Scientific Research Trends Research Articles

A Revision of a Translation Generated by Artificial Intelligence

This study focuses on the English version of an ethnographic text translated by ChatGPT, a new technology that utilises Artificial Intelligence (AI). The purpose of the study is to evaluate the syntactic, semantic, and pragmatic aspects of the translation to assess the strengths and weaknesses of this translation technology presented as a formidable tool that is poised to replace translators and render them unemployed. The method used is qualitative. It interprets the text in the Source Language (SL) and evaluates the translation against criteria of fidelity to the meaning of the SL text, cohesion of the discourse in the Target Language, and respect for the cultural context. The data, manually extracted from the translated text, consists of errors and mistakes found in the translation. The data analysis is conducted following Andrew Chesterman's theory on the three aforementioned translation strategies. The results of the study reveal that contrary to the current propaganda, ChatGPT primarily engages in literal translation. It does not engage in oblique translation. Indeed, errors and mistakes of syntactic, semantic, and pragmatic nature are abundant. Procedures such as transposition, modulation, foreignization, domestication, adaptation, transediting, etc., are almost unknown to it. At the current stage, ChatGPT is a tool that contains a vast number of words and can effectively assist translators in their work. It is too early to envision a scenario where this technology would replace experienced translators. Current scientific research trends should incorporate ChatGPT.

Trends in scientific research on coastal lagoon ecosystem services: A bibliometric analysis

Description of the subject. Coastal lagoons, vital for human wellbeing, are highly threatened ecosystems. Their ecosystem services (ES) have recently gained scientific and policy attention.Objective. This study aims to identify global trends in scientific research on coastal lagoon ecosystem services (CLES) over time.Method. Publications from 1999 to 2022 were aggregated from the Scopus database. A bibliometric analysis of 304 documents was conducted using the Bibliometrix package in R Studio.Results. Analysis revealed an increasing trend in both publications and citations related to CLES from 1999 to 2022. Schernewski G. and Lillebø A. were the most published authors, while Pérez-Ruzafa A. and Newton A. were the most cited. "Estuarine, Coastal and Shelf Science" was a key journal, with Newton et al. (2014) as the most cited document. Europe was the most productive region, and the USA led in CLES publications. Keywords like ecosystem services, coastal lagoons, and climate change were prominent. Thematic evolution showed coastal lagoons as a central theme across all periods.Conclusion. Future CLES research should focus on the impacts of land use and cover changes, local community perceptions, and participatory mapping of ecosystem services. Description du sujet. Les lagunes côtières, écosystèmes parmi les plus productifs, fournissent des biens et services essentiels au bien-être humain, mais sont menacées. Les services écosystémiques (SE) des lagunes côtières ont récemment attiré une attention accrue dans la recherche scientifique et la politique environnementale.Objectif. Cette étude vise à identifier les tendances mondiales dans la recherche sur les services écosystémiques des lagunes côtières (SELC) au fil du temps.Méthodes. Les publications de 1999 à 2022 ont été collectées via la base de données Scopus. Une analyse bibliométrique de 304 documents a été effectuée avec le package Bibliometrix dans R Studio.Résultats. L'analyse des tendances temporelles révèle une augmentation des publications et des citations sur les SELC. Schernewski G. et Lillebø A. sont les auteurs les plus publiés, tandis que Pérez-Ruzafa A. et Newton A. sont les plus cités. "Estuarine, Coastal and Shelf Science" est un journal clé, et Newton et al. (2014) est le document le plus cité. L'Europe est la région la plus productive, et les États-Unis sont le pays leader en publications. Les mots-clés fréquents incluent services écosystémiques, lagunes côtières, et changement climatique. Les lagunes côtières sont le thème dominant.Conclusion : Les recherches futures devraient explorer les impacts de l’utilisation des sols, la perception des communautés locales et la cartographie participative des services écosystémiques.

