Visualizing Collaboration Characteristics and Topic Burst on International Mobile Health Research: Bibliometric Analysis

Research status and hotspots of tight junctions and colorectal cancer: A bibliometric and visualization analysis

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related death. Over the past two decades, numerous researchers have provided important evidence regarding the role of tight junction (TJ) proteins in the occurrence and progression of CRC. The causal relationship between the presence of specific TJ proteins and the development of CRC has also been confirmed. Despite the large number of publications in this field, a bibliometric study to review the current state of research and highlight the research trends and hotspots in this field has not yet been performed.

AIM

To analyze research on TJs and CRC, summarize the field's history and current status, and predict future research directions.

METHODS

We searched the Science Citation Index Expanded database for all literature on CRC and TJs from 2001-2023. We used bibliometrics to analyze the data of these papers, such as the authors, countries, institutions, and references. Co-authorship, co-citation, and co-occurrence analyses were the main methods of analysis. CiteSpace and VOSviewer were used to visualize the results.

RESULTS

A total of 205 studies were ultimately identified. The number of publications on this topic has steadily increased since 2007. China and the United States have made the largest contributions to this field. Anticancer Research was the most prolific journal, publishing 8 articles, while the journal Oncogene had the highest average citation rate (68.33). Professor Dhawan P was the most prolific and cited author in this field. Co-occurrence analysis of keywords revealed that "tight junction protein expression", "colorectal cancer", "intestinal microbiota", and "inflammatory bowel disease" had the highest frequency of occurrence, revealing the research hotspots and trends in this field.

CONCLUSION

This bibliometric analysis evaluated the scope and trends of TJ proteins in CRC, providing valuable research perspectives and future directions for studying the connection between the two. It is recommended to focus on emerging research hotspots, such as the correlations among intestinal microbiota, inflammatory bowel disease, TJ protein expression, and CRC.

The evolution and mapping trends of mobile health (m-Health): a bibliometric analysis (1997-2023)

Background

Mobile health (m-Health) is widely acknowledged as a pivotal domain for improving global healthcare and driving its digital health transformation. Despite the vast amount of literature published in recent years, bibliometric studies on m-Health remain limited in scope and coverage. This study presents a comprehensive review of m-Health literature extracted from Scopus and PubMed databases, spanning the period from 1997 to 2023, including publications during the coronavirus disease 2019 (COVID-19) pandemic.

Methods

The combined Scopus and PubMed databases were used in this study. The search formula for the literature retrieval used the most appropriate and relevant keywords to m-Health. The bibliometric data importation, extraction and analysis of authors, titles, publication date, publication place, publisher, volume number, issue number, citation count, document type, author keywords, affiliation were all carried out using the 'Biblioshiny', 'EndNote X9®', 'Microsoft Excel®' and 'Microsoft Access®' software tools. Duplicate records were manually identified and removed. Visualization maps illustrating the recurrent keywords, collaboration patterns, and prolific publishing countries were generated using 'VOSviewer®'.

Results

A total of 37,470 (20,703 from Scopus and 16,767 from PubMed) publications were selected for the literature analysis. The results provided the definitive literature evidence on the origin of the concept of m-Health in 2003. Significant increase in the publications followed the global surge of smart phones usage in 2007, and the emergence of m-Health applications (Apps) and their global markets and ecosystems. The number of the publications peaked between 2013 and 2022 with most citations in 2022. There was noticeable spike in m-Health literature during the COVID-19 pandemic. The results also showed that most of the highly cited publications, leading institutions, and most prolific authors were predominantly from the developed countries. The USA has the highest number of publications followed by the UK, Australia, Germany, Canada and China, with most of the prolific authors originating from these countries.

Conclusions

In conclusion, while there has been a remarkable increase in global m-Health publications since 2003, most of the impactful literature and publications in this area originated from selected countries in the developed world. The study indicates a significant disparity between the published literature from developed compared to the developing countries. Addressing this disparity, further bibliographical studies are required to address these and other literature gaps.

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

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

Thematic maps with scatter and 4-quadrant plots in R to identity dominant entities on schizophrenia in psychiatry since 2017: Bibliometric analysis

BACKGROUND

Schizophrenia affects more than 21 million people worldwide. There have been a number of articles published in the literature regarding schizophrenia. It is unclear which authors contributed the most to the field of schizophrenia. This study examines which article entities (affiliated countries, institutes, journals, and authors) earn the most research achievements (RAs) and whether keywords in articles are associated with the number of article citations.

METHODS

As of August 25, 2022, 20,606 abstracts published on schizophrenia in psychiatry since 2017 were retrieved from the WoS core collection (WoSCC). RAs were measured using the category, JIF, authorship, and L-index (CJAL) score. The follower-leading cluster algorithm (FLCA) was used to examine clusters of keywords associated with core concepts of research. There were 7 types of visualizations used to report the study results, including Sankey diagrams, choropleth maps, scatter charts, radar plots, and cluster plots. A hypothesis was examined that the mean number of citations for keywords could predict the number of citations for 100 top-cited articles(T100SCHZ).

RESULTS

The results indicate that the US (18861), Kings College London (U.S. (2572), Psychiatry (14603), and Kolanu Nithin (Australia) (9.88) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. The journal of Schizophrenia Res had higher citations (19,017), counts (1681), and mean citations (11.31) in journals. There was a significant correlation between article citations and weighted keywords (F = 1471.74; P < .001).

CONCLUSION

Seven visualizations were presented to report the study results, particularly with thematic maps using scatter and 4-quadrant plots produced in R programming language. We recommend that more future bibliographical studies utilize CAJL scores and thematic maps to report their findings, not restrict themselves solely to schizophrenia in psychiatry as done in this study.

Bibliometric analysis and visualization of research trends on HIV-1 capsid inhibitors (2000-2022)

Background: Acquired immunodeficiency syndrome (AIDS) has seriously endangered human life and health, the main pathogenic agent is human immunodeficiency virus type 1 (HIV-1). The combination antiretroviral therapy (cART) has shown serious drug resistance and side effects, and the discovery of HIV-1 capsid inhibitors is an effective way to solve the problem. Recent studies have shown significant progress in the research of HIV-1 capsid inhibitors. However, there is still a lack of comprehensive overview of bibliometric analysis in this field. This study aimed to provide the research trends and hotspots of HIV-1 capsid inhibitors. Method: Publications related to HIV-1 capsid inhibitors from 2000 to 2022 were searched on the Web of Science Core Collection (WoSCC) database and screened according to inclusion criteria. VOSviewer was conducted to evaluate the results. Results: 96 publications from 25 countries were finally included, and the number of annual publications related to HIV-1 capsid inhibitors showed an increasing trend. The United States was the most productive country with the most publication number, H-index, and total citation number, as well as the widest international cooperation. The most popular journal in this field was Journal of Virology. Drexel University was the most productive institution, and Simon Cocklin participated in the most publications. Keywords co-occurrence analysis exhibited that studying the molecular mechanism of capsid protein, discovering drug candidates, and improving antiretroviral therapy are the main and hot topics in this field. Conclusion: This is the first bibliometric study in the field of HIV-1 capsid inhibitors, which comprehensively analyzed the research trends and hotspots in this direction. This work is expected to provide the scientific community with new insights to promote the research of HIV-1 capsid inhibitors.

