Mapping publication trends and identifying hot spots of research on Internet health information seeking behavior: a quantitative and co-word biclustering analysis

Mapping themes, trends, and knowledge structure of Behcet syndrome: a bibliometric analysis from 2010 to 2021

This study employed bibliometric analysis to examine the current literature on Behcet Syndrome, an autoimmune disorder with complex pathophysiology and inadequate therapeutic options. The researchers collected 3,462 publications related to Behcet Syndrome from 2010 to 2021 via PubMed and conducted co-word and social network analyses to identify research hotspots and potential future directions. The co-word analysis produced a bibliographic data matrix, which revealed 72 high-frequency medical topic title (MeSH) terms. Using repeated dichotomy in the gCLUTO software, the researchers created a visualization matrix that classified the hot topics into six categories over the 12-year study period. The first quadrant contained six mature and well-developed research topics, including biological therapy, immunosuppressive agents, clinical manifestations, complications of Behcet Syndrome, Behcet Syndrome diagnosis, and aneurysm etiology and therapy. The third quadrant comprised four research topics with potential for growth, including Behcet Syndrome genetics and polymorphism, immunosuppressive agents, biological therapy and heart diseases, and thrombosis etiology. The fourth quadrant encompassed the pathophysiology of and quality of life in Behcet Syndrome as well as psychology. In the social network analysis, the researchers identified potential hotspots based on subject keywords close to the network's edge. These included genetic association studies, antibodies, genetic predisposition to disease/genetics, and monoclonal and humanized therapeutic use. Overall, this study's bibliometric analysis of Behcet Syndrome literature from the past 12 years identified unexplored subjects and developing hot spots that could lead to potential research directions for Behcet Syndrome.

Deep learning models for hepatitis E incidence prediction leveraging Baidu index

BACKGROUND

Infectious diseases are major medical and social challenges of the 21st century. Accurately predicting incidence is of great significance for public health organizations to prevent the spread of diseases. Internet search engine data, like Baidu search index, may be useful for analyzing epidemics and improving prediction.

METHODS

We collected data on hepatitis E incidence and cases in Shandong province from January 2009 to December 2022 are extracted. Baidu index is available from January 2009 to December 2022. Employing Pearson correlation analysis, we validated the relationship between the Baidu index and hepatitis E incidence. We utilized various LSTM architectures, including LSTM, stacked LSTM, attention-based LSTM, and attention-based stacked LSTM, to forecast hepatitis E incidence both with and without incorporating the Baidu index. Meanwhile, we introduce KAN to LSTM models for improving nonlinear learning capability. The performance of models are evaluated by three standard quality metrics, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE).

RESULTS

Adjusting for the Baidu index altered the correlation between hepatitis E incidence and the Baidu index from -0.1654 to 0.1733. Without Baidu index, we obtained 17.04±0.13%, 17.19±0.57%, in terms of MAPE, by LSTM and attention based stacked LSTM, respectively. With the Baidu index, we obtained 15.36±0.16%, 15.15±0.07%, in term of MAPE, by the same methods. The prediction accuracy increased by 2%. The methods with KAN can improve the performance by 0.3%. More detailed results are shown in results section of this paper.

CONCLUSIONS

Our experiments reveal a weak correlation and similar trends between the Baidu index and hepatitis E incidence. Baidu index proves to be valuable for predicting hepatitis E incidence. Furthermore, stack layers and KAN can also improve the representational ability of LSTM models.

A bibliometric analysis of studies on death anxiety in patients with cancer

Purpose: This study evaluates the evolution and focal points of research on death anxiety among cancer patients over the last three decades, utilizing bibliometric analyses.

Methods: We analyzed publications related to death anxiety among cancer patients from January 1994 to January 2024 using data from the Web of Science Core Collection. Bibliometric indicators such as the number of publications, leading countries, institutions, and research themes were examined.

Results: A total of 2,602 papers from 286 institutions across 97 countries were identified. There has been a significant increase in research interest, particularly between 2014 and 2023, with a peak in 2022. The United States and Harvard University were found to be the most prolific contributors. Major research themes include quality of life, palliative care, mental health, and cancer-specific concerns.

Conclusion: The results highlight the rapid development in the field of death anxiety research among cancer patients, with an increase in publications and emerging research themes. However, there is limited international and institutional collaboration. The study underscores the need for enhanced cooperative efforts to advance understanding and research in this area, suggesting directions for future research.

Bibliometric analysis confirms expected trends in consumer health information publications

BACKGROUND

This study provides an overview of consumer health information (CHI) scholarly communication trends.

OBJECTIVES

To explore CHI publications trends, journal citations, prolific authors, countries of origin, and distribution of CHI publications.

METHODS

A bibliometric analysis was used; 8953 records from the Web of Science (WoS) and peer-reviewed journal articles from databases, including LISA, MEDLINE, ERIC, PREMEDLINE and EMBASE were analysed.

RESULTS

Publications on CHI rapidly increased from 1980 to 2019, especially during the 1990s and 2000s. Most journals that have published CHI research are based in North America and Europe.

CONCLUSION

The increase in the CHI literature corresponds with that in Internet usage in the 2000s, and explains the availability of CHI content online. This trend is associated with the widespread adoption of personal computers (PCs) and other Internet-enabled gadgets.

Mapping the current trends of autophagy in retinal diseases: A bibliometric analysis

Background

Several scholarly publications have thoroughly examined the significant role of autophagy in the pathogenesis, progression, and treatment of retinal diseases. This research utilized bibliometric analysis to identify the primary areas of focus and emerging trends within the discipline and offer a comprehensive summary.

Methods

The research articles and reviews regarding autophagy and retinal diseases from 2009-01-01 to 2022-12-31 were from the Web of Science Core Collection (WOSCC). The software VOSviewer and CiteSpace were applied to analyze and visualize maps of countries, organizations, authors, journals, keyword networks, and citations in the field of autophagy in retinal diseases.

Results

854 qualified records (721 articles and 133 reviews) were retrieved in this research. The annual publication output of literature shows a growing trend. China is the most productive country, and the author with the most publications is Kai Kaarniranta. Journal Autophagy published the most articles in this field. Keywords analysis can effectively reflect the research hot spots and indicate that diabetic retinopathy and glaucoma have drawn more attention recently. Researchers have shifted the research emphasis on "AMPK", "angiogenesis", "mutation", and "inflammation".

Conclusions

With the bibliometric analysis approach, we presented the number of publications, countries, regions, authors, institutions, keywords, and citations, which further helps researchers understand the hot spots and trends in the field of autophagy in retinal diseases and explore the issues in the rapidly developing area.

Biclustering data analysis: a comprehensive survey

Biclustering, the simultaneous clustering of rows and columns of a data matrix, has proved its effectiveness in bioinformatics due to its capacity to produce local instead of global models, evolving from a key technique used in gene expression data analysis into one of the most used approaches for pattern discovery and identification of biological modules, used in both descriptive and predictive learning tasks. This survey presents a comprehensive overview of biclustering. It proposes an updated taxonomy for its fundamental components (bicluster, biclustering solution, biclustering algorithms, and evaluation measures) and applications. We unify scattered concepts in the literature with new definitions to accommodate the diversity of data types (such as tabular, network, and time series data) and the specificities of biological and biomedical data domains. We further propose a pipeline for biclustering data analysis and discuss practical aspects of incorporating biclustering in real-world applications. We highlight prominent application domains, particularly in bioinformatics, and identify typical biclusters to illustrate the analysis output. Moreover, we discuss important aspects to consider when choosing, applying, and evaluating a biclustering algorithm. We also relate biclustering with other data mining tasks (clustering, pattern mining, classification, triclustering, N-way clustering, and graph mining). Thus, it provides theoretical and practical guidance on biclustering data analysis, demonstrating its potential to uncover actionable insights from complex datasets.

Exploring diverse interests of collaborators in smart cities: A topic analysis using LDA and BERT

Smart cities have emerged as a promising solution to the problems associated with urbanization. However, research that holistically considers diverse stakeholders in smart cities is scarce. This study utilizes data from four types of collaborators (academia, public sector, industry, and civil society actors) to identify key topics and suggest research areas for developing smart cities. We used latent Dirichlet allocation and Bidirectional Encoder Representations from Transformers for topic extraction and analysis. The analysis reveals that sustainability and digital platform have received similar levels of interest from academia, industry, and government, whereas governance, resource, and green space are less frequently mentioned than technology-related topics. Hype cycle analysis, which considers public and media expectations, reveals that smart cities experienced rapid growth from 2015 to 2021, but the growth rate has slowed since 2022. This means that a breakthrough improvement in the current situation is required. Accordingly, we propose resolving the unbalanced distribution of topic interests among collaborators, especially in the areas of governance, environment, economy, and healthcare. We expect that our findings will help researchers, policymakers, and industry stakeholders in understanding which topics are underdeveloped in their fields and taking active measures for the future development of smart cities.