Research-Oriented Hospitals in China: A Bibliometric and Visualization Analysis Based CiteSpace.

Research-oriented hospitals represent the primary direction for the future development of large-scale, high-level hospitals in China. Research-oriented hospitals, increasingly highlighted in domestic policies, lacks a comprehensive analysis of existing research outcomes. Bibliometric evaluates scientific research endeavors and trends in disciplines by statistically analyzing literature data. Citespace is a widely used bibliometric software that helps researchers visualize research hotspots and trends in a specific field by measuring and modeling literature data from that area. This study employs CiteSpace software to conduct a bibliometric analysis and visualization analysis of the literature in the field of research-oriented hospitals, spanning publications from 2003 to 2023 and sourced from databases including the China National Knowledge Infrastructure (CNKI), Wanfang, and Weipu (VIP). Findings indicate rapid publication growth from 2010 to 2016, followed by fluctuations characterized by alternating declines and increases. In terms of the distribution of authors and institutions, the study observes a relatively modest level of collaboration among highly productive researchers and research institutions, suggesting room for enhanced interdisciplinary and institutional partnerships. Moreover, research hotspots in the field of research-oriented hospitals can be categorized into hospital development strategy, hospital management, and technological innovation. Considering the limitations of current research and the evolution of social needs, this study suggests that future research should focus more on clarifying the essence of research-oriented hospitals, developing targeted development strategies, and addressing the numerous obstacles faced during the hospital innovation process. In conclusion, this bibliometric analysis provides a snapshot of the current research status and trend. The insights gained from this research not only aim to inform future studies but also to inspire relevant stakeholders such as policy makers, hospital managers, and scholars to strengthen practical actions, enhance the construction and operation of research-oriented hospitals, thereby improving healthcare outcomes for populations.

Near-infrared photoimmunotherapy in cancer treatment: a bibliometric and visual analysis.

Near-infrared photoimmunotherapy (NIR-PIT) is an emerging cancer treatment technology that combines the advantages of optical technology and immunotherapy to provide a highly effective, precise, and low side-effect treatment approach. The aim of this study is to visualize the scientific results and research trends of NIR-PIT based on bibliometric analysis methods. The Web of Science Core Collection (WoSCC) database was searched in August 2024 for relevant publications in the field of NIR-PIT. Data were analyzed using mainly CiteSpace and R software for bibliometric and visual analysis of the country/region, authors, journals, references and keywords of the publications in the field. A total of 245 publications were retrieved, including articles (n = 173, 70.61%) and reviews (n = 72, 29.39%). The annual and cumulative number of publications increased every year. The highest number of publications was from the United States (149, 60.82%), followed by Japan (70, 28.57%) and China (33, 13.47%). The research institution with the highest number of publications was National Institutes of Health (NIH)-USA (114, 46.53%). Kobayashi H (109) was involved in the highest number of publications, Mitsunaga M (211) was the most frequently cited in total. CANCERS (17) was the most frequently published journal, and NAT MED (220) was the most frequently co-cited journal. The top 10 keywords include near-infrared photoimmunotherapy (166), photodynamic therapy (61), monoclonal antibody (58), in vivo (50), cancer (46), expression (31), breast cancer (27), enhanced permeability (24), antibody (23), growth factor receptor (16). Cluster analysis based on the co-occurrence of keywords resulted in 13 clusters, which identified the current research hotspots and future trends of NIR-PIT in cancer treatment. This study systematically investigated the research hotspots and development trends of NIR-PIT in cancer treatment through bibliometric and visual analysis. As an emerging strategy, the research on the application of NIR-PIT in cancer treatment has significantly increased in recent years, mainly focusing on the targeting, immune activation mechanism, and treatment efficacy in solid tumors has received extensive attention. Future studies may focus on improving the efficacy and safety of NIR-PIT in cancer treatment, as well as developing novel photosensitizers and combination therapeutic regimens, and exploring the efficacy of its application in a wide range of solid tumors, which will provide an important reference and guidance for the application of NIR-PIT in clinical translation.