Visualizing burst spots on research for four authors in MDPI journals named to be Citation Laureates 2021 using temporal bar graph

BACKGROUND

The appearance of a topic in a document stream is signaled by a burst of activity, with certain features rising sharply in frequency as the topic emerges. Although temporal bar graph (TBG) is frequently applied to present the burst spot in the bibliographical study, none of the research has combined the inflection point (IP) to interpret the burst spot feature. The aims of this study are to improve the traditional TBG and apply the TBG to understand better the evolution of a topic (e.g., publications and citations for a given author).

METHODS

The EISTL model, including entity, indicator, selection of a few vital ones (named attributes) with higher values in quantity (e.g., the citation data of the top 10 entities), TBG and line-chart plots to verify the trend of interest, was proposed to demonstrate the TBG as a whole. The IP locations compared to the median point in data along with the heap map and line-chart trend were identified. The burst strength was computed. A dashboard on Google Maps was designed and launched for bibliometric analysis. Four authors in MDPI (Multidisciplinary Digital Publishing Institute) journals named to be Citation Laureates 2021 were recruited to compare their research achievements shown on the TBG, particularly displaying the burst spots and the recent developments and stages (e.g., increasing, ready to increase, slowdown, or decreasing).

RESULTS

We observed that the highest burst strengths in publication and citations are earned by Barry Halliwell (8.99) and Jean-Pierre Changeux (18.01). The breakthrough of TBG using the EISTL model to display the influence of authors in academics was made with 2 parts of the primary IP point and the trend feature in the data.

CONCLUSION

The dashboard-type TBG shown on Google Maps is unique and innovative and able to provide deeper insights to readers, not merely limited to the publications and citations for a given author as we did in this study.

Analyzing the number of articles with network meta-analyses using chord diagrams and temporal heatmaps over the past 10 years: Bibliometric analysis

BACKGROUND

Network meta-analyses (NMAs) are statistical techniques used to synthesize data from multiple studies and compare the effectiveness of different interventions for a particular disease or condition. They have gained popularity in recent years as a tool for evidence-based decision making in healthcare. Whether publications in NMAs have an increasing trend is still unclear. This study aimed to investigate the trends in the number of NMA articles over the past 10 years when compared to non-NMA articles.

METHODS

The study utilized data from the Web of Science database, specifically searching for articles containing the term "meta-analysis" published between 2013 and 2022. The analysis examined the annual number of articles, as well as the countries, institutions, departments, and authors associated with the articles and the journals in which they were published. Ten different visualization techniques, including line charts, choropleth maps, chord diagrams, circle packing charts, forest plots, temporal heatmaps, impact beam plots, pyramid plots, 4-quadrant radar plots, and scatter plots, were employed to support the hypothesis that the number of NMA-related articles has increased (or declined) over the past decade when compared to non-NMA articles.

RESULTS

Our findings indicate that there was no difference in mean citations or publication trends between NMA and non-NMA; the United States, McMaster University (Canada), medical schools, Dan Jackson from the United Kingdom, and the Journal of Medicine (Baltimore) were among the leading entities; NMA ranked highest on the coword analysis, followed by heterogeneity, quality, and protocol, with weighted centrality degrees of 32.51, 30.84, 29.43, and 24.26, respectively; and the number of NMA-related articles had increased prior to 2020 but experienced a decline in the past 3 years, potentially due to being overshadowed by the intense academic focus on COVID-19.

CONCLUSION

It is evident that the number of NMA articles increased rapidly between 2013 and 2019 before leveling off in the years following. For researchers, policymakers, and healthcare professionals who are interested in evidence-based decision making, the visualizations used in this study may be useful.

The ascendancy of research in acronyms related to COVID-19 displayed on a growth-share matrix (GSM): Bibliometric analysis

BACKGROUND

The acronym COVID, which stands for coronavirus disease, has become one of the most infamous acronyms in the world since 2020. An analysis of acronyms in health and medical journals has previously found that acronyms have become more common in titles and abstracts over time (e.g., DNA and human immunodeficiency virus are the most common acronyms). However, the trends in acronyms related to COVID remain unclear. It is necessary to verify whether the dramatic rise in COVID-related research can be observed by visualizations. The purpose of this study was to display the acronym trends in comparison through the use of temporal graphs and to verify that the COVID acronym has a significant edge over the other 2 in terms of research dominance.

METHODS

An analysis of the 30 most frequently used acronyms related to COVID in PubMed since 1950 was carried out using 4 graphs to conduct this bibliometric analysis, including line charts, temporal bar graphs (TBGs), temporal heatmaps (THM), and growth-share matrices (GSM). The absolute advantage coefficient (AAC) was used to measure the dominance strength for COVID acronym since 2020. COVID's AAC trend was expected to decline over time.

RESULTS

This study found that COVID, DNA, and human immunodeficiency virus have been the most frequently observed research acronyms since 2020, followed by computed tomography and World Health Organization; although there is no ideal method for displaying acronym trends over time, researchers can utilize the GSM to complement traditional line charts, TBGs, and THMs, as shown in this study; and COVID has a significant edge over the other 2 in terms of research dominance by ACC (≥0.67), but COVID's AAC trend has declined (e.g., AACs 0.83, 0.80, and 0.69) since 2020.

CONCLUSIONS

It is recommended that the GSM complement traditional line charts, TBGs, and THMs in trend analysis, rather than being restricted to acronyms in future research. This research provides readers with the AAC to understand how research dominates its counterparts, which will be useful for future bibliometric analyses.

Using chord diagrams to explore article themes in 100 top-cited articles citing Hirsch's h-index since 2005: A bibliometric analysis

BACKGROUND

The h-index is increasingly being used as a measure of individual research achievement (IRA). More than 4876 citing articles have been published and indexed in Web of Science. The articles citing the h-index that have made the greatest contribution to scientific academics are still unknown. It is also unclear which subject categories (SCs) can be classified based on their keywords.

METHODS

These 4976 citing articles have been collected from the Web of Science since 2005. SCs were classified using chord diagrams to visualize their associations of SCs and documents in 100 top-cited articles (T100hciting). In addition to chord diagrams, 6 visualizations were used to illustrate study results: choropleth maps were used to depict the geographical distribution of publications across countries, network diagrams were created by using coword analysis, box plots were created to complement the network diagrams, Sankey diagrams highlighted the 5 most important elements in each article entity, the dot plot was used for displaying T100hciting, and a radar plot was used to present the top 10 high-IRA elements of countries, institutes, departments, and authors based on category, journal impact factor, authorship, and L-index scores.

RESULTS

A coword cluster analysis indicates that the majority of articles come from the US (918, 18%) and China (603, 12%), the top 2 SCs are h-index and bibliometric analysis, and the top 5 countries account for 55% in T100hciting, such as the US (25%), Spain (10%), Netherlands (9%), China (6%), and Belgium (5%). In T100hciting, 4 SCs are included, namely, the h-index (72%), bibliometric analysis (24%), physics & multidisciplinary (3%), and infectious diseases (1%).