Blinded by Stress: A Patient and Physician Perspective on Central Serous Chorioretinopathy

This commentary is co-authored by a patient with central serous chorioretinopathy (CSC), which is the fourth most common exudative maculopathy. The patient, a young and profiled member of the Danish Parliament, kindly shares his experience living with stress, onset of symptoms, and the experience of being diagnosed with CSC and receiving photodynamic treatment. The experiences of the patient are put into perspective by an ophthalmologist.

Inclusion of a computerized test in ADHD diagnosis process can improve trust in the specialists' decision and elevate adherence levels

Attention deficit and hyperactivity disorder (ADHD) affects many life aspects of children and adults. Accurate identification, diagnosis and treatment of ADHD can facilitate better care. However, ADHD diagnosis and treatment methods are subject of controversy. Objective measures can elevate trust in specialist's decision and treatment adherence. In this observational study we asked whether knowing that a computerized test was included in ADHD diagnosis process results in more trust and intention to adhere with treatment recommendations. Questionnaires were administered to 459 people, 196 men, average age = 40.57 (8.90). Questions regarding expected trust and adherence, trust trait, trust in physician and health-care-institutions, and ADHD scales followed a scenario about parents referred to a neurologist for sons' ADHD diagnosis. The scenario presented to the test group (n = 185) mentioned that a computerized test was part of the diagnostic process. The control group scenario didn't mention any computerized test in the diagnostic process. Test group participants expressed more trust in the diagnosis and greater levels of intention for treatment adherence. Group differences in intention for treatment adherence were mediated by trust in decision. Inclusion of a computerized test in ADHD diagnosis process can improve trust in the specialists' decision and elevate adherence levels.

Artificial Intelligence-Based ChatGPT Responses for Patient Questions on Optic Disc Drusen

INTRODUCTION

Optic disc drusen (ODD) are acellular deposits in the optic nerve head, which are most often benign and asymptomatic. Patients may develop visual field defects and be at increased risk of ischemic co-morbidities. As ODD can be difficult to distinguish from papilledema, patients are at risk of unnecessary clinical workups. Patient information is a key aspect of ODD management. In this study, we explored the accuracy of ChatGPT responses for typical patient questions on ODD.

METHODS

Two content experts reached consensus on 20 typical patient questions. We retrieved five separate responses for each question from ChatGPT, totaling 100 responses. Each response was evaluated on a 5-point Likert-scale on accuracy by each content expert in an individual fashion.

RESULTS

The two experts were in fair/substantial agreement in the evaluation of responses (Cronbach's alpha: 0.64). Of the 100 responses, 17 were relevant and without any inaccuracies, 78 were relevant and with inaccuracies not being harmful, and five were relevant and with inaccuracies potentially harmful. The lowest accuracy scores were obtained for questions dealing with treatment and prognosis.

CONCLUSIONS

ChatGPT often provides relevant answers for patient questions on ODD, but inaccuracies become potentially harmful when questions deal with treatment and prognosis.

Knowledge Mapping of Primary Dysmenorrhea: Hotspots, Knowledge Structure, and Theme Trends

Purpose

The global incidence of primary dysmenorrhea is continuously increasing, and understanding its research trends is crucial for effective pain management and women's health. Therefore, this study aims to perform a comprehensive bibliometric analysis of primary dysmenorrhea research to identify hotspots, explore emerging trends, and provide valuable insights for future research endeavors.

Material and Methods

All of the relevant studies on primary dysmenorrhea in the Web of Science™ Core Collection database were searched for bibliometric analysis. Biclustering analysis using gCLUTO software was performed to identify research hotspots. Social network analysis with Ucinet was employed to reveal knowledge structure. Evolutionary analysis using SciMAT was utilized to predict thematic trends.

Results

A total of 903 papers were analyzed, indicating a gradual increase in research on primary dysmenorrhea in recent years, with the scope of research expanding and diversifying. We identified seven hotspots, three treatment nodes, and four thematic trends. Research hotspots focused on epidemiological studies, adolescent primary dysmenorrhea, drug and non-drug treatments. Within the realm of treatments, we have identified three treatment nodes: acupuncture, acupressure, and ibuprofen. The evolution of research has witnessed a shift from traditional epidemiological studies toward a more diverse research landscape. Adolescent primary dysmenorrhea is expected to remain a prominent research topic while dietary supplements and lifestyle are predicted to gain more attention. An emerging theme is the study of variation and polymorphism of circadian rhythm genes concerning primary dysmenorrhea.

Conclusion

This bibliometric analysis provides valuable insights into the current state of research on primary dysmenorrhea, offering a clearer understanding of the field's landscape. The identified hotspots, knowledge structure, and thematic trends can serve as valuable references for future investigations in this area. The research holds significant scientific importance and innovative value in elucidating the mechanisms of primary dysmenorrhea and finding more effective treatment approaches.

Research trends on the relationship between air pollution and cardiovascular diseases in 2013-2022 - A scientometric analysis

Exposure to air pollution is linked with an elevated risk of cardiovascular diseases (CVDs) and CVDs-related mortality. However, there is a shortage of scientometric analysis on this topic. Therefore, we propose a scientometric study to explore research hotspots and directions in this topical field over the past decade. We used the core collection of Web of Science (WoS) to obtain relevant publications and analyzed them using Excel, the Bibliometix R-package, CiteSpace, and VOSviewer. The study covered various aspects such as annual publications, highly cited papers, co-cited references, journals, authors, countries, organizations, and keywords. Research on air pollution and CVDs has remarkable increase over the past decade, with notable researchers including Kan H, Brook RD, Peters A, and Schwartz J. The 3144 articles were published by 4448 institutions in 131 countries/regions. The leading countries were the USA and China, and the most published journal was Environmental Research. Mortality, hospital admissions, oxidative stress, inflammation, long-term exposure, fine particulate matter, and PM2.5 are the top areas that merit further investigation and hold significant potential for advancing our understanding of the complex relationship between air pollution and CVDs.

A Bibliometric Analysis of Mesenchymal Stem Cell-Derived Exosomes in Acute Lung Injury/Acute Respiratory Distress Syndrome from 2013 to 2022

Background

Mesenchymal stem cell-derived exosomes (MSC-exosomes) have been found to effectively improve the systemic inflammatory response caused by acute lung injury and acute respiratory distress syndrome (ALI/ARDS), regulate systemic immune disorders, and help injured cells repair. The purpose of this study was to take a holistic view of the current status and trends of MSC-exosomes research in ALI/ARDS.

Methods

Bibliometrix, Citespace and VOSviewer software were used for bibliometric analysis of the data. We analysed the world trends, country distribution, institution contribution, most relevant journals and authors, research hotspots, and research hotspots related to Coronavirus Disease 2019 (COVID-19) based on the data collected.

Results

China possessed the largest number of publications, while the USA had the highest H-index and the number of citations. Both China and the USA had a high influence in this research field. The largest number of publications in the field of MSC-exosomes and ALI/ARDS were mainly from the University of California system. Stem Cell Research & Therapy published the largest number of papers in this scope. The author with the greatest contribution was LEE JW, and ZHU YG published an article in Stem Cell with the highest local citation score. The most frequent keyword and the latest research hotspot were "NF-κB" and "Coronavirus Disease 2019". Furthermore, our bibliometric analysis results demonstrated that MSC-exosomes intervention and treatment can effectively alleviate the inflammatory response caused by ALI/ARDS.

Conclusion

Our bibliometric study suggested the USA and China have a strong influence in this field. COVID-19-induced ALI/ARDS had become a hot topic of research.

Mapping Research Trends of Medications for Multidrug-Resistant Pulmonary Tuberculosis Based on the Co-Occurrence of Specific Semantic Types in the MeSH Tree: A Bibliometric and Visualization-Based Analysis of PubMed Literature (1966-2020)

Background

Before the COVID-19 pandemic, tuberculosis is the leading cause of death from a single infectious agent worldwide for the past 30 years. Progress in the control of tuberculosis has been undermined by the emergence of multidrug-resistant tuberculosis. The aim of the study is to reveal the trends of research on medications for multidrug-resistant pulmonary tuberculosis (MDR-PTB) through a novel method of bibliometrics that co-occurs specific semantic Medical Subject Headings (MeSH).

Methods

PubMed was used to identify the original publications related to medications for MDR-PTB. An R package for text mining of PubMed, pubMR, was adopted to extract data and construct the co-occurrence matrix-specific semantic types. Biclustering analysis of high-frequency MeSH term co-occurrence matrix was performed by gCLUTO. Scientific knowledge maps were constructed by VOSviewer to create overlay visualization and density visualization. Burst detection was performed by CiteSpace to identify the future research hotspots.

Results

Two hundred and eight substances (chemical, drug, protein) and 147 diseases related to MDR-PTB were extracted to form a specific semantic co-occurrence matrix. MeSH terms with frequency greater than or equal to six were selected to construct high-frequency co-occurrence matrix (42 × 20) of specific semantic types contains 42 substances and 20 diseases. Biclustering analysis divided the medications for MDR-PTB into five clusters and reflected the characteristics of drug composition. The overlay map indicated the average age gradients of 42 high-frequency drugs. Fifteen top keywords and 37 top terms with the strongest citation bursts were detected.