Innovation processes: from linear models to artificial intelligence

Abstract This study aims to map scientific publications, intellectual structure and research trends in the development of innovation process models and to characterise and compare them. Specifically, to identify the innovation process models and their characteristics, comparative analysis of the models, and predict the direction of development. A hybrid method was used, which involved many years of in-depth literature monitoring and comparative analysis based on a set of parameters developed by the authors. The results made it possible to identify and classify 15 various theoretical models of the innovation process (from M1 — linear to M15 with the AI contribution) development through categorisation according to five main features: C1 — complexity, C2 — openness, C3 — the role of technology, C4 — the participation of the market/users, and C5 — the form of presentation. This study identifies, explores, analyses and summarises the main ideas of innovation processes by identifying their models and characterising those specifics that can ensure international standards of excellence. The study provides an objective view of the existing innovation process models and the relevant studies that can guide managers in their decision-making innovation processes. This study is a first attempt at unveiling the evolution of knowledge in the field of existing innovation processes and their characteristics and comparative analysis. The presented models of innovation processes should constitute an indication for practitioners who can choose a model to be used in the economic practice of their organisation.

Research hotspots and trend of glioblastoma immunotherapy: a bibliometric and visual analysis.

Glioblastoma (GBM) is one of the common malignant tumors of the central nervous system (CNS), characterized by rapid proliferation, heterogeneity, aggressiveness, proneness to recurrence after surgery, and poor prognosis. There is increasing evidence that tumorigenesis is inextricably linked to immune escape, and immunotherapy is undoubtedly an important complement to clinical treatment options for GBM, and will be a focus and hot topic in GBM treatment research. The purpose of this study was to visualize and analyze the scientific results and research trends of immunotherapy for GBM. Publications concerning immunotherapy for GBM were retrieved from the Web of Science Core Collection (WOScc) database. Bibliometric and visual analysis was performed mainly using CiteSpace and R software, and the Online Analysis Platform of Literature Metrology (https://bibliometric.com/app) for countries/regions, authors, journals, references and keywords related to publications in the field. Among totally 3491 publications retrieved in this field, 1613 publications were finally obtained according to the screening criteria, including 1007 articles (62.43%) and 606 reviews (37.57%). The number of publications increased year by year, with an average growth rate (AGR) of 17.41%. Such a number was the largest in the USA (717, 44.45%), followed by China (283, 17.55%), and the USA showed the strongest international collaboration. Among the research institutions, Duke Univ (94, 5.83%) was the largest publisher in the field, followed by Harvard Med Sch (70, 4.34%). In addition, the most prolific authors in this field were OHN H SAMPSON (51) and MICHAEL LIM (43), and the degree of collaboration (DC) between authors was 98.26%. Among the co-cited authors, STUPP R (805) was the most cited author, followed by REARDON DA (448). The journal with the most published publications was FRONTIERS IN IMMUNOLOGY (75), and the most cited journal in terms of co-citation was CLIN CANCER RES (1322), followed by CANCER RES (1230). The high-frequency keyword included glioblastoma (672) and immunotherapy (377). Cluster analysis was performed on the basis of keyword co-occurrence analysis, yielding 17 clusters, based on which the current research status and future trends in the field of immunotherapy for GBM were identified. Immunotherapy is currently a novel treatment strategy for GBM that has attracted much attention. In the future, it is necessary to strengthen cooperation and exchanges between countries and institutions towards relevant research to promote the development of this field. Immunotherapy is expected to be an important part of the future treatment strategy for GBM, and it has already become a hot spot of current research and will be the key focus of future research.