CONCLUSION

A total of 7 visualizations were used to display the results in this study. Chord diagrams are suggested as a tool for future bibliographical studies to classify SCs Future bibliometrics with chord diagrams should not be limited to the topic of h-index-citing articles, as we did in this study.

Analysis of citation trends to identify articles on delirium worth reading using DDPP model with temporal heatmaps (THM): A bibliometric analysis

BACKGROUND

Delirium is one of the most common geriatric syndromes in older patients, accounting for 25% of hospitalized older patients, 31 to 35% of patients in the intensive care unit, and 8% to 17% of older patients in the emergency department (ED). A number of articles have been published in the literature regarding delirium. However, it is unclear about article citations evolving in the field. This study proposed a temporal heatmap (THM) that can be applied to all bibliographical studies for a better understanding of cited articles worth reading.

METHODS

As of November 25, 2022, 11,668 abstracts published on delirium since 2013 were retrieved from the Web of Science core collection. Research achievements were measured using the CJAL score. Social network analysis was applied to examine clusters of keywords associated with core concepts of research. A THM was proposed to detect articles worth reading based on recent citations that are increasing. The 100 top-cited articles related to delirium were displayed on an impact beam plot (IBP).

RESULTS

The results indicate that the US (12474), Vanderbilt University (US) (634), Anesthesiology (2168), and Alessandro Morandi (Italy) (116) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. Articles worthy of reading were highlighted on a THM and an IBP when an increasing trend of citations over the last 4 years was observed.

CONCLUSION

The THM and IBP were proposed to highlight articles worth reading, and we recommend that more future bibliographical studies utilize the 2 visualizations and not restrict them solely to delirium-related articles in the future.

The model of descriptive, diagnostic, predictive, and prescriptive analytics on 100 top-cited articles of nasopharyngeal carcinoma from 2013 to 2022: Bibliometric analysis

BACKGROUND

Nasopharyngeal carcinomas (NPCs) are prevalent in southeast Asia. There is a need to systematically review the current trend and status of NPC research. However, most bibliometric analyses have tended to focus on descriptive and diagnostic analytics rather than predictive and prescriptive analyses. Thus, it is necessary to use the model of the 4 (called the descriptive, diagnostic, predictive, and prescriptive analytics [DDPP]) to derive insights from the data. This study aimed to apply the DDPP model to classify article themes and illustrate the characteristics of NPCs; compare NPC researcher achievements across countries, institutes, departments, and authors; determine whether the mean citations of keywords can be used to predict article citations; and highlight articles that are worthy of reading.

METHODS

The Web of Science Core Collection was searched for 100 top-cited articles and reviews related to NPCs published between 2013 and 2022. As part of Microsoft Office Excel 2019, Visual Basic for Applications was used to illustrate the number of publications and scientific productivity of authors over time and to generate network/temporal heatmaps, chord/Sankey diagrams, radar/impact beam plots, and scatter/pyramid charts about collaborations among countries. The DDPP model identifies institutions, authors, and hotspots of NPC research. The category, journal, authorship, and L-index (CJAL) score was applied to evaluate individual research achievements.

RESULTS

A total of 10,564 publications were extracted from Web of Science Core Collection and screened for 100 top-cited articles and reviews related to NPCs. Despite having the highest number of publications (36%), China lags slightly behind the US in CJAL scores. CJAL was higher at Sun Yat-Sen University, Radiat Oncol department, and author Jun Ma from China. The number of article citations was significantly correlated with the number of weighted keywords (F = 1791.17; P < .0001). Six articles with significantly increasing citations over the last 4 years were recommended.

CONCLUSION

This bibliometric study utilizes the DDPP model to analyze the scientific progress of NPC over the past decade. The whole genome is a hot topic that may prove to be a promising research area in the future. A temporal heatmap may serve as a tool for providing readers with articles that are worth reading, which could lead to additional research in bibliometrics.

Using temporal heatmaps to identify worthwhile articles on immune checkpoint blockade for melanoma (ICBM) in Mainland China, Hong Kong, and Taiwan since 2000: A bibliometric analysis

BACKGROUND

Melanoma is a life-threatening form of skin cancer. Due to its remarkable effectiveness, the immune checkpoint blockade is widely used to treat melanoma (ICBM). No research has been conducted on ICBM for identifying the most readable articles. A bibliometric analysis of 100 top-cited ICBM (T100ICBM) in recent decades is required to highlight articles worth reading.

METHODS

Based on the Web of Science Core Collection, we summarized the articles on ICBM published in each year from 2000 to 2022, with first authors from Mainland China, Hong Kong, and Taiwan (CHT). Using the CJAL score, data extraction and visualization of the distribution of ICBM publications were conducted on 2718, and 100 top-cited articles, respectively. We used the temporal heatmap to identify the most readable articles. Four descriptive, diagnostic, predictive, and prescriptive analytics (called DDPP model) were applied to describe the features of T100ICBM articles. The absolute advantage coefficient was used to determine the dominance extent of the most influential region, institute, department, and author.

RESULTS

A total of 2718 publications was included after removing first or corresponding authors who were not affiliated with CHT. Publications by year showed a sharp increase from 2014 onward and either peaked in 2022 or have not yet peaked. It was evident that there was a large difference between the number of publications in provinces/metropolitan cities/regions on CHT. Beijing, Sichuan University, Oncology, and Guo Jun from Beijing are the most prolific and influential region, institute, department, and author. When comparing research achievements to the next productive authors based on the CJAL score, only Dr Jun has a medium effect of dominance (=0.60). On the basis of their consecutive growth in citations over the past 4 years, 20 T100ICBM articles were recommended for readers.

CONCLUSION

The field of ICBM is growing rapidly, and Beijing and Sichuan University are taking the lead in CHT. Furthermore, the study provides references for worth-reading articles using the temporal heatmap. Future research hot spots may focus on these 4 themes of immunotherapy, melanoma, metastatic melanoma, regulatory T cells, cells, and activation, which may pave the way for additional study.

Psychological Skills Training for Athletes in Sports: Web of Science Bibliometric Analysis

Psychological Skill Training (PST) for optimal performance in sports has received extensive attention from athletes, coaches, and experts, and numerous studies have been conducted, but despite this interest, it has not been the subject of any bibliographic analysis. The analysis covered 405 articles and reviews that were located in the Thomson Reuters Web of Science (Core CollectionTM) between 1992 and 2021. These papers were published by 1048 authors from 543 different universities across 54 countries in 107 different journals. The fundamental bibliometric calculations and co-word networks were completed. As a result, the following thematic elements were grouped into four clusters: (1) PST for stress, mental toughness, and coping, (2) PST for anxiety, motivation, self-confidence, and self-efficacy, (3) PST for flow and mindfulness, and (4) PST for emotions. From the results of this study, it was confirmed that the topic of PST is converging toward the best performance, with various approaches, such as stress management, anxiety control, and coping as techniques for PST. Furthermore, mindfulness and positive psychology studies emphasize athletes' quality of life, so coaches and experts should pay more attention to improving athletes' quality of life in future research.