Conclusion

This study evaluated the literatures related to MDR-PTB drug therapy, providing a co-occurrence matrix model based on the specific semantic types and a new attempt for text knowledge mining. Compared with the macro knowledge structure or hot spot analysis, this method may have a wider scope of application and a more in-depth degree of analysis.

Research hotspots and trends in internal fixation of femoral neck fractures from 2010 to 2022: A 12-year bibliometric analysis

BACKGROUND

This study endeavors to scrutinize the hotspots and trends in the literature concerning the internal fixation of femoral neck fractures (INFNF) through a comprehensive bibliometric analysis. Notably, this analytical process encompasses both qualitative and quantitative components.

METHODS

The present study has utilized the Science Citation Index-Expanded from the Web of Science Core Collection to extract datasets ranging from January 1, 2010, to August 31, 2022. Quantitative analysis was carried out using sophisticated analytical tools such as the Bibliographic Item Co-Occurrence Matrix Builder, the Online Analysis Platform of Literature Metrology, and CiteSpace software. Further, the major Medical Subject Headings terms and their subheading counterparts associated with INFNF were extracted from the PubMed2XL website using the corresponding PMIDs. These Medical Subject Headings terms were employed in conducting a co-word clustering analysis. Ultimately, the Graphical CLUstering TOolkit program was utilized to execute a co-word biclustering analysis to discern the prevailing hotspots in this domain.

RESULTS

Between January 1, 2010, and August 31, 2022, a total of 463 publications were issued on INFNF. The INJURY-INTERNAL JOURNAL OF THE CARE OF THE INJURED stood out as the most extensively perused journal in this area. Notably, China emerged as the foremost contributor to publishing articles within the last 12 years, followed by the United States and Canada. McMaster University was identified as the leading institution in INFNF research, while Bhandari M emerged as the most prolific author in this field. Moreover, the study identified five notable research hotspots within the domain of INFNF.

CONCLUSIONS

This study has identified five critical areas of research in the field of INFNF. It suggests that the primary focus of future research is likely to center on advancing internal fixation methods and robot-assisted instrumentation for femoral neck fractures. As such, this study provides valuable insights into future research directions and ideas for those working in this field.

Global trends in research on extracorporeal shock wave therapy (ESWT) from 2000 to 2021

BACKGROUND

This study intended to analyze the application of extracorporeal shock wave therapy in medicine and to evaluate the quality of related literature.

METHODS

All publications were extracted from 2000 to 2021 from the Web of Science Core Collection (WoSCC). The literature characteristics were depicted by VOSviewer (version 1.6.15) and the online bibliometric website ( http://bibliometric.com/ ). The future trends and hotspots were conducted by Bibliographic Item Co-occurrence Matrix Builder (version 2.0) and gCLUTO software.

RESULTS

We analyzed 1774 articles corresponding to the criteria for ESWT publications from 2000 to 2021. Most studies were conducted within the United States and China which besides have the most cooperation. The most published research institutions are Chang Gung University, Kaohsiung Chang Gung Memorial Hospital, and Kaohsiung Medical University. Six research hotspots were identified by keyword clustering analysis: Cluster0: The effects of ESWT on muscle spasticity; Cluster1: The application of ESWT in osteoarthritis (OA); Cluster2: Therapeutic effect of ESWT on tendon diseases; Cluster3: Early application of ESWT/ESWL in urolithiasis; Cluster4: The Role of angiogenesis in ESWT and the efficiency of ESWT for penile disease; Cluster5: The Special value of radial extracorporeal shock wave therapy (rESWT).

CONCLUSIONS

A comprehensive and systematic bibliometric analysis of ESWT was conducted in our study. We identified six ESWT-related research hotspots and predicted future research trends. With the gradual increase of research on ESWT, we find that ESWT is used more and more extensively, such in musculoskeletal disease, bone delay union, neurological injury, andrology disorders, lymphedema, and so on. In addition, the mechanism is not destructive damage, as initially thought, but a restorative treatment. Furthermore, delayed union, cellulite, burn, and diabetic foot ulcers may be the future direction of scientific study.

Research Trends of the Internet of Things in Relation to Business Model Innovation: Results from Co-Word and Content Analyses

In the era of the Internet of Things, innovative business model initiatives continue to deepen, and the trend of search domains continues to expand. This paper aims to scientifically analyze research trends of the Internet of Things in relation to Business Model Innovation through bibliometric studies. The data were collected using the Clarivate Web of Science (WoS) Core Collection (SSCI and SCI indexed) from 2005 to 2022 (November). However, the publications for the research domains started in 2015. The results show that scientific publications on the Internet of Things in relation to Business Model Innovation have increased gradually since 2019. The WoS database is utilized for analyses because it contains journals and conference proceedings deemed more relevant by the academic domain and highly reputable sources for bibliometric studies. The VOS viewer, R Language, and Microsoft Excel were also used to analyze and complete the study. Bibliometric and scientometric analyses were conducted to identify publication patterns, text analysis, most important keywords (co-word, word cloud, and co-occurrence), trends for the topicality, and content clustering for the publication periods. The visualization of the research trends of the Internet of Things in relation to Business Model Innovation resulted in four co-occurrence clusters leading to some of the topic areas mentioned as follows: (1) The Internet of Things, (2) Business model innovation, (3) Technology infrastructure, and (4) Digital transformation and capabilities. The results of this study will assist academics in identifying worldwide research trends related to the Internet of Things and Business Model Innovation as well as recommending future research areas.

A bibliometric analysis of the theme trends and knowledge structures of pulmonary embolism from 2017 to 2021

Background

Pulmonary embolism (PE) is a popular area of research in the field of respiratory medicine. We performed a bibliometric analysis based on PubMed database to characterize the distribution pattern of literature and knowledge structures related to PE.

Methods

Literature pertaining to PE from January 1, 2017, to December 31, 2021, was retrieved from the PubMed database. Bibliographic information was generated using the Bibliographic Item Co-Occurrence Matrix Builder (BICOMB). The visualization matrix was established using gCLUTO software. Strategic diagram analysis was performed using GraphPad Prism 9 software. Social network analysis (SNA) was generated using Ucinet6.0 and NetDraw 2.084 software.

Results

Out of all the retrieved MeSH terms and subheadings, 52 MeSH terms/MeSH subheadings with a high frequency were found, and hot subjects were sorted into 6 clusters. The strategy diagram showed that the epidemiology, etiology, and drug therapy of PE were well advanced. In contrast, studies on diagnostic imaging, pathology, and complications of PE were still immature and offered potential research space. Social network analysis showed that marginal topics such as surgical treatment of pulmonary hypertension, prevention and control of postoperative complications, and metabolism and analysis of fibrin/fibrinogen degradation products were emerging research hotspots.

Conclusion

Objective analysis of the research developments in the field of PE can provide intuitive knowledge structure for researchers and clinicians. Analysis of the research hotspots related to PE is helpful for researchers and clinicians by highlighting future research directions.

Mapping intellectual structure and research hotspots in the field of fibroblast-associated DFUs: a bibliometric analysis

Background

Diabetic foot ulcers (DFUs) are one of the most popular and severe complications of diabetes. The persistent non-healing of DFUs may eventually contribute to severe complications such as amputation, which presents patients with significant physical and psychological challenges. Fibroblasts are critical cells in wound healing and perform essential roles in all phases of wound healing. In diabetic foot patients, the disruption of fibroblast function exacerbates the non-healing of the wound. This study aimed to summarize the hotspots and evaluate the global research trends on fibroblast-related DFUs through bibliometric analysis.

Methods

Scientific publications on the study of fibroblast-related DFUs from January 1, 2000 to April 27, 2022 were retrieved from the Web of Science Core Collection (WoSCC). Biblioshiny software was primarily performed for the visual analysis of the literature, CiteSpace software and VOSviewer software were used to validate the results.

Results

A total of 479 articles on fibroblast-related DFUs were retrieved. The most published countries, institutions, journals, and authors in this field were the USA, The Chinese University of Hong Kong, Wound Repair and Regeneration, and Seung-Kyu Han. In addition, keyword co-occurrence networks, historical direct citation networks, thematic map, and the trend topics map summarize the research hotspots and trends in this field.

Conclusion

Current studies indicated that research on fibroblast-related DFUs is attracting increasing concern and have clinical implications. The cellular and molecular mechanisms of the DFU pathophysiological process, the molecular mechanisms and therapeutic targets associated with DFUs angiogenesis, and the measures to promote DFUs wound healing are three worthy research hotspots in this field.

Exploring the health information seeking behavior of social media users under the background of COVID-19 pandemic: An empirical study based on social cognitive theory

With the outbreak of COVID-19 in late 2019, people's awareness of actively searching for health information has been growing. Coupled with the promotion of "Internet + medical and health," social media, as an important platform for health information dissemination, has become one of the important information sources for users to obtain health information. However, health information seeking behavior in public health emergencies are quite different from those in daily life. Therefore, the research question of this paper is to explore the influencing factors of health information seeking behavior of social media users in the context of COVID-19. To this end, based on the research framework of social cognition theory, this paper selects six variables to construct a structural equation modeling, including information and platform quality, experience, social support, emotional arousal, self-efficacy, and social media users' health information seeking behavior. The empirical study is carried out by collecting 219 valid questionnaires. The research results show that: (1) Information and platform quality, and use experience have a significant positive effect on emotional arousal; (2) Experience, social support, and emotional arousal have a significant positive effect on self-efficacy; (3) Emotional arousal and self-efficacy have a significant positive effect on social media users' health information seeking behavior. The research provides an important theoretical reference for social media users and operators to cope with the huge demand for health information in the post-COVID-19 era.