Methods of wind energy harnessing: A state-of-the-art and bibliometric analysis

Wind energy is one of the most promising alternatives for obtaining a sustainable electricity generation model with low greenhouse gas emissions. The maturity of this technology, coupled with its low investment costs and good performance, makes it highly interesting for countries to develop projects within this field. However, its high operation intermittency caused by the natural behavior of wind requires preliminary research on the technical conditions (Installation, Capacity, Environmental, Legal, Administrative, Logistics) of the geographical area wherein the wind energy project is planned. This paper provides an overview of the state-of-the-art research studies on the potential of wind energy within a territory. This review describes current methodological alternatives for assessing wind energy generation projects and potential energy studies in different geographical areas globally. Therefore, a bibliometric analysis is included, examining the scientific research trends in the field of wind energy in addition to the different technologies and innovations that have contributed to the viability of a greater wind energy generation project. Finally, the study discusses the technical restriction criteria faced by any such project. This paper also seeks to become a point of reference for future reviews and decision-making in wind projects.

UNTRM On the Global Scene: A Bibliometric Analysis of Its Scientific Production Indexed in Scopus

The purpose of this study is to conduct a comprehensive bibliometric analysis of the publications of authors affiliated with the Universidad Nacional Toribio Rodríguez de Mendoza (UNTRM) indexed in Scopus, in order to understand the scientific approach and research trends of this Amazonian institution. The methodology employed follows a qualitative, descriptive, non-experimental and longitudinal bibliometric approach, using the Scopus database for its broad academic coverage. A total of 455 documents related to the UNTRM were analyzed, including articles, contributions to conferences, reviews and other publications, without temporal restrictions. Data were downloaded in CSV format and processed using spreadsheets, open source software such as VOSviewer and bibliometrix R with Biblioshiny. The results reveal a significant growth in the number of UNTRM publications, with presence in high impact international journals and regional specialized sources. Prolific authors, prominent areas of knowledge such as Agricultural, Biological, Social, Environmental and Medical Sciences were identified, as well as a strong network of inter-institutional collaborations. The trend analysis showed a thematic diversity aligned with the institutional mission, encompassing biodiversity, environmental management, medicine, genetics and education, among others. In conclusion, this bibliometric study reveals a promising outlook for research at UNTRM, with remarkable growth, international presence, strong collaborations and thematic diversity relevant to the Amazon region.

Contemporary trends in scientific research and their influence on the categorical apparatus of jurisprudence

Contemporary trends in scientific research and their influence on the categorical apparatus of jurisprudence

Crime Rate Prediction using Python

It has never been easy to invest in a set of assets, the abnormality of the financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consists of making computers perform tasks that normally require human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Machine learning Model. The main objective of this paper is to see in which precision a Machine learning algorithm can predict. Predicting crime prediction rate is a complex task that traditionally involves extensive human-computer interaction.. The network is trained and evaluated for accuracy with various sizes of data, and the results are tabulated. This project is to predict crime to make more acquainted and precise crime in the area

Emerging trends in research on perineal trauma management: A bibliometric analysis of articles published since 1985

BackgroundThe purpose of this bibliometric analysis is to explore global trends in scientific research involving spontaneous perineal tears sustained during childbirth. This research is critical as a significant number of women have vaginal lacerations after birth resulting in complications such as pain and pelvic floor dysfunction. MethodsThe articles used in this bibliometric analysis were collected from PubMed, Web of Science, Cochrane library and Scopus. Analysis was carried out in Python and R programming languages with some visualizations created using VOS software. Apart from traditional methods, this analysis also involved time series forecasting and assessment of rolling correlations. ResultsResults indicate authors and institutions from the United Kingdom as the most productive in the research on this subject research. National level analyses for six countries showed that productivity was positively correlated with GDP/capita, average health expenditure and negatively associated with proportion of C-sections. Recent and emerging themes include those involving pharmacological interventions for pain management. ConclusionThere is a growing global interest in the research on postnatal perineal trauma with authors from the UK playing a leading role so far. Countries with high vaginal birth rates, need to promote research in this field to minimise trauma-associated comorbidities.