Research trends on the relationship between gut microbiota and colorectal cancer: A bibliometric analysis

Background

Colorectal cancer (CRC)is the third most common cancer in the world and the second leading cause of cancer-related deaths, and over the past two decades, many of these researchers have provided a substantial amount of important information on the role of gut microbes in the development and progression of CRC. A causal relationship between the presence of specific microorganisms and CRC development has also been validated. Although a large number of papers related to this area have been published, no bibliometric study has been conducted to review the current state of research in this area and to highlight the research trends and hotspots in this area. This study aims to analyze the current status and future research trends of gut microbiota and CRC through bibliometric analysis.

Methods

Publications from 2001 to 2022 were retrieved from the Web of Science Core Collection database and screened according to inclusion criteria. VOSviewer and CiteSpace software were used to visualize the research trends in this field, including the analysis of title, country, institution, author, number of publications, year of publication, number of citations, journal, and H-index.

Results

A total of 863 studies were eventually identified, and the articles retrieved were cited an average of 44.85 times each. The number of publications on this topic has been increased steadily since 2011. China and the USA have made the largest contribution in the field. FRONTIERS IN MICROBIOLOGY is the top productive journal with 26 papers, and Gut journal has the highest average citation (167.23). Shanghai Jiao Tong University is the most contributive institution. Professor Yu J, Sung, Joseph J. Y and Fang JY are the most productive authors in this field. Keyword co-occurrence analysis showed that the terms of "Gut Microbiota", "Colorectal Cancer", "Inflammation", "Probiotic" and "Fusobacterium Nucleatum" were the most frequent, which revealed the research hotpots and trends in this field.

Conclusions

There has been a growing number of publications over the past two decades according to the global trends. China and the USA still maintained the leading position in this field. However, collaboration between institutions needs to be strengthened. It's commended to pay attention to the latest hotspots, such as "F. nucleatum" and "probiotics". This bibliometric analysis evaluates the scope and trends of gut microbiota and CRC, providing a useful perspective on current research and future directions for studying the link between the gut microbiota and CRC.

The status and trends of mitochondrial dynamics research: A global bibliometric and visualized analysis

BACKGROUND

Mitochondria are remarkably dynamic organelles encapsulated by bilayer membranes. The dynamic properties of mitochondria are critical for energy production.

AIMS

The aim of our study is to investigate the global status and trends of mitochondrial dynamics research and predict popular topics and directions in the field.

METHODS

Publications related to the studies of mitochondrial dynamics from 2002 to 2021 were retrieved from Web of Science database. A total of 4,576 publications were included. Bibliometric analysis was conducted by visualization of similarities viewer and GraphPadPrism 5 software.

RESULTS

There is an increasing trend of mitochondrial dynamics research during the last 20 years. The cumulative number of publications about mitochondrial dynamics research followed the logistic growth model [Formula: see text]. The USA made the highest contributions to the global research. The journal Biochimica et Biophysica Acta (BBA)-Molecular Cell Research had the largest publication numbers. Case Western Reserve University is the most contributive institution. The main research orientation and funding agency were cell biology and HHS. All keywords related studies could be divided into three clusters: "Related disease research", "Mechanism research" and "Cell metabolism research".

CONCLUSIONS

Attention should be drawn to the latest popular research and more efforts will be put into mechanistic research, which may inspire new clinical treatments for the associated diseases.

Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

BACKGROUND

We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT.

METHODS

Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords.

RESULTS

We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs.

CONCLUSION

Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

Thematic analysis of articles on artificial intelligence with spine trauma, vertebral metastasis, and osteoporosis using chord diagrams: A systematic review and meta-analysis

BACKGROUND

Spine trauma, vertebral metastases, and osteoporosis (SVO) can result in serious health problems. If the diagnosis of SVO is delayed, the prognosis may be deteriorated. The use of artificial intelligence (AI) is an essential method for minimizing the diagnostic errors associated with SVO. research achievements (RAs) of SVO on AI are required as a result of the greatest number of studies on AI solutions reported. The study aimed to: classify article themes using visualizations, illustrate the characteristics of SVO on AI recently, compare RAs of SVO on AI between entities (e.g., countries, institutes, departments, and authors), and determine whether the mean citations of keywords can be used to predict article citations.

METHODS

A total of 31 articles from SVO on AI (denoted by T31SVOAI) have been found in Web of Science since 2018. The dominant entities were analyzed using the CJAL score and the Y-index. Five visualizations were applied to report: the themes of T31SVOAI and their RAs in comparison for article entities and verification of the hypothesis that the mean citations of keywords can predict article citations, including: network diagrams, chord diagrams, dot plots, a Kano diagram, and radar plots.

RESULTS

There were five themes classified (osteoporosis, personalized medicine, fracture, deformity, and cervical spine) by a chord diagram. The dominant entities with the highest CJAL scores were the United States (22.05), the University of Pennsylvania (5.72), Radiology (6.12), and Nithin Kolanu (Australia) (9.88). The majority of articles were published in Bone, J. Bone Miner. Res., and Arch. Osteoporos., with an equal count (=3). There was a significant correlation between the number of article citations and the number of weighted keywords (F = 392.05; P < .0001).

CONCLUSION

A breakthrough was achieved by displaying the characteristics of T31SVOAI using the CJAL score, the Y-index, and the chord diagram. Weighted keywords can be used to predict article citations. The five visualizations employed in this study may be used in future bibliographical studies.

The 100 most cited articles have fewer citations than other bibliometric articles: A pairwise comparison using a temporal bubble graph

BACKGROUND

More than 400 articles with the title of 100 top-cited articles (Top100) have been published in PubMed. It is unknown whether their citations are fewer (or more) than those found in other bibliometric studies (Nontop100). After determining article themes using coword analysis, a temporal bubble graph (TBG) was used to verify the hypothesis that the Top100 had fewer citations than the Nontop100.

METHODS

Using the Web of Science core collection, the top 50 most cited articles were compiled by Top100 and Nontop100, respectively, based on the research area of biomedicine and bibliometrics only. Coword analysis was used to extract themes. The study results were displayed using 6 different visualizations, including charts with bars, pyramids, forests, clusters, chords, and bubbles. Mean citations were compared between Top100 and Nontop100 using the bootstrapping method.

RESULTS

There were 18 citations in total for the 2 sets of the 50 most cited articles (range 1-134; 5 and 26.5 for Top100 and Nontop100, respectively). A significant difference in mean citations was observed between the 2 groups of Top100 and Nontop100 based on the bootstrapping method (3, 95% confidence interval: [1.18, 4.82]; 26.5, 95% confidence interval: [23.82, 29.18], P < .001). The 11 themes were clustered using coword analysis and applied to a TBG, which is composed of 4 dimensions: themes, years, citations and groups of articles. Among the 2 groups, the majority of articles were published in the journal of Medicine (Baltimore), with 9 and 7, respectively.

CONCLUSION

Eleven themes were identified as a result of this study. In addition, it reveals distinct differences between the 2 groups of Top100 and Nontop100, with the former containing more recently published articles and the latter containing more citations for articles. Clinical and research clinicians and researchers can use bibliometric analysis to appraise published literature and to understand the scientific landmark using TBG in bibliometrics.

Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model

The unprecedented development of information and communication technologies has opened up immense possibilities in the field of health care. Mobile health (mHealth) is gaining increasing attention as an important technology for solving health-related problems. Although a high rate of smartphone usage among young people in Japan has been identified, smartphone usage for health management is not high. As Japanese youth are important potential users of mHealth, it is necessary to explore theories that influence the behavioral intention of Japanese youth to adopt mHealth. This study conducted a questionnaire survey in a Japanese university and collected 233 valuable responses. This study was adapted and extended from the unified theory of acceptance and use of technology (UTAUT) model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention. Structural equation modeling was used for hypothesis testing. We found that trust, performance expectancy, and effort expectancy directly influenced the behavioral intention to use mHealth. Health consciousness and social influence indirectly influence behavioral intention through trust and performance expectancy. Facilitation conditions indirectly influenced behavioral intention through effort expectancy. This study makes a vital theoretical contribution to policymakers and product developers for the further diffusion of mHealth among young people in Japan.

A comparison of 3 productive authors' research domains based on sources from articles, cited references and citing articles using social network analysis

BACKGROUND

An individual's research domain (RD) can be determined from objective publication data (e.g., medical subject headings and Medical Subject Headings (MeSH) terms) by performing social network analysis. Bibliographic coupling (such as cocitation) is a similarity metric that relies on citation analysis to determine the similarity in RD between 2 articles. This study compared RD consistency between articles as well as their cited references and citing articles (ARCs).

METHODS

A total of 1388 abstracts were downloaded from PubMed and authored by 3 productive authors. Based on the top 3 clusters in social network analysis, similarity in RD was observed by comparing their consistency using the major MeSH terms in author articles, cited references and citing articles (ARC). Impact beam plots with La indices were drawn and compared for each of the 3 authors.

RESULTS

Sung-Ho Jang (South Korea), Chia-Hung Kao (Taiwan), and Chin-Hsiao Tseng (Taiwan) published 445, 780, and 163 articles, respectively. Dr Jang's RD is physiology, and Dr Kao and Dr Tseng's RDs are epidemiology. We confirmed the consistency of the RD terms by comparing the major MeSH terms in the ARC. Their La indexes were 5, 5, and 6, where a higher value indicates more extraordinary research achievement.

CONCLUSION

RD consistency was confirmed by comparing the main MeSH terms in ARC. The 3 approaches of RD determination (based on author articles, the La index, and the impact beam plots) were recommended for bibliographical studies in the future.

Citation analysis of the 100 top-cited articles on the topic of hidradenitis suppurativa since 2013 using Sankey diagrams: Bibliometric analysis

BACKGROUND

Hidradenitis suppurativa (HS) is a chronic, inflammatory and debilitating dermatosis characterized by painful nodules, sinus tracts and abscesses in apocrine gland-bearing areas that predominantly affect women worldwide. New therapeutic interventions based on the clinical manifestations of patients have recently been introduced in numerous articles. However, which countries, journals, subject categories, and articles have the ultimate influence remain unknown. This study aimed to display influential entities in 100 top-cited HS-related articles (T100HS) and investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations.

METHODS

T100HS data were extracted from PubMed since 2013. Subject categories were classified by MeSH terms using social network analysis. Sankey diagrams were applied to highlight the top 10 influential entities in T100HS from the three aspects of publication, citations, and the composited score using the hT index. The difference in article citations across subject categories and the predictive power of MeSH terms on article citations in T100HS were examined using one-way analysis of variance and regression analysis.

RESULTS

The top three countries (the US, Italy, and Spain) accounts for 54% of the T100HS. The T100HS impact factor (IF) is 12.49 (IF = citations/100). Most articles were published in J Am Acad Dermatol (15%; IF = 18.07). Eight subject categories were used. The "methods" was the most frequent MeSH term, followed by "surgery" and "therapeutic use". Saunte et al, from Roskilde Hospital, Denmark, had 149 citations in PubMed for the most cited articles. Sankey diagrams were used to depict the network characteristics of the T100HS. Article citations did not differ by subject category (F(7, 92) = 1.97, P = .067). MeSH terms were evident in the number of article citations predicted (F(1, 98) = 129.1106; P < .001).

CONCLUSION

We achieved a breakthrough by displaying the characteristics of the T100HS network on the Sankey diagrams. MeSH terms may be used to classify articles into subject categories and predict T100HS citations. Future studies can apply the Sankey diagram to the bibliometrics of the 100 most-cited articles.

Comparing the similarity and differences in MeSH terms associated with spine-specific journals using the forest plot: A bibliometric analysis

BACKGROUND

A common concern in the literature is the comparison of the similarities and differences between research journals, as well as the types of research they publish. At present, there are no clear methodologies that can be applied to a given article of interest. When authors use an effective and efficient method to locate journals in similar fields, they benefit greatly. By using the forest plot and major medical subject headings (MeSH terms) of Spine (Phila Pa 1976) compared to Spine J, this study: displays relatively similar journals to the target journal online and identifies the effect of the similarity odds ratio of Spine (Phila Pa 1976) compared to Spine J.

METHODS

From the PubMed library, we downloaded 1000 of the most recent top 20 most similar articles related to Spine (Phila Pa 1976) and then plotted the clusters of related journals using social network analysis (SNA). The forest plot was used to compare the differences in MeSH terms for 2 journals (Spine (Phila Pa 1976) and Spine J) based on odds ratios. The heterogeneity of the data was evaluated using the Q statistic and the I-square (I2) index.

RESULTS

This study shows that: the journals related to Spine (Phila Pa 1976) can easily be presented on a dashboard via Google Maps; 8 journal clusters were identified using SNA; the 3 most frequently searched MeSH terms are surgery, diagnostic imaging, and methods; and the odds ratios of MeSH terms only show significant differences with the keyword "surgery" between Spine (Phila Pa 1976) and Spine J with homogeneity at I2 = 17.7% (P = .27).

CONCLUSIONS

The SNA and forest plot provide a detailed overview of the inter-journal relationships and the target journal using MeSH terms. Based on the findings of this research, readers are provided with knowledge and concept diagrams that can be used in future submissions to related journals.

Global trends and hotspots in research on extended reality in sports: A bibliometric analysis from 2000 to 2021

Objective

Extended reality technologies (e.g. virtual reality (VR), augmented reality (AR) and mixed reality (MR)) are gaining popularity in sports owing to their unique advantages. This study aims to analyse the progress of the application of extended reality technology in sports and reveal its cooperative features, research hotspots and development trends.

Methods

We searched the literature in the Web of Science Core Collection (WoSCC) database within the period 2000 to 2021 and conducted a bibliometric analysis. The analysis methods included statistical, co-occurrence, hierarchical clustering and social network analyses.

Results

A total of 340 articles were gathered. The literature related to its research showed an increasing trend over time. The paper collaboration rate was 90.88% (309/340 papers), and the degree of author collaboration was 3.96 (1345/340). VR was found to be the most productive journal, and Queen's University Belfast was the most productive institution. The United States, China and the United Kingdom were the three main contributors to the field. The foundational themes in sports extended reality research were (i) sports games and extended reality systems, (ii) virtual simulation devices and artificial intelligence, (iii) sports training and performance and (iv) age-appropriate physical activity, sports rehabilitation and physical education.