Bibliometric and Visual Analysis of the Current Status and Trends of Postoperative Pain in Children from 1950-2021

Background

Postoperative pain in children has been overlooked for a long time. The knowledge structure, research hotspots and trends related to postoperative pain in children are unclear and have not been systematically summarized.

Purpose

We aimed to analyze the current state of research on postoperative pain in children and to conduct in-depth mining of the knowledge structure.

Methods

The PubMed database for publications on postoperative pain in children between 1950 and 2021 was searched. Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) was performed to obtain the co-word matrix and co-occurrence matrix. The H-index method was used to extract high-frequency main Medical Subject Headings (MeSH) terms/subheadings.

Results

The high-frequency MeSH terms were analyzed by biclustering, strategic diagram and social network analyses. Totally, 4022 publications were retrieved. The analysis showed that 60 countries or regions published relevant documents, with the United States publishing the most significant number of papers. Totally, 811 journals published relevant papers, with Pediatric Anesthesia ranking first. Moreover, we extracted 43 high-frequency main MeSH terms/subheadings and clustered them into five categories: overview, aetiology and epidemiology, pharmacotherapy, opioid administration and dosing, and prevention and control of postoperative pain in children.

Conclusion

Pharmacological treatments, pain prevention and control are the focus of research and are becoming increasingly mature. Opioid stewardship and regional anesthesia is the trend and focus of future research. Our study offers a better understanding of the current status and knowledge structure of postoperative pain in children and provides a reference for improving postoperative pain management in children in the future.

Global Trends in Research on Cell-Free Nucleic Acids in Obstetrics and Gynecology during 2017–2021

Objectives. The objectives of this study were to identify global trends in research on cell-free deoxyribonucleic acid (cfDNA) from a bibliometric perspective and provide researchers with new research hotspots. Methods. In all, we extracted 5038 pieces of literature from PubMed and 527 articles from the Web of Science Core Collection (WoSCC) database related to cfDNA published from 1 January 2017 to 31 December 2021. For PubMed literature, we employed co-word, biclustering, and strategic diagram analysis to describe the trends in research on cfDNA in the said five years. Then, we used VOSviewer analysis for the WoSCC database to display the trends in research on cfDNA in obstetrics and gynecology during 2017–2021. Results. Strategy diagram analysis of 95 major Medical Subject Headings terms extracted from 5038 pieces of literature indicated that cfDNA sequence analysis for non-invasive prenatal and genetic testing and its application in the fields of neoplasm genetics and diagnosis is a newly emerging immature theme of cfDNA. VOSviewer analysis of 527 articles showed the global trends in research on cfDNA in obstetrics and gynecology, for example, in terms of most influential authors, institutions, countries, journals, and five research hotspots: (1) cfDNA application in prenatal screening and prenatal diagnosis, (2) cfDNA application in assisted reproductive technology, (3) cfDNA application in pre-eclampsia, DNA methylation, etc., (4) cfDNA application in placental dysfunction and fetal growth restriction, and (5) cfDNA application in fetal chromosomal abnormalities (fetal aneuploidy). Conclusions. Comprehensive visual analysis provides information regarding authors, organizations, countries/regions, journals, research hotspots, and emerging topics in the field of cfDNA for obstetrics and gynecology research. This comprehensive study could make it easier to find a partner for project development and build a network of knowledge on this emerging topic.

Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis

Background

Artificial intelligence (AI) is more and more widely used in cancer, which is of great help to doctors in diagnosis and treatment. This study aims to summarize the current research hotspots in the Application of Artificial Intelligence in Cancer (AAIC) and to assess the research trends in AAIC.

Methods

Scientific publications for AAIC-related research from 1 January 1998 to 1 July 2022 were obtained from the Web of Science database. The metrics analyses using bibliometrics software included publication, keyword, author, journal, institution, and country. In addition, the blustering analysis on the binary matrix was performed on hot keywords.

Results

The total number of papers in this study is 1592. The last decade of AAIC research has been divided into a slow development phase (2013-2018) and a rapid development phase (2019-2022). An international collaboration centered in the USA is dedicated to the development and application of AAIC. Li J is the most prolific writer in AAIC. Through clustering analysis and high-frequency keyword research, it has been shown that AI plays a significantly important role in the prediction, diagnosis, treatment and prognosis of cancer. Classification, diagnosis, carcinogenesis, risk, and validation are developing topics. Eight hotspot fields of AAIC were also identified.

Conclusion

AAIC can benefit cancer patients in diagnosing cancer, assessing the effectiveness of treatment, making a decision, predicting prognosis and saving costs. Future AAIC research may be dedicated to optimizing AI calculation tools, improving accuracy, and promoting AI.

Medical information seeking behavior of urban patients in Zhejiang Province, China: a cross-sectional study

Background

Health information seeking behavior (HISB) is a prevalent research topic. However, little is known about sociodemographic factors of HISB in China. This study aimed to examine the HISB of urban patients in China and identify predictors of source preference, online information seeking, and the timing of online seeking.

Methods

Based on the Health Information National Trends Survey (HINTS), this study conducted a cross-sectional survey of 1653 participants in different types of hospitals in 3 cities of different income levels within Zhejiang Province, China. Binary logistic regression analysis and multinomial logistic regression analysis were used to identify predictors of source preference, online medical information seeking, and the timing of online seeking for urban patients.

Results

The offline was the primary source of medical information for 58.61% of adult urban patients, while 78.19% had ever sought medical information online. 36.81% of online medical information seekers sought information before the medical visit, 8.65% sought information after the visit, and 54.54% sought information before and after the visit. China’s urban patients with higher education levels, higher income levels, young, active in internet use, and living in high-income cities were more likely to be active online medical information seekers (using the internet as the primary source) and online medical information seekers (having ever sought medical information online). Except for gender and age, most sociodemographic characteristics were not significantly associated with the timing of online medical information seeking.

Conclusions

Significant predictors of active online medical information seekers and online medical information seekers in China were almost the same. Regional economic development had a significant direct impact on medical information seekers. Most sociodemographic characteristics were not significantly associated with the timing of online medical information seeking. The findings of this study imply that China’s health information technology industry has Chinese characteristics.

Research trends and hotspots of breast cancer management during the COVID-19 pandemic: A bibliometric analysis

Background

The coronavirus disease 2019 (COVID-19) pandemic is disrupting routine medical care of cancer patients, including those who have cancer or are undergoing cancer screening. In this study, breast cancer management during the COVID-19 pandemic (BCMP) is reviewed, and the research trends of BCMP are evaluated by quantitative and qualitative evaluation.

Methods

In this study, published studies relating to BCMP from 1 January 2020 to 1 April 2022 were searched from the Web of Science database (WoS). Bibliometric indicators consisted of publications, research hotspots, keywords, authors, journals, institutions, nations, and h-index.

Results

A total of 182 articles investigating BCMP were searched. The United States of America and the University of Rome Tor Vergata were the nation and the institution with the most publications on BCMP. The first three periodicals with leading published BCMP studies were Breast Cancer Research and Treatment, Breast, and In Vivo. Buonomo OC was the most prolific author in this field, publishing nine articles (9/182, 4.94%). The co-keywords analysis of BCMP suggests that the top hotspots and trends in research are screening, surgery, rehabilitation, emotion, diagnosis, treatment, and vaccine management of breast cancer during the pandemic. The hotspot words were divided into six clusters, namely, screening for breast cancer patients in the pandemic, breast cancer surgery in the pandemic, recovery of breast cancer patients in the pandemic, motion effect of the outbreak on breast cancer patients, diagnosis and treatment of breast cancer patients in the pandemic, and vaccination management for breast cancer patients during a pandemic.

Conclusion

BCMP has received attention from scholars in many nations over the last 3 years. This study revealed significant contributions to BCMP research by nations, institutions, scholars, and journals. The stratified clustering study provided the current status and future trends of BCMP to help physicians with the diagnosis and treatment of breast cancer through the pandemic, and provide a reference for in-depth clinical studies on BCMP.

Digital Health Literacy: Bibliometric Analysis

Background

Digital health is growing at a rapid pace, and digital health literacy has attracted increasing attention from the academic community.

Objective

The purposes of this study are to conduct a systematic bibliometric analysis on the field of digital health literacy and to understand the research context and trends in this field.

Methods

Methods: A total of 1955 scientific publications were collected from the Web of Science core collection. Institutional co-operation, journal co-citation, theme bursting, keyword co-occurrence, author co-operation, author co-citation, literature co-citation, and references in the field of digital health literacy were analyzed using the VOSviewer and CiteSpace knowledge mapping tools.