Three Decades of Groundwater Drought Research: Evolution and Trends

In most parts of the world, groundwater is the main source of their water supply, particularly during periods of drought when surface water is scarce. As a result, groundwater drought is among the most worrying problems of our time. In order to shed light on the diversity of scientific productions related to this theme, this analysis was conducted on 151 publications, 76 sources, and 469 authors using version 4.3.1 of Rstudio’s Bibliometrix tool. The clusters and keyword occurrence analysis reveals a research trend towards the use of advanced technologies and a more holistic approach that takes into account the complexity of hydrological systems. The use of drought indices to characterize and monitor groundwater drought, as well as satellite products and their assimilation into Land Surface Models are among the adopted solutions. This was endorsed through a summary of the five most cited publications in this field. The results also highlighted the performance of Chinese institutions in analyzing the various aspects related to this topic, as well as a lack of international collaboration between research structures. In conclusion, this study has enabled us to present the evolution and trends in scientific research and helped to specify the main emerging themes and future areas of research related to groundwater drought.

Artificial Intelligence in Kidney Disease: A Comprehensive Study and Directions for Future Research.

Artificial intelligence (AI) has emerged as a promising tool in the field of healthcare, with an increasing number of research articles evaluating its applications in the domain of kidney disease. To comprehend the evolving landscape of AI research in kidney disease, a bibliometric analysis is essential. The purposes of this study are to systematically analyze and quantify the scientific output, research trends, and collaborative networks in the application of AI to kidney disease. This study collected AI-related articles published between 2012 and 20 November 2023 from the Web of Science. Descriptive analyses of research trends in the application of AI in kidney disease were used to determine the growth rate of publications by authors, journals, institutions, and countries. Visualization network maps of country collaborations and author-provided keyword co-occurrences were generated to show the hotspots and research trends in AI research on kidney disease. The initial search yielded 673 articles, of which 631 were included in the analyses. Our findings reveal a noteworthy exponential growth trend in the annual publications of AI applications in kidney disease. Nephrology Dialysis Transplantation emerged as the leading publisher, accounting for 4.12% (26 out of 631 papers), followed by the American Journal of Transplantation at 3.01% (19/631) and Scientific Reports at 2.69% (17/631). The primary contributors were predominantly from the United States (n = 164, 25.99%), followed by China (n = 156, 24.72%) and India (n = 62, 9.83%). In terms of institutions, Mayo Clinic led with 27 contributions (4.27%), while Harvard University (n = 19, 3.01%) and Sun Yat-Sen University (n = 16, 2.53%) secured the second and third positions, respectively. This study summarized AI research trends in the field of kidney disease through statistical analysis and network visualization. The findings show that the field of AI in kidney disease is dynamic and rapidly progressing and provides valuable information for recognizing emerging patterns, technological shifts, and interdisciplinary collaborations that contribute to the advancement of knowledge in this critical domain.

Update on the Development of Educational Research in Vietnam until 2023: A Bibliometrics Analysis using Web of Science Database

Scientific research in education is the process of investigating and exploring issues about educational management, teaching, and learning activities within educational institutions. It plays a crucial role in generating new solutions for educational activities, thereby enhancing the quality of education. This esearch aims to analyze the development trends and update new trends in scientific research in education in Vietnam from 1991 to 2023. This research utilized quantitative analysis methods through databases published in the field of educational science, collecting a dataset of 636 original articles from the Web of Science (WOS). The research results indicate that the number of publications related to educational research on WOS by Vietnamese authors was limited before 2018. However, the number in the last 5 years has increased significantly, accounting for approximately 88.68% of the total articles. This increase is a direct result of significant changes in the Vietnam national primary education in 2018 and the establishment of the Education Law in 2019. Vietnamese researchers collaborated with 10 common partner countries, with Australia being the most frequent research collaborator. The Journal for Education Teacher and Trainers (JETT) is the journal that published the most educational scientific works by Vietnamese authors. The topics published on educational science in Vietnam are diverse, with some highly focused keywords, such as ‘higher education’, followed by ‘online education’, ‘high school education’, and 'covid-19’.