Conclusion

The level of author collaboration was low, but the degree of author collaboration is largely on the rise. The closeness of the collaboration between institutions and countries was also low. In addition, the subject of sport extended reality is relatively fragmented. Therefore, more research is needed to strengthen it in the future.

Trend and prediction of citations on the topic of neuromuscular junctions in 100 top-cited articles since 2001 using a temporal bar graph: A bibliometric analysis

BACKGROUND

A neuromuscular junction (NMJ) (or myoneural junction) is a chemical synapse between a motor neuron (MN) and a muscle fiber. Although numerous articles have been published, no such analyses on trend or prediction of citations in NMJ were characterized using the temporal bar graph (TBG). This study is to identify the most dominant entities in the 100 top-cited articles in NMJ (T100MNJ for short) since 2001; to verify the improved TBG that is viable for trend analysis; and to investigate whether medical subject headings (MeSH terms) can be used to predict article citations.

METHODS

We downloaded T100MNJ from the PubMed database by searching the string ("NMJ" [MeSH Major Topic] AND ("2001" [Date - Modification]: "2021" [Date - Modification])) and matching citations to each article. Cluster analysis of citations was performed to select the most cited entities (e.g., authors, research institutes, affiliated countries, journals, and MeSH terms) in T100MNJ using social network analysis. The trend analysis was displayed using TBG with two major features of burst spot and trend development. Next, we examined the MeSH prediction effect on article citations using its correlation coefficients (CC) when the mean citations in MeSH terms were collected in 100 top-cited articles related to NMJ (T100NMJs).

RESULTS

The most dominant entities (i.e., country, journal, MesH term, and article in T100NMJ) in citations were the US (with impact factor [IF] = 142.2 = 10237/72), neuron (with IF = 151.3 = 3630/24), metabolism (with IF = 133.02), and article authored by Wagh et al from Germany in 2006 (with 342 citing articles). The improved TBG was demonstrated to highlight the citation evolution using burst spots, trend development, and line-chart plots. MeSH terms were evident in the prediction power on the number of article citations (CC = 0.40, t = 4.34).

CONCLUSION

Two major breakthroughs were made by developing the improved TBG applied to bibliographical studies and the prediction of article citations using the impact factor of MeSH terms in T100NMJ. These visualizations of improved TBG and scatter plots in trend, and prediction analyses are recommended for future academic pursuits and applications in other disciplines.

Using the Sankey diagram to visualize article features on the topics of whole-exome sequencing (WES) and whole-genome sequencing (WGS) since 2012: Bibliometric analysis

BACKGROUND

Sequencing technologies, such as whole-exome sequencing (WES) and whole-genome sequencing (WGS), have been increasingly applied to medical research in recent years. Which countries, journals, and institutes (called entities) contributed most to the fields (WES/WGS) remains unknown. Temporal bar graphs (TBGs) are frequently used in trend analysis of publications. However, how to draw the TBG on the Sankey diagram is not well understood in bibliometrics. We thus aimed to investigate the evolution of article entities in the WES/WGS fields using publication-based TBGs and compare the individual research achievements (IRAs) among entities.

METHODS

A total of 3599 abstracts downloaded from icite analysis were matched to entities, including article identity numbers, citations, publication years, journals, affiliated countries/regions of origin, and medical subject headings (MeSH terms) in PubMed on March 12, 2022. The relative citation ratio (RCR) was extracted from icite analysis to compute the hT index (denoting the IRA, taking both publications and citations into account) for each entity in the years between 2012 and 2021. Three types of visualizations were applied to display the trends of publications (e.g., choropleth maps and the enhanced TBGs) and IRAs (e.g., the flowchart on the Sankey diagram) for article entities in WES/WGS.

RESULTS

We observed that the 3 countries (the US, China, and the UK) occupied most articles in the WES/WGS fields since 2012, the 3 entities (i.e., top 5 journals, research institutes, and MeSH terms) were demonstrated on the enhanced TBGs, the top 2 MeSH terms were genetics and methods in WES and WGS, and the IRAs of 6 article entities with their hT-indices were succinctly and simultaneously displayed on a single Sankey diagram that was never launched in bibliographical studies.

CONCLUSION

The number of WES/WGS-related articles has dramatically increased since 2017. TBGs, particularly with hTs on the Sankey, are recommended for research on a topic (or in a discipline) to compare trends of publications and IRAs for entities in future bibliographical studies.

Citation analysis of the 100 top-cited articles on discectomy via endoscopy since 2011 using alluvial diagrams: bibliometric analysis

Background

Percutaneous endoscopic lumbar discectomy (PELD) is synonymous with percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID). PEID has gained increasing recognition for its small incision, quick recovery, short hospital stay, and equivalent clinical outcome to open surgery. Numerous articles related to PEID have been published in the literature. However, which countries, journals, subject categories, and articles have ultimate influence remains unknown. The study aimed to (1) display influential entities in 100 top-cited PEID-related articles (T100PEID) on the alluvial diagram and (2) investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations.

Methods

T100PEID data can be found since 2011 in the PubMed and Web of Science (WOS) databases. Using alluvial diagrams, citation analysis was conducted to compare the dominant entities. We used social network analysis (SNA) to classify MeSH terms and research areas extracted from PubMed and WOS. The difference in article citations across subject categories and the predictive power of MeSH terms on article citations in T100 PEID were examined using one-way analysis of variance (ANOVA) and regression analysis.

Results

A total of 81% of T100PEID is occupied by the top three countries (the US, China, and South Korea). There was an overall T100PEID impact factor of 41.3 (IF = citations/100). Articles were published in Spine (Phila Pa 1976) (23%; IF = 41.3). Six subject categories were classified using the SNA. The most cited article authored by D Scott Kreiner from Ahwatukee Sports and Spine in the US state of Phoenix had 123 citations in PubMed. The network characteristics of T100PEID are displayed on the alluvial diagram. No difference was found in article citations among subject categories (F = 0.813, p = 0.543). The most frequently occurring MeSH term was surgery. MeSH terms were evident in the prediction power of the number of article citations (F = 15.21; p < 0 .001).

Conclusion

We achieved a breakthrough by displaying the T100PEID network characteristics on the alluvial plateau. The MeSH terms can be used to classify article subject categories and predict T100PEID citations. The alluvial diagram can be applied to bibliometrics on 100 top-cited articles in future studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00782-0.

An Alluvial diagram was drawn to display the network characteristics of T100PEID, which is novel and modern in the literature.

The method of drawing the Alluvial demonstrated in detail with documents in supplemental digital contents can be applied to make bibliometric studies brief, concise, and powerful.

The impact beam plot (IBP) is an additional visualization introduced in this study. The online IBP was demonstrated and worthy of future similar studies to highlight the most influential articles with a glance at a picture.