Results

The results demonstrate that the United States has the highest number of publications and citations in this field. The University of California System was first in terms of institutional contributions. The Journal of Medical Internet Research led in the number of publications, citations, and co-citations. Research areas of highly cited articles in the field of digital health literacy mainly include the definition and scale of health literacy, health literacy and health outcomes, health literacy and the digital divide, and the influencing factors of health literacy.

Conclusions

We summarized research progress in the field of digital health literacy and reveal the context, trends, and trending topics of digital health literacy research through statistical analysis and network visualization. We found that digital health literacy has a significant potential to improve health outcomes, bridge the digital divide, and reduce health inequalities. Our work can serve as a fundamental reference and directional guide for future research in this field.

Design for Pandemic Information: Examining the Effect of Graphs on Anxiety and Social Distancing Intentions in the COVID-19

To increase public awareness and disseminate health information, the WHO and health departments worldwide have been visualizing the latest statistics on the spread of COVID-19 to increase awareness and thus reduce its spread. Within various sources, graphs are frequently used to illustrate COVID-19 datasets. Limited research has provided insights into the effect of different graphs on emotional stress and ineffective behavioral strategies from a cross-cultural perspective. The result of current research suggests a graph with a high proportion size of the colored area (e.g., stacked area graph) might increase people's anxiety and social distancing intentions; people in collectivist culture might have a high level of anxiety and social distancing intentions; the effect of different graphs on social distancing intentions is mediated by anxiety experienced. Theoretical contribution and practical implications on health communication were also discussed in this study.

Exosomes in the Field of Neuroscience: A Scientometric Study and Visualization Analysis

Exosomes have received great attention for their diagnostic, therapeutic, and prognostic roles in the field of neuroscience over the past decade. This scientometric study aimed to quantitatively and qualitatively evaluate knowledge structure, hot topics, and research trends of studies about exosomes in the field of neuroscience using visualization tools. Web of Science Core collection databases were searched for relevant publications between 2005 and 2021. The Carrot2 online system, BICOMB, gCLUTO, and Ucinet software were utilized for key word analysis, and co-citations analyses were conducted in Citespace and VOSviewer. Altogether, 21 high-frequency key words were collected from 856 included articles, and 5 clusters were identified through biclustering analyses. The strategic diagram and social network analysis further determined research hotspots and trends. Co-citation analysis results revealed a few crucial works that contributed to the development of research on exosomes in the field of neuroscience. Moreover, the important sources that had contributed to the development of this field were identified. Our findings suggested that Alzheimer's disease-related research remained a hot topic in this field till now, and recent researchers had extended their scopes to more cognitive impairments. Importantly, researches related to exosomes in multiple sclerosis and Parkinson's disease were promising. While exosomes in acute central nervous system injury had not been sufficiently investigated, with continuous improvement in exosome-based delivery technology, this subject might make a breakthrough in terms of therapeutic innovations in the immediate future.

Research hotspot and trend of microneedles in biomedical field: A bibliometric analysis from 2011 to 2020

BACKGROUND

Microneedles composed of arrays of micro-sized needles assembled on a patch, has attracted increasing interest in transdermal drug delivery due to its ease of use and lack of painful responses. Here, a bibliometric analysis was conducted to determine a hotspot and trend of microneedles in the biomedical field.

METHODS

All relevant articles about microneedles between 2011 and 2020 were obtained from the databases of Web of Science (WOS) and PubMed of the National Center for Biotechnology Information (NCBI). A series of software such as VOSviwewer, the online bibliometric analysis website, CiteSpace, BICOMB and gCLUTO were used to process the data and get visual images. Processed data and visualized images were conducted to predict the trend of this research field.

RESULTS

The number of articles published over the last decade had increased rapidly (37 in 2011, 165 in 2020), the Journal of Controlled Release was the most productive journal in microneedle studies. The United States was the most productive country, while the Queens Univ Belfast topped the other institutions. Ryan F Donnelly was the most productive author in the field, while the two most cited articles were published by Gu Zhen group. More importantly, the research trend of microneedles had ranged from physicochemical properties and pharmacokinetics to insulin transdermal injection and vaccine development over the past decade. The four hot spots in microneedle studies, including skin rejuvenation, vaccines, fabrication technology and insulin delivery, were identified. Microneedle vaccination shows promising application prospects, and polymers are considered as the most promising materials for microneedles manufacturing.

CONCLUSIONS

This study will help researchers understand the hot spots and trends of microneedles in the biomedical field accurately and quickly. Moreover, the exploitation of novel polymeric microneedles will be a solid direction for subsequent research and development of transdermal drug delivery.

Knowledge Domain and Hotspots Predict Concerning Electroactive Biomaterials Applied in Tissue Engineering: A Bibliometric and Visualized Analysis From 2011 to 2021

Objective: Electroactive biomaterials used in tissue engineering have been extensively studied. Electroactive biomaterials have unique potential advantages in cell culture and tissue regeneration, which have attracted the attention of medical researchers worldwide. Therefore, it is important to understand the global scientific output regarding this topic. An analysis of publications on electroactive biomaterials used in tissue engineering over the past decade was performed, and the results were summarised to track the current hotspots and highlight future directions.

Methods: Globally relevant publications on electroactive biomaterials used in tissue engineering between 2011 and 2021 were extracted from the Web of Science database. The VOSviewer software and CiteSpace were employed to visualise and predict trends in research on the topic.

Results: A total of 3,374 publications were screened. China contributed the largest number of publications (995) and citations (1581.95, actual value ×0.05). The United States achieved the highest H-index (440 actual values ×0.05). The journal Materials Science & Engineering C-materials for Biological Applications (IF = 7.328) published the most studies on this topic (150). The Chinese Academy of Science had the largest number of publications (107) among all institutions. The publication titled Nanotechnological strategies for engineering complex tissues by Dir, T of the United States had the highest citation frequency (985 times). Regarding the function of electroactive materials, the keyword “sensors” emerged in recent years. Regarding the characterisation of electroactive materials, the keyword “water contact angle” appeared lately. Regarding electroactive materials in nerve and cardiac tissue engineering, the keywords “silk fibroin and conductive hydrogel” appeared recently. Regarding the application of electroactive materials in bone tissue engineering, the keyword “angiogenesis” emerged in recent years. The current research trend indicates that although new functional materials are constantly being developed, attention should also be paid to their application and transformation in tissue engineering.

Conclusion: The number of publications on electroactive biomaterials used in tissue engineering is expected to increase in the future. Topics like sensors, water contact angle, angiogenesis, silk fibroin, and conductive hydrogels are expected to be the focuses of research in the future; attention should also be paid to the application and transformation of electroactive materials, particularly bone tissue engineering. Moreover, further development of the field requires joint efforts from all disciplines.

Twitter Research Synthesis for Health Promotion: A Bibliometric Analysis

Background:

This study enriched our understanding by systematically reviewing knowledge management twitter health (KMTH) articles extracted from Web of Science (WoS) using cartography analysis through VOSviewer–for the last 11 years.

Methods:

A total of 798 KMTH articles were found from 2009 to 2019, analyzed based on the most cooccurrence keywords of KMTH articles.

Results:

Three clusters emerged through cartography analysis; Cluster 1: Twitter as health education and health promotion platform; Cluster 2: Twitter as public health promotion platform and Cluster 3: Twitter as health sentiment platform through big data and machine learning.

Conclusion:

This study opened new avenues for all health care providers to utilize Twitter as a KM platform to promote health care. This is the first bibliometric analysis of KMTH publications according to our best knowledge.

Mapping Intellectual Structures and Research Hotspots of Triple Negative Breast Cancer: A Bibliometric Analysis

Background

Triple negative breast cancer (TNBC) is a highly heterogeneous breast cancer subtype with a poor prognosis due to its extremely aggressive nature and lack of effective treatment options. This study aims to summarize the current hotspots of TNBC research and evaluate the TNBC research trends, both qualitatively and quantitatively.

Methods

Scientific publications of TNBC-related studies from January 1, 2010 to October 17, 2020 were obtained from the Web of Science database. The BICOMB software was used to obtain the high-frequency keywords layout. The gCLUTO was used to produce a biclustering analysis on the binary matrix of word-paper. The co-occurrence and collaboration analysis between authors, countries, institutions, and keywords were performed by VOSviewer software. Keyword burst detection was performed by CiteSpace.

Results

A total of 12,429 articles related to TNBC were identified. During 2010-2020, the most productive country/region and institution in TNBC field was the USA and The University of Texas MD Anderson Cancer Center, respectively. Cancer Research, Journal of Clinical Oncology, and Annals of Oncology were the first three periodicals with maximum publications in TNBC research. Eight research hotspots of TNBC were identified by co-word analysis. In the core hotspots, research on neoadjuvant chemotherapy, paclitaxel therapy, and molecular typing of TNBC is relatively mature. Research on immunotherapy and PARP inhibitor for TNBC is not yet mature but is the current focus of this field. Burst detection of keywords showed that studies on TNBC proteins and receptors, immunotherapy, target, and tumor cell migration showed bursts in recent three years.

Conclusion

The current study revealed that TNBC studies are growing. Attention should be paid to the latest hotspots, such as immunotherapy, PARP inhibitors, target, and TNBC proteins and receptors.

