Articles on Cervical Disc Arthroplasty: A Bibliometric Analysis.

Bibliometric analysis. Cervical disc arthroplasty (CDA) has emerged as an effective surgical intervention for degenerative cervical disc disease with potential advantages over traditional cervical fusion. This bibliometric analysis aimed to assess the current state of research on CDA by analyzing the relevant literature using bibliometric indicators. Web of Science Core Collection. A comprehensive search was conducted using the Web of Science database, for articles related to CDA published in the last 19 years. The top 100 articles were reviewed using bibliometric analysis. Publication trends, citation patterns, authorship, and collaboration networks were analyzed using VOSviewer and the Bibliometrix package in RStudio. The results revealed a significant increase in the number of publications related to CDA over the past 2 decades, with most of the articles being published in orthopedic and spine surgery journals. The most frequently cited articles were related to clinical outcomes, complications, and biomechanical studies of CDA. Co-authorship analysis identified influential authors and collaborative networks, highlighting the multidisciplinary nature of CDA research involving neurosurgeons, orthopedic surgeons, and engineers. Overall, this bibliometric analysis provides a comprehensive overview of the current state of research on CDA, highlighting the key research themes, influential authors, and collaborative networks in the field. These findings can serve as a guide for researchers, clinicians, and policymakers to identify knowledge gaps, research trends, and future directions in the field of CDA.

Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-μg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

Global research on centenarians: A historical and comprehensive bibliometric analysis from 1887 to 2023.

Centenarians are considered the most successful human biological aging model. However, the characteristics and patterns of research among centenarians have not been described or analyzed. Thus, this study aimed to disclose the historical landscape of global research on centenarians. This bibliometric study investigated historical evidence on centenarian research published in the Scopus database. The bibliometrix package in R was used to perform visual and quantitative analyses of research metrics, trends, and patterns. Of the 2061 documents included between 1887 and 2023, 84.2% (n = 1736) were published as articles with primary data. We identified international collaboration and annual growth rates of 21.4% and 3.15%, respectively. The United States published the highest number of papers on centenarians (n = 786), whereas the publications from Italy had the highest impact (h-index = 90). Based on the frequency of keywords, mortality, genetics, dementia, Alzheimer's disease, and immunosenescence are a few of the most studied topics among centenarians, with emerging research related to mitochondrial DNA and comparison of results between nonagenarians and centenarians. Italy, the United States, and China lead the global research collaboration network, collaborating most frequently with Japan and European countries. Global research on centenarians has grown over the last 20 years, primarily led by Italy, the United States, and China. Latin American and African countries have conducted little or no research on centenarians. The most widely studied topics include mortality, cognition, immunosenescence, and genetics.

Advancements and turning point of artificial intelligence in ophthalmology: A comprehensive analysis of research trends and collaborative networks.

Artificial intelligence (AI) has emerged as a transformative force with great potential in various fields, including healthcare. In recent years, AI has garnered significant attention due to its potential to revolutionise ophthalmology, leading to advancements in patient care such as disease detection, diagnosis, treatment and monitoring of disease progression. This study presents a comprehensive analysis of the research trends and collaborative networks at the intersection of AI and ophthalmology. In this study, we conducted an extensive search of the Web of Science Core Collection to identify articles related to 'artificial intelligence' in ophthalmology published from 1968 to 2023. We performed co-occurrence keywords and co-authorship network analyses using VOSviewer software to explore the relationships between keywords and country collaboration. We found a remarkable surge in articles applying AI in ophthalmology after 2017, marking a turning point in the integration of AI within the medical field. The primary application of AI shifted towards the diagnosis of ocular disease, which was particularly evident through keywords such as glaucoma, diabetic retinopathy and age-related macular degeneration. Analysis of the collaboration networks of countries revealed a global expansion of ophthalmology-related AI research. This study provides valuable insights into the evolving landscape of AI integration in ophthalmology, indicating its growing potential for enhancing disease detection, diagnosis, treatment planning and monitoring of disease progression. In order to translate AI technologies into clinical practice effectively, it is imperative to comprehend the evolving research trends and advancements at the intersection of AI and ophthalmology.