Mapping trends in hemifacial spasm research: bibliometric and visualization-based analyses of the Web of Science Core Collection.

Hemifacial spasm (HFS) is a common cranial nerve disease. In HFS research, we conducted a bibliometric analysis to examine the development and research trends. A retrieval of HFS studies published between 2011 and 2022 was performed from the Web of Science Core Collection in September 2022. Two scientometric tools were used to perform bibliometric and visualization-based analyses: VOSviewer and CiteSpace. Bibliometric analysis of 1461 studies published between 2011 and 2022 was carried out using data from 444 journals, 6021 authors, 1732 institutions, and 76 countries/regions. China, the USA, Japan, and South Korea were four key contributors to this study. Shanghai Jiaotong University was the major institution with the larger number of publications. Li Shiting was the most prolific author. Jannetta PJ was the most co-cited author. World Neurosurgery was the top prolific journal. Journal of Neurosurgery was the top co-cited journal. The top five keywords were hemifacial spasm, microvascular decompression, trigeminal neuralgia, surgery, and neurovascular compression. This study examines the research trends in global scientific research on HFS over the last decade. Researchers interested in learning more about current trends and novel research frontiers in this area can benefit from the study.

Trends in Aflatoxin M1 Global Research: A Bibliometric Analysis Study.

Fungal metabolites known as aflatoxin M1 (AFM1) are linked to contaminated milk and milk products. Consuming food contaminated with AFM1 poses major health risks and may even be fatal. The retrieved publications were categorized in this bibliometric study using the Web of Science (WoS) database Jan 1, 1970 to Nov 30, 2022 based on a variety of factors, including the time of publication of articles, citation totals, languages, research areas, countries, affiliations, funding agencies, journals, and keywords analysis to identify any hot and developing subjects. Additionally, VOSviewer software version 1.6.18 provided the bibliometric analysis of the global collaboration network and hot research themes. Overall, 679 published documents were detected. Food Control was the top-line journal in publications on AFM1 research with 540 published articles, while the USA was the best productive country in AFM1 publications as well as the major country with the maximum co-authorship collaboration. This study ensures quantitative and qualitative analyses of the top 25 journals, most cited published articles, most relevant authors and title word occurrences in published documents on AFM1 publications. Over the past two decades, there has been an enormous rise for research conducted on global AFM1. The assessment of the historical state and development trend in AFM1 scientific research can serve as a roadmap for future research and eventually, serve as a foundation for bettering management practices for territorial decisions, healthcare, and dairy industries.

TECHNICAL TRAINING OF WRESTLERS: RESEARCH REVIEW

Introduction. Sports training includes physical, technical, tactical, theoretical, psychological and integral components, each of which has its own specifics, but serves a common goal. Technical training is one of the key components of the general training of athletes, especially in wrestling, where it determines the ability to perform complex techniques with high accuracy and speed. Scientific research and constant development of technical training contribute to the improvement of approaches to training and increase the effectiveness of the training process. The aim of the study is to identify current trends in scientific research on the technical training of wrestlers. Material and methods: methods of analysis of literary sources and the Internet, analysis and synthesis of information were used. The search for scientific publications was carried out through Google Scholar, Scopus, and Web of Science, using the keywords. The main search period covered January 2020 - June 2024, publications outside this period were additionally considered. Of the more than 1,100 publications found, only a few met the research objective. Results. in the field of technical training of wrestlers can be conventionally divided into four main directions. The first direction concerns the construction of the educational and training process. The second covers competitive activity and the impact of competition rules on the technical and tactical arsenal. The third direction is dedicated to the individualization of the educational and training process, in particular technical training. The last direction is related to the modeling and forecasting of training and competitive activities of wrestlers, which has been gaining more and more attention in recent years. Conclusions. The analysis of scientific publications showed that technical training remains a relevant direction in the training of wrestlers. Technical preparation is critically important for successful competitive activity. The main features of technical training include a high specific weight of special training, especially before competitions; implementation of an individual approach and relationships with special physical training.