Antecedents of self-protective behavior during the COVID-19 pandemic in Bangladesh

CONTEXT

Self-protective behavior (SPB) plays a significant role in controlling the spread of infection of a pandemic like coronavirus disease (COVID-19). Little research has been conducted to examine critical factors influencing SPB, especially in a developing country like Bangladesh.

AIMS

This study aimed to develop and test a theoretical model based on the extended information-motivation-behavior (IMB) skills model to investigate factors associated with SPB among Bangladeshi people.

METHODS

An online, cross-sectional survey was conducted on Bangladesh citizens (18 years and older) from June 1 and July 31, 2020. A total of 459 responses were used to assess the proposed model's overall fit and test the hypothesized relationships among the model constructs.

STATISTICAL ANALYSIS USED

The data were analyzed using partial least squares structural equation modeling to identify relationships among model variables.

RESULTS

Health information-seeking behavior, health motivation, self-efficacy, and health consciousness (HC) (P < 0.05) had a significant impact on SPB among Bangladeshi people. The results identified the consequences of various degrees of HC on SPB in the COVID-19 outbreak.

CONCLUSIONS

This study confirms the IMB model's applicability for analyzing SPB among people in developing countries like Bangladesh. The findings of this study could guide policymakers to develop and implement targeted strategies to ensure timely and transparent information for motivating people to improve SPB during the COVID-19 and in case of a future outbreak of an epidemic.

Mapping the structure of depression biomarker research: A bibliometric analysis

BACKGROUND

Depression is a common mental disorder and the diagnosis is still based on the descriptions of symptoms. Biomarkers can reveal disease characteristics for diagnosis, prognosis, and treatment. In recent years, many biomarkers relevant to the mechanisms of depression have been identified. This study uses bibliometric methods and visualization tools to analyse the literature on depression biomarkers and its hot topics, and research frontiers to provide references for future research.

METHODS

Scientific publications related to depression biomarkers published between 2009 and 2022 were obtained from the Web of Science database. The BICOMB software was used to extract high-frequency keywords and to construct binary word-document and co-word matrices. gCLUTO was used for bicluster and visual analyses of high-frequency keywords. Further graphical visualizations were generated using R, CiteSpace and VOSviewer software.

RESULTS

A total of 14,403 articles related to depression biomarkers were identified. The United States (34.81%) and China (15.68%), which together account for more than half of all publications, can be considered the research base for the field. Among institutions, the University of California, University of London, and Harvard University are among the top in terms of publication number. Three authors (Maes M, Penninx B.W.J.H., and Berk M) emerged as eminent researchers in the field. Finally, eight research hotspots for depression biomarkers were identified using reference co-citation analysis.

CONCLUSION

This study used bibliometric methods to characterize the body of literature and subject knowledge in the field of depression biomarker research. Among the core biomarkers of depression, functional magnetic resonance imaging (fMRI), cytokines, and oxidative stress are relatively well established; however, research on machine learning, metabolomics, and microRNAs holds potential for future development. We found "microRNAs" and "gut microbiota" to be the most recent burst terms in the study of depression biomarkers and the likely frontiers of future research.

Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis

Geospatial data is an indispensable data resource for research and applications in many fields. The technologies and applications related to geospatial data are constantly advancing and updating, so identifying the technologies and applications among them will help foster and fund further innovation. Through topic analysis, new research hotspots can be discovered by understanding the whole development process of a topic. At present, the main methods to determine topics are peer review and bibliometrics, however they just review relevant literature or perform simple frequency analysis. This paper proposes a new topic discovery method, which combines a word embedding method, based on a pre-trained model, Bert, and a spherical k-means clustering algorithm, and applies the similarity between literature and topics to assign literature to different topics. The proposed method was applied to 266 pieces of literature related to geospatial data over the past five years. First, according to the number of publications, the trend analysis of technologies and applications related to geospatial data in several leading countries was conducted. Then, the consistency of the proposed method and the existing method PLSA (Probabilistic Latent Semantic Analysis) was evaluated by using two similar consistency evaluation indicators (i.e., U-Mass and NMPI). The results show that the method proposed in this paper can well reveal text content, determine development trends, and produce more coherent topics, and that the overall performance of Bert-LSA is better than PLSA using NPMI and U-Mass. This method is not limited to trend analysis using the data in this paper; it can also be used for the topic analysis of other types of texts.

Emerging Trends and Thematic Evolution of Breast Cancer: Knowledge Mapping and Co-Word Analysis

BACKGROUND

One of the requirements for scientists and researchers to enter any field of science is to have a comprehensive and accurate understanding of that discipline.

OBJECTIVE

This study aims to draw a science map, provide structural analysis, explore the evolution, and determine new trends in research articles published in the field of breast cancer.

METHODS

This study comprised a descriptive survey with a scientometric approach. Data were collected from MEDLINE using a search strategy based on Medical Subject Heading (MeSH) terms. This study used science mapping, which provides a visual representation and a longitudinal evolution of possible interrelations between scientific areas, documents, or authors, thus reflecting the cognitive architecture of science mapping. For this scientometric evaluation of the topic of breast cancer research, a very long period was considered for data collection. Moreover, due to the availability of numerous publications in the database, the assessment was divided into three different periods ranging from 1988 to 2020.

RESULTS

A total of 12,577 records related to scientometric studies were extracted. The field of breast cancer research demonstrated three diagrams containing the most relevant themes for the three chronological periods evaluated. Each diagram was plotted based on the centrality and density linked to each research topic. The research output in the field was observed to revolve around 8 areas or themes: radiation injury, cardiovascular disease, fibroadenoma, antineoplastic agent, estrogen antagonistic, immunohistochemistry, soybean, and epitopes, each represented with different colors.

CONCLUSIONS

In the strategic diagrams, the themes were both well developed and important for the structuring of a research field. The first quadrant comprised motor themes of the specialty, which present strong centrality and high density (eg, corticosteroid antineoplastic age, stem cell, T-lymphocyte, protein tyrosine kinase, dietary, and phosphatidyl inositol-3-kinase). In the second quadrant of diagram, themes have well-developed internal ties but unimportant external ties, as they are of only marginal importance for the field. These themes are very specialized and peripheral (eg, DNA-binding). In the third quadrant, themes are both weakly developed and marginal. The themes in this quadrant have low density and centrality and mainly represent either emerging or declining themes (eg, ovarian neoplasm). Themes in the fourth quadrant of the strategic diagram are considered important for a research field but are not fully developed. This quadrant contains transversal and general, basic themes (eg, immunohistochemistry). Scientometric analysis of breast cancer research can be regarded as a roadmap for future research and policymaking for this important field.

Profile of the Users and the Most Visited Topics of a Pediatric eHealth Website

Parents need information about their children's health, and the Internet has become an essential repository for this information. However, there is almost no information about which topics are the most searched, consulted, or shared, or about the main characteristics of pediatric website users. The main aim of this research was to describe the profile of the users of a pediatric website, which topics they searched for, which topics were the most consulted, and which were the most shared. Users' demographic data were analyzed regarding their use of the Internet to search for information about health. A pediatric website for parents was analyzed. A 26-item questionnaire collected demographical features of the users of the website. Descriptive and analytical analyses were performed. Most participants used general search engines for their health searches, and the most searched keywords were prurigo, barking cough, and laryngitis. The most visited topics were unexplained fever, snots, and laryngitis. The most shared were snots, lipotomy, and dizziness. The users were mainly women (67.8%), with an average age of 38.8 years, and one or two children (89%) with a mean age of 4.6 years. The users who mainly used the Internet for health purposes were women of younger age, and with a higher educational level.

Current Status and Emerging Trends on the Adaptive Reuse of Buildings: A Bibliometric Analysis

The emerging demand for sustainable development and the need for efficient use of resources across the built environment have stirred research efforts globally. The construction sector is often regarded as one of the major world consumers of resources, so many international establishments are trying to create a sustainable environment through adaptive reuse of existing building stocks, a concept which has been receiving momentous recognition by reason of its richly diversified applicability for circular economy. Thus, profound knowledge of the topic and research trends is requisite to promote scholarship. For this analysis, the global research developments in adaptive reuse are assessed according to published documents, co-authorship, geographical distribution and keyword- co-occurrences. From the Scopus directory, 227 journal articles published from 2006 to 2021 were retrieved. Results showed that from 2006, published documents rose by 221 articles. About 29% of the publications were from Italy and the United Kingdom. Among the articles, 110 were from the subject area of environmental science (48.5%), while the subject area of engineering represents 104 publications (45.8%). Recent progress in adaptive reuse in building and construction includes, but not limited to: (i) component and materials reuse and technology, (ii) life cycle assessment, (iii) economic assessment and multi-criteria decision making and (iv) regulatory policies and stakeholders’ analysis. The findings are important to furnish all relevant personnel in the academic and industries with a broad perception of the status and potential emerging trends on the adaptive reuse of buildings.