Current progress in international pediatric emergency medicine.

Over the past four decades, pediatric emergency Medicine (PEM) has witnessed significant global development, with a notable increase in training programs and official recognition by regulatory bodies. However, disparities persist in the recognition of PEM as an independent subspecialty, availability of training programs on a global scale, academic recognition, and the ability to provide high-quality care to children worldwide. There is paucity of published literature regarding development of PEM globally. This review explores the current trends and challenges in international pediatric emergency medicine. Current trends in international pediatric emergency medicine encompass the provision of training in pediatric-focused emergency and acute care, increased propagation of evidence-based guidelines specific to the care of children, the growth of collaborative research networks and interest groups within national and international societies. Simultaneously, the field continues to face challenges such as the lack of recognition, inequities in access, and a lack of dissemination of global PEM initiatives. While recent advancements have significantly enhanced the state of international pediatric emergency medicine, including pediatric specific research networks and training programs, barriers still hinder its overall quality. Many of these obstacles are not unique to pediatric emergency medicine but are directly affected by financial disparities and lack of governmental and public recognition of the essential role of pediatric emergency care.

Challenges in conducting clinical research in primary care dentistry

The integration of dentistry into primary health care is crucial for promoting patient well-being. However, clinical studies in dentistry face challenges, including issues with study design, transparency, and relevance to primary care. Clinical trials in dentistry often focus on specific issues with strict eligibility criteria, limiting the generalizability of findings. Randomized clinical trials (RCTs) face challenges in reflecting real-world conditions and using clinically relevant outcomes. The need for more pragmatic approaches and the inclusion of clinically relevant outcomes (CROs) is discussed, such as tooth loss or implant success. Solutions proposed include well-controlled observational studies, optimized data collection tools, and the integration of artificial intelligence (AI) for predictive modelling, computer-aided diagnostics and automated diagnosis. In this position paper advocates for more efficient trials with a focus on patient-centred outcomes, as well as the adoption of pragmatic study designs reflecting real-world conditions. Collaborative research networks, increased funding, enhanced data retrieval, and open science practices are also recommended. Technology, including intraoral scanners and AI, is highlighted for improving efficiency in dental research. AI is seen as a key tool for participant recruitment, predictive modelling, and outcome evaluation. However, ethical considerations and ongoing validation are emphasized to ensure the reliability and trustworthiness of AI-driven solutions in dental research. In conclusion, the efficient conduct of clinical research in primary care dentistry requires a comprehensive approach, including changes in study design, data collection, and analytical methods. The integration of AI is seen as pivotal in achieving these objectives in a meaningful and efficient way.

Women’s entrepreneurship education: a systematic review and future agenda

Purpose In this systematic review of the literature on women’s entrepreneurship education, this paper aims to examine the current state of the field. The authors analyze publication trends, identify major themes and propose an agenda for future research. Design/methodology/approach The authors review 363 articles published between 1993 and 2023, to develop a synthesized overview of women’s entrepreneurship education, complete with insights into the journals that have provided the most coverage of this topic, as well as how it has emerged over time. Findings The authors tracked the evolution of research themes and collaboration networks over a 30-year period. Results show there has been significant growth in research on women’s entrepreneurship education, as evidenced by a surge of publications on the topic and the total number of citations. Originality/value The authors categorized and analyzed six thematic clusters within the literature: entrepreneurial intention, ethical perspectives, gender-specific barriers, gender stereotypes, rural entrepreneurship and entrepreneurial self-efficacy. Building on these thematic clusters, this study discusses future research directions to advance the field.

Psychological interventions for depression in children and adolescents: A bibliometric analysis.