Using Sankey diagrams to explore the trend of article citations in the field of bladder cancer: Research achievements in China higher than those in the United States

BACKGROUND

Urology authors are required to evaluate research achievements (RAs) in the field of bladder cancer (BC). However, no such bibliometric indices were appropriately applied to quantify the contributions to BC in research. In this study, we examined 3 questions: whether RAs in China are higher than those in the United States, how the Sankey-based temporal bar graph (STBG) may be applied to the analysis of the trend of article citations in the BC field, and what subthemes were reflected in China's and the United States' proportional counts in BC articles.

METHODS

Using the PubMed search engine to download data, we conducted citation analyses of BC articles authored by urology scholars since 2012. A total of 9885 articles were collected and analyzed using the relative citations ratios (RCRs) and the STBG. The 3 research goals were verified using the RCRs, the STBG, and medical subject headings (MesH terms). The choropleth map and the forest plot were used to 1 highlight the geographical distributions of publications and RCRs for countries/regions and 2 compare the differences in themes (denoted by major MeSH terms on proportional counts using social network analysis to cluster topics) between China and the United States.

RESULTS

There was a significant rise over the years in RCRs within the 9885 BC articles. We found that the RCRs in China were substantially higher than those in the United States since 2017, the STBG successfully explored the RCR trend of BC articles and was easier and simpler than the traditional line charts, area plots, and TBGs, and the subtheme of genetics in China has a significantly higher proportion of articles than the United States. The most productive and influential countries/regions (denoted by RCRs) were {Japan, Germany, and Italy} and {Japan, Germany, New York}, respectively, when the US states and provinces/metropolitan cities/areas in China were separately compared to other countries/regions.

CONCLUSIONS

With an overall increase in publications and RCRs on BC articles, research contributions assessed by the RCRs and visualized by the STBGs are suggested for use in future bibliographical studies.

Using the forest plot to compare citation achievements in bibliographic and meta-analysis studies since 2011 using data on PubMed Central: A retrospective study

BACKGROUND

We saw a steady increase in the number of bibliographic studies published over the years. The reason for this rise is attributed to the better accessibility of bibliographic data and software packages that specialize in bibliographic analyses. Any difference in citation achievements between bibliographic and meta-analysis studies observed so far need to be verified. In this study, we aimed to identify the frequently observed MeSH terms in these 2 types of study and investigate whether the highlighted MeSH terms are strongly associated with one of the study types.

METHODS

By searching the PubMed Central database, 5121 articles relevant to bibliometric and meta-analysis studies were downloaded since 2011. Social network analysis was applied to highlight the major MeSH terms of quantitative and statistical methods in these 2 types of studies. MeSH terms were then individually tested for any differences in event counts over the years between study types using odds of 95% confidence intervals for comparison.

RESULTS

In these 2 studies, we found that the most productive countries were the United States (19.9%), followed by the United Kingdom (8.8%) and China (8.7%); the most number of articles were published in PLoS One (2.9%), Stat Med (2.5%), and Res Synth (2.4%); and the most frequently observed MeSH terms were statistics and numerical data in bibliographic studies and methods in meta-analysis. Differences were found when compared to the event counts and the citation achievements in these 2 study types.

CONCLUSION

The breakthrough was made by developing a dashboard using forest plots to display the difference in event counts. The visualization of the observed MeSH terms could be replicated for future academic pursuits and applications in other disciplines using the odds of 95% confidence intervals.

A VOSviewer-Based Bibliometric Analysis of Prescription Refills

Purpose

Prescription refills are long-term prescriptions for chronic patients in stable status, which varies from country to country. A well-established prescription refill system is beneficial for chronic patients’ medication management and facilitates the efficacy of clinical care. Therefore, we carried out a bibliometric analysis to examine the development of this field.

Summary

Publications on prescription refills from 1970 to 2021 were collected in the Web of Science Core Collection (WoSCC). Search strategy TS = “prescri* refill*” OR “medi* refill*” OR “repeat prescri*” OR “repeat dispens*” OR TI = refill* was used for search. VOSviewer was applied to visualize the bibliometric analysis. A total of 319 publications were found in WoSCC. Study attention on prescription refills has shown a steady rise but is still low in recent years. The United States was the most productive country, which had the highest total citations, average citations per publication, and the highest H-index, and participated in international collaboration most frequently. The University of California system was the most productive institution. The U.S. Department of Veterans Affairs was the institution with the most citations, most average citation, and highest H-index. Sundell was the most productive author, and Steiner J. F. was the most influential author. “Adherence,” “medication,” and “therapy” were the most prominent keywords.

Conclusion

Publications on prescription refills have increased rapidly and continue to grow. The United States had the leading position in the area. It is recommended to pay closer attention to the latest hotspots, such as “Opioids,” “Surgery,” “Differentiated care,” and “HIV.”

Research disciplinary interactions on scientific collaboration network in photocatalytic hydrogen evolution: Characteristics and dynamics

Interdisciplinary scientific collaboration promotes the innovative development of scientific research. Photocatalytic hydrogen evolution (PHE) is a typical interdisciplinary subject. This study aims to explore the characteristics of discipline interaction and the temporal evolution in the field. Bibliometric analysis could be used to understand the stage of research in a particular subject. In this work, the publications on the topic in Web of Science (WoS) platform from 1999 to 2020 were selected. On the basis of social network theory, the characteristics of interdisciplinary were revealed from three perspectives. First, the disciplinary interaction network is constructed through disciplinary co-occurrence to detect the characteristics of interaction structure among different disciplines. Then the node centrality index is employed to explore the influence of disciplines in the interactive network by using network centrality analysis. Moreover, the dynamic of discipline interaction evolution is studied using blockmodeling analysis. In the field of PHE, the number of disciplines and the intensity of interaction among different subjects gradually increased in the past 20 years. Chemistry and Material Sciences are the core discipline, and they play an important role in the network. The whole network is divided into different discipline groups. The scale of the discipline group is becoming large, and the disciplinary interaction is becoming more complex. The obtained results are helpful for guiding scholars to carry out interdisciplinary interaction. The methods of detecting interdisciplinary interactive relationship could provide paths for interdisciplinary research in other fields.

Bibliometric and Visual Analysis on Metabolomics in Coronary Artery Disease Research

Background

Metabolomics has immense research value in coronary artery disease and has drawn increasing attention over the past decades. Many articles have been published in this field, which may challenge researchers aiming to investigate all the available information. However, bibliometrics can provide deep insights into this research field.

Objective

We aimed to qualitatively and quantitatively study metabolomics and coronary artery disease research, visually analyse the development status, trends, research hotspots, and frontiers of this field, and provide a reference for research on coronary artery disease.

Methods

Articles were acquired from the Web of Science Core Collection. VOSviewer and CiteSpace software were used to analyse publication growth, country/region, institution, journal distribution, author, reference, and keywords, and detected the keywords with strong citation burstness to identify emerging topics.