Association Between eHealth Literacy in Online Health Communities and Patient Adherence: Cross-sectional Questionnaire Study

Background

eHealth literacy is significantly associated with patients’ online information behavior, physician-patient relationship, patient adherence, and health outcomes. As an important product of the internet, online health communities (OHCs) can help redistribute idle medical resources, increase medical resource utilization, and improve patient adherence. However, studies on eHealth literacy in OHCs are limited. Therefore, this study examined patients’ eHealth literacy regarding health information–seeking behavior and physician-patient communication in OHCs.

Objective

This study aimed to investigate the association between eHealth literacy in OHCs and patient adherence by employing social cognitive theory.

Methods

This was an empirical study, in which a research model consisting of 1 independent variable (patients’ eHealth literacy), 3 mediators (physician-patient communication in OHCs, patient health information–seeking behavior in OHCs, and patients’ perceived quality of health information in OHCs), 1 dependent variable (patient adherence), and 4 control variables (age, gender, living area, and education level) was established to examine the associations. Multi-item scales were used to measure variables. An anonymous online survey involving 560 participants was conducted through Chinese OHCs in July 2018 to collect data. Partial least squares and structural equation modeling were adopted to analyze data and test hypotheses.

Results

The survey response rate was 79.6% (446/560). The reliability, convergent validity, and discriminant validity were acceptable. Age, gender, living area, and education level were positively associated with patient adherence, and gender was positively associated with physician-patient communication and patients’ perceived quality of internet health information in OHCs. Patients’ eHealth literacy was positively associated with patient adherence through the mediations of physician-patient communication, internet health information–seeking behavior, and perceived quality of internet health information in OHCs.

Conclusions

Results indicate that physician-patient communication, internet health information–seeking behavior, and the perceived quality of internet health information are significantly associated with improving patient adherence via a guiding of eHealth literacy in OHCs. These findings suggest that physicians can understand and guide their patients’ eHealth literacy to improve treatment efficiency; OHCs’ operators should this strengthen the management of information quality, develop user-friendly features, and minimize the gap between the actual and perceived information quality.

Research hotspots and trends in nursing education from 2014 to 2020: A co-word analysis based on keywords

AIMS

To investigate research hotspots and trends in nursing education from 2014 to 2020, and provide references for researchers to understand the research status and developing trends in this field.

DESIGN

A co-word analysis based on keywords.

METHODS

Data were obtained from nursing education-related academic research articles that were retrieved through a literature search using PubMed during the period of 2014-2020. Keywords included in the analysis of literature were considered as the research objects. Bibliographic Item Co-occurrence Matrix Builder (BICOMB) was employed to extract high-frequency keywords and generate co-occurrence matrix, graphical clustering toolkit (gCLUTO) was used to perform cluster analysis, and SPSS 25.0 was used to perform strategic diagram analysis.

RESULTS

Overall, 7857 articles were retrieved, from which 2679 keywords were obtained and 64 high-frequency keywords extracted. The results revealed seven hotspots in nursing education during the period of 2014-2020, which included research on: (i) continuing education in nursing, (ii) application and influence of the internet in nursing education, (iii) postgraduate nursing education, (iv) undergraduate nursing education and clinical quality training, (v) current development status and tendency of nursing education, (vi) nursing teaching methods and (vii) organization and management in nursing education.

CONCLUSION

The seven research hotspots could reflect the publication trends in nursing education. By providing a co-word analysis-including cluster and strategic diagram analysis-an overall command of the latest hotspots can be depicted, and researchers conducting research in nursing education can have some hints.

IMPACT

This study allows the development of future research on nursing education. Future researchers should explore the application of new network technologies in the process of nursing teaching, quality of postgraduate nursing education, innovative teaching methods as well as teaching strategies of improving students' clinical ability, current situation of economics and leadership in nursing education and ability of organization and management in undergraduate nursing education.

Online Public Attention Toward Premature Ejaculation in Mainland China: Infodemiology Study Using the Baidu Index

BACKGROUND

Premature ejaculation (PE) is one of the most described psychosocial stress and sexual complaints worldwide. Previous investigations have focused predominantly on the prospective identification of cases that meet researchers' specific criteria. The genuine demand from patients with regard to information on PE and related issues may thus be neglected.

OBJECTIVE

This study aims to examine the online search trend and user demand related to PE on a national and regional scale using the dominant major search engine in mainland China.

METHODS

The Baidu Index was queried using the PE-related terms for the period of January 2011 to December 2020. The search volume for each term was recorded to analyze the search trend and demographic distributions. For user interest, the demand and trend data were collected and analyzed.

RESULTS

Of the 36 available PE search keywords, 4 PE searching topics were identified. The Baidu Search Index for each PE topic varied from 46.30% (86,840,487/187,558,154) to 6.40% (12,009,307/187,558,154). The annual percent change (APC) for the complaint topic was 48.80% (P<.001) for 2011 to 2014 and -16.82% (P<.001) for 2014 to 2020. The APC for the inquiry topic was 16.21% (P=.41) for 2011 to 2014 and -11.00% (P<.001) for 2014 to 2020. For the prognosis topic, the annual APC was 11.18% (P<.001) for 2011 to 2017 and -19.86% (P<.001) for 2017 to 2020. For the treatment topic, the annual APC was 14.04% (P<.001) for 2011 to 2016 and -38.83% (P<.001) for 2016 to 2020. The age distribution of those searching for topics related to PE showed that the population aged 20 to 40 years comprised nearly 70% of the total search inquiries (second was 17.95% in the age group younger than 19 years). People from East China made over 50% of the total search queries.

CONCLUSIONS

The fluctuating online popularity of PE searches reflects the real-time population demands. It may help medical professionals better understand population interest, population concerns, regional variations, and gender differences on a nationwide scale and make disease-specific health care policies. The internet search data could be more reliable when the insufficient and lagging registry data are completed.

Online Patient Information on Domiciliary Oxygen Therapy: An Evaluation of Quality, Suitability, Reliability, Readability and Content

BACKGROUND

Domiciliary oxygen therapy (DOT) is a complex intervention and has significant impact on patients' daily activities, quality of life, and mental wellbeing. Suitable education is pertinent in improving patients' understanding and usage of DOT, as those receiving appropriate education have a better knowledge of their prescription, clearer expectations, and improved adherence to DOT.

RESEARCH QUESTION

Do currently available online patient resources on DOT provide high-quality information for patients?

STUDY DESIGN AND METHODS

We evaluated the first 100 results of three major search engines [Google, Yahoo and Bing] using the terms, "home oxygen therapy" and "information or education". Website content was assessed based on Thoracic Society of Australia and New Zealand and British Thoracic Society domiciliary oxygen guidelines. Validated tools were used to evaluate resource quality [DISCERN instrument], suitability [Suitability Assessment of Materials (SAM)], reliability [Journal of the American Medical Association (JAMA) benchmarks and the Health on the Net (HON) code], and readability [Flesch Reading Ease and Flesch-Kincaid Grade Level].

RESULTS

Thirty-six websites met study inclusion criteria. Websites from foundation/advocacy organisations scored the highest in quality and suitability, with a median DISCERN total score of 48.0 (interquartile range: 43.5-60.0) or "fair" and a median SAM suitability score of 70% (53.0-71.0) or "superior". Industry/for-profit websites had the best content score of 7.8 (5.0-8.6). The HON accreditation seal was present on 14% of the websites and only five websites met the four JAMA benchmarks. The median readability scores exceeded the recommended reading grades of 6th to 8th level for consumer health-related educational resources.

INTERPRETATION

The overall quality, suitability, reliability, and content of online health resources for DOT are of a low-to-moderate standard, with the reading grade at an unsuitable level for the general population. Health professionals should be aware of the limitations of currently available online DOT patient resources.

Theme Trends and Knowledge-Relationship in Lifestyle Research: A Bibliometric Analysis

Healthy living habits (healthy eating, regular physical activity, abstinence from smoking, restrictions on alcohol consumption, and stress management) can help prevent a significant number of diseases. The purpose of this study is to use a bibliometric analysis to analyze the relationships between countries, institutions and authors through lifestyle studies from 2016 to 2020 to find out the latest research trends. This study utilized bibliometric data collected through Scopus including thesis titles, authors, agencies, countries/regions, publication years, and keywords. Data were analyzed using the VOS viewer (Vers. 1.6.13; Leiden University, Leiden, The Netherlands) and the findings were used to visualize similarity mapping techniques. Publication of lifestyle-related research papers has steadily increased between 2016 and 2020. The country/region most actively conducting such research was the United States, also home to the majority of institutions conducting work in the field. PloS ONE published the most lifestyle-related research under the field of Medicine. Identified keywords were related to risk measures, psychosocial factors, prevention, health promotion, and risk factors. Lifestyle research is a promising field of research worldwide and has great potential to improve human health, the environment, and quality of life. The findings are expected to promote future research and give direction to the advancement of the field of research by comprehensively analyzing and summarizing lifestyle research trends.