Depression has gradually become a common psychological disorder among children and adolescents. Depression in children and adolescents affects their physical and mental development. Psychotherapy is considered to be one of the main treatment options for depressed children and adolescents. However, our understanding of the global performance and progress of psychological interventions for depression in children and adolescents (PIDCA) research is limited. To identify collaborative research networks in this field and explore the current research status and hotspots through bibliometrics. Articles and reviews related to PIDCA from January 2010 to April 2023 were identified from the Web of Science Core Collection database. The Charticulator website, CiteSpace and VOSviewer software were used to visualize the trends in publications and citations, the collaborative research networks (countries, institutions, and authors), and the current research status and hotspots. Until April 16, 2023, 1482 publications were identified. The number of documents published each year and citations had increased rapidly in this field. The United States had the highest productivity in this field. The most prolific institution was the University of London. Pim Cuijpers was the most prolific author. In the context of research related to PIDCA, both reference co-citation analysis and keywords co-occurrence analysis identified 10 research hotspots, including third-wave cognitive behavior therapy, short-term psychoanalytic psychotherapy, cognitive behavioral analysis system of psychotherapy, family element in psychotherapy, modular treatment, mobile-health, emotion-regulation-based transdiagnostic intervention program, dementia risk in later life, predictors of the efficacy of psychological intervention, and risks of psychological intervention. This bibliometric study provides a comprehensive overview of PIDCA from 2010 to present. Psychological intervention characterized as psychological-process-focused, short, family-involved, modular, internet-based, emotion-regulation-based, and personalized may benefit more young people.

Healthcare Burden and Resource Utilization After Pediatric Acute Respiratory Distress Syndrome: A Secondary Analysis of the Collaborative Pediatric Critical Care Research Network Acute Respiratory Distress Syndrome Study.

To describe family healthcare burden and health resource utilization in pediatric survivors of acute respiratory distress syndrome (ARDS) at 3 and 9 months. Secondary analysis of a prospective multisite cohort study. Eight academic PICUs in the United States (2019-2020). Critically ill children with ARDS and follow-up survey data collected at 3 and/or 9 months after the event. None. We evaluated family healthcare burden, a measure of healthcare provided by families at home, and child health resource use including medication use and emergency department (ED) and hospital readmissions during the initial 3- and 9-month post-ARDS using proxy-report. Using multivariable logistic regression, we evaluated patient characteristics associated with family healthcare burden at 3 months. Of 109 eligible patients, 74 (68%) and 63 patients (58%) had follow-up at 3- and 9-month post-ARDS. At 3 months, 46 families (62%) reported healthcare burden including (22%) with unmet care coordination needs. At 9 months, 33 families (52%) reported healthcare burden including 10 families (16%) with unmet care coordination needs. At month 3, 61 patients (82%) required prescription medications, 13 patients (18%) had ED visits and 16 patients (22%) required hospital readmission. At month 9, 41 patients (65%) required prescription medications, 19 patients (30%) had ED visits, and 16 (25%) required hospital readmission were reported. Medication use was associated with family healthcare burden at both 3 and 9 months. In a multivariable analysis, preillness functional status and chronic conditions were associated with healthcare burden at month 3 but illness characteristics were not. Pediatric ARDS survivors report high rates of healthcare burden and health resource utilization at 3- and 9-month post-ARDS. Future studies should assess the impact of improved care coordination to simplify care (e.g., medication management) and improve family burden.

Sex Differences in the Effectiveness of First-Line Tumor Necrosis Factor Inhibitors in Psoriatic Arthritis: Results From the European Spondyloarthritis Research Collaboration Network.