Artificial intelligence in healthcare

Research on the issues and problems of the introduction of artificial intelligence into various spheres of life of a modern individual, the society, and the state are in the trend of scientific research at the present stage of information technology development. Artificial intelligence (AI) is being used now more than ever before, especially in the healthcare sector. Artificial intelligence has provided a more efficient way to automate routine work and other daily tasks, as well as manage patients and medical resources. The system can perform most of the tasks previously performed by humans, making it faster and cheaper. This significant advantage has facilitated the activities of interacting parties in the healthcare sector, doctors and patients. Artificial intelligence continues to gain momentum. Currently, there are modern machine learning solutions that can act, learn, understand, and predict. This is a step forward compared to robotic assistants in surgical interventions and the binding of genetic codes previously controlled by artificial intelligence. The article demonstrates that the development of artificial intelligence in healthcare involves some risks and problems — artificial intelligence systems expose patients to the risk of injury, and patient data for use in artificial intelligence systems involve the risk of privacy invasion. The article shows the advantages and disadvantages of the introduction of artificial intelligence in the field of healthcare, and the necessary conclusions are drawn.

GPGPU Programming for Dipolar Field Calculation

Abstract Accelerating computational processes is paramount in numerical infrastructure development, particularly in applications such as the finite element method (FEM) and extensive calculations for simulating 3D processes in materials. In this work, we introduce a novel technique for computing the magnetostatic field of an ellipsoid particle, leveraging CUDA on a graphical card for parallel processing. The implementation on a GPU resulted in a remarkable 20-fold improvement in calculation speed. This achievement not only expedites research tasks, but also enables the exploration of larger and more intricate simulations, facilitating quicker model refinements and deeper insights into material behaviours under various conditions. The utilization of GPU computing aligns with the broader trend in scientific research and engineering, offering a versatile solution for diverse computational challenges beyond this specific task of magnetism. Overall, our work contributes to the ongoing effort to harness high-performance computing (HPC) technologies for accelerated and more efficient simulations in materials science and related fields.

Studies on Pain Associated with Anxiety or Depression in the Last 10 Years: A Bibliometric Analysis.

The prevalence of pain comorbid and anxiety/depression in clinical observations has been high, and the number of related publications has increased in recent years. Nevertheless, few studies have used bibliometric methods to analyze the scientific research on comorbid pain and depression/anxiety. The aim of this study was to systematically examine the trends in global scientific research on comorbid pain and depression/anxiety from 2012 to 2022. Papers published between 2012 and 2022 were identified in the Web of Science database. Publications that examined comorbid pain and depression/anxiety were included. The language was limited to English. CiteSpace, Excel and VOSviewer were used to analyze the volume of publications, countries, institutions, authors, cocited authors, and keywords. A total of 30,290 papers met the inclusion criteria of the study. Using CiteSpace, VOSviewer and Excel, the results showed that the United States (10,614 publications), Harvard University (1195 publications), and Jensen, Mark P. (77 publications) were the most productive country, institution, and author, respectively. The hotspots and frontiers were "relationship between depression and pain", "gender differences in pain and depression/anxiety domains", "study of specific pain types with depression/anxiety", "treatment of pain combined with anxiety/depression", and "effects of COVID-19 on patients with pain combined with depression/anxiety". These findings indicate a growing interest in the field of comorbid pain and depression/anxiety. The research has been broad and deep, but there is still much room for growth. Furthermore, there is a need for more mature global collaborative networks as well as more high-quality research results in the future.