The Sustainable Development of Financial Topic Detection and Trend Prediction by Data Mining

Blockchain technology is the most cutting-edge technology in the field of financial technology, which has attracted extensive attention from governments, financial institutions and investors of various countries. Blockchain and finance, as an interdisciplinary, cross-technology and cross-field topic, has certain limitations in both theory and application. Based on the bibliometrics data of Web of Science, this paper conducts data mining on 759 papers related to blockchain technology in the financial field by means of co-word analysis, bi-clustering algorithm and strategic coordinate analysis, so as to explore hot topics in this field and predict the future development trend. The experimental results found ten research topics in the field of blockchain combined with finance, including blockchain crowdfunding, Fintech, encryption currency, consensus mechanism, the Internet of Things, digital financial, medical insurance, supply chain finance, intelligent contract and financial innovation. Among them, blockchain crowdfunding, Fintech, encryption currency and supply chain finance are the key research directions in this research field. Finally, this paper also analyzes the opportunities and risks of blockchain development in the financial field and puts forward targeted suggestions for the government and financial institutions.

Using Search Trends to Analyze Web-Based Interest in Lower Urinary Tract Symptoms-Related Inquiries, Diagnoses, and Treatments in Mainland China: Infodemiology Study of Baidu Index Data

Background

Lower urinary tract symptoms (LUTS) are one of the most commonly described urination disorders worldwide. Previous investigations have focused predominantly on the prospective identification of cases that meet the researchers’ criteria; thus, the genuine demands regarding LUTS from patients and related issues may be neglected.

Objective

We aimed to examine web-based search trends and behaviors related to LUTS on a national and regional scale by using the dominant, major search engine in mainland China.

Methods

Baidu Index was queried by using LUTS-related terms for the period of January 2011 to September 2020. The search volume for each term was recorded to analyze search trends and demographic distributions. For user interest, user demand graph data and trend data were collected and analyzed.

Results

Of the 13 LUTS domains, 11 domains are available in the Baidu Index database. The Baidu search index for each LUTS domain varied from 37.78% to 1.47%. The search trends for urinary frequency (2011-2018: annual percent change APC=7.82%; P<.001), incomplete emptying (2011-2014: APC=17.74%; P<.001), nocturia (2011-2018: APC=11.54%; P<.001), dysuria (2017-2020: APC=20.77%; P<.001), and incontinence (2011-2016: APC=13.39%; P<.001) exhibited fluctuations over time. The search index trends for weak stream (2011-2017: APC=−4.68%; P<.001; 2017-2020: APC=9.32%; P=.23), split stream (2011-2013: APC=9.50%; P=.44; 2013-2020: APC=2.05%; P=.71), urgency (2011-2018: APC=−2.63%; P=.03; 2018-2020: APC=8.58%; P=.19), and nocturnal enuresis (2011-2018: APC=−3.20%; P=.001; 2018-2020: APC=−4.21%; P=.04) remained relatively stable and consistent. The age distribution of the population for all LUTS-related inquiries showed that individuals aged 20 to 40 years made 73.86% (49,218,123/66,635,247) of the total search inquiries. Further, individuals aged 40 to 49 years made 12.29% (8,193,922/66,635,247) of the total search inquiries for all LUTS-related terms. People from the east part of China made 67.79% (45,172,031/66,635,247) of the total search queries. Additionally, most of the searches for LUTS-related terms were related to those for urinary diseases to varying degrees.

Conclusions

Web-based interest in LUTS-related terms fluctuated wildly and was reflected timely by Baidu Index in mainland China. The web-based search popularity of each LUTS-related term varied significantly and differed based on personal interests, the population’s concerns, regional variations, and gender. These data can be used by care providers to track the prevalence of LUTS and the population’s interests, guide the establishment of disease-specific health care policies, and optimize physician-patient health care sessions.

Predictors of Health Information-Seeking Behavior: Systematic Literature Review and Network Analysis

Background

People engage in health information–seeking behavior to support health outcomes, and being able to predict such behavior can inform the development of interventions to guide effective health information seeking. Obtaining a comprehensive list of the predictors of health information–seeking behavior through a systematic search of the literature and exploring the interrelationship of these predictors are critical first steps in this process.

Objective

This study aims to identify significant predictors of health information–seeking behavior in the primary literature, develop a common taxonomy for these predictors, and identify the evolution of the concerned research field.

Methods

A systematic search of PsycINFO, Scopus, and PubMed was conducted for all years up to and including December 10, 2019. Quantitative studies identifying significant predictors of health information–seeking behavior were included. Information seeking was broadly defined and not restricted to any source of health information. Data extraction of significant predictors was performed by 2 authors, and network analysis was conducted to observe the relationships between predictors with time.

Results

A total of 9549 articles were retrieved, and after the screening, 344 studies were retained for analysis. A total of 1595 significant predictors were identified. These predictors were categorized into 67 predictor categories, with the most central predictors being age, education, gender, health condition, and financial income. With time, the interrelationship of predictors in the network became denser, with the growth of new predictor grouping reaching saturation (1 new predictor identified) in the past 7 years, despite increasing publication rates.

Conclusions

A common taxonomy was developed to classify 67 significant predictors of health information–seeking behavior. A time-aggregated network method was developed to track the evolution of the research field, showing the maturation of new predictor terms and an increase in primary studies reporting multiple significant predictors of health information–seeking behavior. The literature has evolved with a decreased characterization of novel predictors of health information–seeking behavior. In contrast, we identified a parallel increase in the complexity of predicting health information–seeking behavior, with an increase in the literature describing multiple significant predictors.

The progress and trend of pro-environmental behavior research: a bibliometrics-based visualization analysis

Pro-environmental behavior (PEB) has always been a hot topic in academic and practical, and it is highly necessary to explore the research progress and development trend of PEB. Based on 1038 relevant literatures published and the Web of Science core database, this paper used citation analysis, co-word analysis and cluster analysis methods to systematically analyze the dynamic evolution process of PEB's research topics, knowledge base and subject areas. The results show that PEB research is currently in a period of rapid growth. And PEB research presents typical multidisciplinary characteristics, mainly focuses on Psychology-Education-Social, Economics-Economic-Political, Environmental-Toxicology-Nutrition and other disciplines. Then, this study also finds that the PEB research hotspots mainly concentrated in seven directions such as "Environmental cognition, emotion and motivation process", etc., which can be further classified into three horizontal levels and three vertical levels. This study will provide valuable theoretical and practical reference for the future research of PEB.

Mapping themes trends and knowledge structure of trophoblastic invasion, a bibliometric analysis from 2012-2021

OBJECTIVES

Trophoblastic invasion at the maternal-fetal interface can affect pregnancy outcomes. To describe an intuitive theme trends and knowledge structure of trophoblastic invasion-related literature from a bibliometric perspective, and provide researchers with new research hotspots.

STUDY DESIGN

The literature form PubMed database related to trophoblastic invasion from January 1, 2012 to April 30, 2021 were extracted, and then biclustering analysis, co-word analysis, strategy diagram and social network analysis were performed to provide immature, or newly emerging research hotspots for researchers.

RESULTS

A total of 96 high-frequency medical subjects heading terms were extracted and classified into 6 clusters. Themes in the first and second quadrant of strategy diagram, including trophoblasts metabolism, placenta metabolism, pre-eclampsia, etc., as the mature parts of the research on trophoblastic invasion have been well developed. On the other hand, themes in the third and fourth quadrants of strategy diagram, such as embryo implantation and trophoblasts immunology, pregnancy complication, matrix metalloproteinase and trophoblasts metabolism, habitual abortion and trophoblasts metabolism, etc., are immature themes. Social network analysis suggests that themes at the edge, such as habitual abortion / metabolism, placenta / immunology, natural killer cells / physiology, natural killer cells / immunology, embryo implantation / immunology, are considered new research hotspots and have considerable research space.

CONCLUSION

By analyzing the research hotspots related to trophoblastic invasion, immature themes and emerging hotspots deserve more attention and can be considered as hints when launching new research projects.

Bibliometrics and Visual Analysis of the Research Status and Trends of Postpartum Depression From 2000 to 2020

The purpose of this study was to evaluate the international scientific output on postpartum depression (PPD) research during 2000–2020 through a bibliometric analysis and to explore research hotspots, frontiers, and trends in the field of postpartum depression. We searched the Web of Science Core Collection for publications on postpartum depression published between 2000 and 2020. CiteSpace, gCluto, and other software applications were used to analyze the data by year, journal, and country. A total of 2,963 publications were retrieved and 96 countries or regions published related papers. The United States had the largest number of published papers and the highest betweenness centrality, which is the dominant position in the field of postpartum depression. A total of 717 journals published papers, with the Archives of Womens Mental Health ranked first in terms of volume and betweenness centrality. In this study, 31 high-frequency main MeSH terms/subheadings were selected. The high-frequency MeSH terms were clustered into six categories: an overview of depression-related research, diagnostic and screening scales for postpartum depression, epidemiological investigation into postpartum depression, treatment and drug selection for postpartum depression, psychological research on postpartum depression, and etiology, physiopathology, complications, genetics of postpartum depression. Finally, we used strategic diagram to analyze research trends in postpartum depression. This study has identified a continuous significant increase in the publication of PPD articles. Currently, the etiology, physiological pathology, intervention and treatment of complications on PPD are immature, which provides reference for the trend of obstetric psychology.