Women with psoriatic arthritis (PsA) may have reduced tumor necrosis factor inhibitor (TNFi) effectiveness compared to men. We examined sex differences in treatment response and retention rates during 24 months of follow-up among patients with PsA initiating their first TNFi. Data from patients with PsA across 13 European Spondyloarthritis Research Collaboration Network registries starting their first TNFi were pooled. Logistic regression was used to analyze the association between sex and treatment response using low disease activity (LDA) according to the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP) (<3.2) at six months as the primary outcome. Analyses were adjusted for age, country, conventional synthetic disease-modifying antirheumatic drug treatment, and TNFi start year. Retention rates were explored using the Kaplan-Meier estimator. We analyzed the treatment response of 7,679 patients with PsA (50% women) with available data on LDA at six months. At baseline, women and men had similar characteristics, including mean DAS28-CRP (women vs men, 4.4 [SD 1.2] vs 4.2 [SD 1.2]), though patient-reported outcome measures were worse in women. At six months, 64% of women and 78% of men had LDA (relative risk [RR] 0.82; 95% confidence interval [CI] 0.80-0.84). This difference was similar after adjustment (RR 0.83; 95% CI 0.81-0.85). TNFi retention rates were evaluated in 17,842 patients with PsA. Women had significantly lower retention rates than men at all time points (women 79%, 64%, and 50% vs men 88%, 77%, and 64% at 6, 12, and 24 months, respectively). Despite comparable disease characteristics at baseline, women with PsA have reduced treatment response and retention rates to their first TNFi, highlighting the need to consider sex differences in PsA research and management.

Evaluating research collaboration networks among venous thromboembolism researchers before and during the COVID-19 pandemic

Evaluating research collaboration networks among venous thromboembolism researchers before and during the COVID-19 pandemic

What Is the Role of Public History and Environmental Oral History in Supporting Conservation through Agroecology?

Indigenous peoples and local communities are key actors in the preservation of important biodiversity resources around the world. However, the ever-encroaching agricultural frontier and expansion of conventional agricultural practices threaten these communities, their autonomy over the land, and the traditional knowledge and practices associated with biodiverse ecosystems. Agroecology emerges as an important solution to support the continuation of agrobiodiversity, food security, and environmental conservation, but top-down solutions often do not resonate with the lived realities of traditional, Indigenous, and small-scale farming communities. This paper examines a collaborative research and narrative network developed over the past several years around traditional erva-mate agroforestry production in Southern Paraná, Brazil. It offers an example of how oral environmental history and public history can support conservation practices through agroecology. The key outcomes of this interdisciplinary, multi-dimensional research and engagement were the development of a candidacy for the system to be recognized as a Globally Important Agricultural Heritage System (GIAHS) from the Food and Agricultural Organization of the United Nations (FAO) and the implementation of a Dynamic Conservation Action Plan to address the threats and challenges farmers and communities are facing. The discussion explores two concepts that were integral to these processes, the creation of narrative networks and a focus on plurivocity. Both approaches ensured that the actions, knowledge, and narratives developed through the GIAHS candidacy were not imposed but agreed upon and generative through narrative and dialogue, remaining true to the realities and lived experiences of community members.

Adapting an Organizational Culture to Stay Abreast of Technological Changes in Indonesia’s Government Scientific Sector

This research navigates the disruptions the government science sector faces in an era of rapid technological change, examining the interplay of government science funding, information technology integration, and research collaboration networks. The study employs a cross-sectional design, exploring the impact of government scientific communication policies and access to advanced research technologies as independent variables, mediated by a researcher's digital literacy and skills, on the dependent variable of innovation resilience in government science. Additionally, the moderating role of government scientific infrastructure and capabilities is investigated. A comprehensive survey was administered to participants within the government science sector in Indonesia, encompassing diverse demographics and scientific disciplines. Results reveal a significant positive association between transparent government communication policies and innovation resilience, highlighting the pivotal role of effective communication in fostering adaptability. Furthermore, the study underscores the importance of government initiatives in building digital literacy and skills among researchers. The positive impact of communication policies on digital capabilities emphasizes the need for proactive strategies to enhance workforce proficiency in a technologically dynamic environment. The conceptual framework, validated through empirical findings, introduces the central construct of innovation resilience in government science, emphasizing adaptability to disruptive changes and consistent innovation.

Research hot spots and trends of keratoconus in China: a bibliometric analysis

Objective: To review the studies related to keratoconus in China, investigate research hotspots and development trends in this field, and provide reference for future research. Methods: This is a bibliometrics study. The relevant literature written in Chinese was retrieved from the WanFang DATA and the China National Knowledge Infrastructure, English articles were collected from the Web of Science Core Collection database. Searched for journal articles related to keratoconus VOSviewer software, CiteSpace, and Bibliometrix in the R language were employed to create the knowledge map. The analysis encompassed the distribution of published journals, research collaboration networks of countries/regions, institutions, and authors. Additionally, core authors, high-frequency keyword co-occurrence, keyword topic maps, and keyword emergence time ranking were examined. Results: The study ultimately included 1 100 Chinese articles and 668 English articles. Chinese literature and English literature began to increase in 1997 and 2009, respectively, indicating that the field is currently in a developmental stage. The publications involved 244 Chinese journals and 150 English journals, predominantly in the field of ophthalmology. The United States collaborated the most with China, contributing to 123 articles, followed by other countries such as the United Kingdom and Switzerland. Chinese literature and English literature involved 552 and 883 institutions, respectively. The institution with the highest number of Chinese literature publications was the Eye Institute of Shandong First Medical University (63 papers), while Wenzhou Medical University had the highest number of English literature publications (91 papers). Chinese literature involved 2 435 authors, and English literature involved 2 073 authors. The largest collaboration cluster in Chinese literature was formed by the teams of Xie Lixin and Shi Weiyun, while the Gao Hua team formed the largest cluster in English literature. However, collaboration between authors was primarily limited to within each team. A total of 622 and 1 611 keywords were extracted from Chinese and English literature, respectively. The node centrality of the four Chinese keywords, "keratoconus", "cornea", "corneal transplantation" and "myopia" as well as the three English keywords, "keratoconus", "collagen cross-linking" and "penetrating keratoplasty" was greater than 0.1. "Collagen", "riboflavin", "corneal transplantation" and "ultraviolet A" were identified as common core hotspots and important research topics in Chinese and English literature on keratoconus. Keyword emergence analysis indicated that the keywords with the highest intensity of emergence in Chinese and English literature were "myopia" (13.54) and "penetrating keratoplasty" (9.99), respectively. The longest emergence time was observed for "contact lenses" (1995-2006) and "penetrating keratoplasty" (2003-2014). Conclusions: At present, research on keratoconus in China is on the rise, with research hotspots including pathogenesis, various new surgical methods, and improvement in quality of life. The future research trend mainly focuses on early diagnosis and screening methods, artificial intelligence, biomechanical examination, subclinical keratoconus, and small incision lenticule extraction.

Nip risks in the bud: research data ethics governance framework and collaborative network from the perspective of UK policy

PurposeThis research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.Design/methodology/approachThis study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.FindingsResults indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.Research limitations/implicationsThis research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.Practical implicationsA research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.Originality/valueThis study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

Analisis Jaringan Kolaborasi Penelitian tentang Teknologi Blockchain dalam Keuangan dengan Pendekatan Bibliometrik

This research applies bibliometric analysis to explore and identify research trends as well as research collaboration networks related to the application of blockchain technology in the financial sector. Leveraging major scientific research databases, such as PubMed, IEEE Xplore, and ScienceDirect, we collected 980 research articles published between 2014 and 2024. Through literature clustering analysis, we grouped articles into 11 clusters, covering aspects of blockchain adoption in banking, the advantages of blockchain technology in international trade, transparency issues, financial risks, and current topics such as auditing and supply chain finance. Research trend analysis illustrates the evolution of research topics over time, highlighting the increased focus on specific aspects in recent years. The most impactful articles and potential topics for future research provide direction for researchers and practitioners in this field. Analysis of author collaboration networks identifies close relationships between authors, creating collaboration opportunities that can increase the richness of multidisciplinary research in the future.