Results

A total of 1121 references were obtained, and the annual number of publications increased over the past 16 years. Metabolomics research has shown a gradual upward trend in coronary artery disease. The United States of America and China ranked at the top in terms of percentage of articles. The institution with the highest number of research publications in this field was Harvard University, followed by the University of California System and Brigham Women's Hospital. The most frequently cited authors included Hazen SL, Tang WH, and Wang ZN. Ala-Korpela M was the most productive author, followed by Clish CB and Adamski J. The journal with the most publications in this field was Scientific Reports, followed by PLoS One and the Journal of Proteome Research. The keywords used at a high frequency were "risk," "biomarkers," "insulin resistance," and "atherosclerosis." Burst detection analysis of top keywords showed that "microbiota," "tryptophan," and "diabetes" are the current research frontiers in this field.

Conclusion

This study provides useful information for acquiring knowledge on metabolomics and coronary artery diseases. Metabolomics research has shown a gradual upward trend in coronary artery disease studies over the past 16 years. Research on tryptophan metabolism regulated by intestinal flora will become an emerging academic trend in this field, which can offer guidance for more extensive and in-depth studies in the future.

Suggestions to the article: demonstrating the ascendancy of COVID-19 research using acronyms

The article published on 16 May 2021 is interesting and impressive, particularly on the Figure displaying several acronyms in trend. Although the most popular eight acronyms in 2019 and 2020 are individually highlighted and labeled, how to determine the points in 2019 and 2020 is required for classifications. The analysis for the evolution of keywords is common and necessary in the bibliographic study. None of the studies addressed the determination of the bursting point for a given keyword over the years. We aim to illustrate the way to determine the inflection point on a given ogive curve and apply the temporal bar graph (TBG) to interpret the trend of a specific keyword (or acronym). The prediction model is based on item response theory, commonly used in educational and psychometric fields. The eight acronyms presented in the previous study were demonstrated using the TBG. We found that the TBG includes more valuable information than the traditional trend charts. The inflection point denoted the topic burst indicates the turning point suddenly from increasing to decreasing. The TBG combined with the inflection point to represent the trend of a given keyword can make the data in trend easier and clearer to understand than any graph used in ever before bibliometric analyses.

Classification and citation analysis of the 100 top-cited articles on adult spinal deformity since 2011: A bibliometric analysis

BACKGROUND

Studies of the 100 most-cited articles are reported for many subjects. However, none has analyzed the article characteristics associated with high citation frequency. This study aims to (1) graphically depict characteristics of the 100 top-cited articles addressing adult spinal deformity (ASD), (2) diagram the association between articles according to subject and major topic medical subject headings (MeSHs), and (3) investigate whether major topic MeSH correlates with article citation frequency.

METHODS

The 100 top-cited ASD publications since 2011 were retrieved using a PubMed Central search on May 6, 2020. Using titles and abstracts, eight subject categories were identified: surgery, conservative treatment, normal values in spinopelvic alignment, review, cervical alignment, classification, compensatory mechanism, and spine-hip relationship. Sankey diagrams were used to organize the information. Network analysis was performed according to article subject and major topic MeSHs. Pearson's r was used to determine whether the weighted number of citations correlates with major topic MeSHs and the number of citations.

RESULTS

The average number of citations per article was 34.8 (range, 19-156). The most represented country was USA (n = 51). The most productive and highly cited journal was Spine (Phila Pa 1976) (n = 34; average, 38.2 citations per article). The most frequent subject categories and major topic MeSHs were "surgery" (n = 53) and "scoliosis" (weighted count, 9.8), while articles with the subject "compensatory" had the highest average number of citations (64.7). The most highly cited article, by Dr. F. Schwab in 2012, had 156 citations. Network analysis revealed the relationships between these articles according to major topic MeSHs. The weighted number of citations according to major topic MeSHs correlated significantly with article citation frequency (Pearson's r, 0.57; p < 0.001).

CONCLUSION

Multiple characteristics of the 100 top-cited ASD articles are presented in diagrams to guide evidence-based clinical decision-making in ASD.

Visualizing the features of inflection point shown on a temporal bar graph using the data of COVID-19 pandemic

BACKGROUND

Exponential-like infection growth leading to peaks (denoted by inflection points [IP] or turning points) is usually the hallmark of infectious disease outbreaks, including coronaviruses. To determine the IPs of the novel coronavirus (COVID-19), we applied the item response theory model to detect phase transitions for each country/region and characterize the IP feature on the temporal bar graph (TBG).

METHODS

The IP (using the item difficulty parameter to locate) was verified by the differential equation in calculus and interpreted by the TBG with 2 virtual and real empirical data (i.e., from Collatz conjecture and COVID-19 pandemic in 2020). Comparisons of IPs, R2, and burst strength [BS = ln() denoted by the infection number at IP(Nip) and the item slope parameter(a) in item response theory were made for countries/regions and continents on the choropleth map and the forest plot.

RESULTS

We found that the evolution of COVID-19 on the TBG makes the data clear and easy to understand, the shorter IP (=53.9) was in China and the longest (=247.3) was in Europe, and the highest R2 (as the variance explained by the model) was in the US, with a mean R2 of 0.98. We successfully estimated the IPs for countries/regions on COVID-19 in 2020 and presented them on the TBG.

CONCLUSION

Temporal visualization is recommended for researchers in future relevant studies (e.g., the evolution of keywords in a specific discipline) and is not merely limited to the IP search in COVID-19 pandemics as we did in this study.

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis

BACKGROUND

Smartphones have become an integral part of our lives with unprecedented popularity and a diverse selection of apps. The continuous upgrading of information technology has also enabled smartphones to display great potential in the field of health care.

OBJECTIVE

We aimed to determine the future research direction of mobile health (mHealth) by analyzing its research trends and latest research hotspots.

METHODS

This study collected mHealth-related literature published between 2000 and 2020 from the Web of Science database. Descriptive statistics of publication trends of mHealth research were determined by analyzing the annual number of publications in the literature and annual number of publications by country. We constructed visualization network maps of country (or regional) collaborations and author-provided keyword co-occurrences, as well as overlay visualization maps of the average publication year of author-provided keywords to analyze the hotspots and research trends in mHealth research.

RESULTS

In total, 12,593 mHealth-related research papers published between 2000 and 2020 were found. The results showed an exponential growth trend in the number of annual publications in mHealth literature. JMIR mHealth and uHealth, the Journal of Medical Internet Research, and JMIR Research Protocols were the 3 top journals with respect to number of publications. The United States remained the leading contributor to the literature in this area (5294/12,593, 42.0%), well ahead of other countries and regions. Other countries and regions also showed a clear trend of annual increases in the number of mHealth publications. The 4 countries with the largest number of publications-the United States, the United Kingdom, Canada, and Australia-were found to cooperate more closely. The rest of the countries and regions showed a clear geographic pattern of cooperation. The keyword co-occurrence analysis of the top 100 authors demonstrated 5 clusters, namely, development of mHealth medical technology and its application to various diseases, use of mHealth technology to improve basic public health and health policy, mHealth self-health testing and management in daily life, adolescent use of mHealth, and mHealth in mental health. The research trends revealed a gradual shift in mHealth research from health policy and improving public health care to the development and social application of mHealth technologies.

CONCLUSIONS

To the best of our knowledge, the most current bibliometric analysis dates back to 2016. However, the number of mHealth research published between 2017 and 2020 exceeds the previous total. The results of this study shed light on the latest hotspots and trends in mHealth research. These findings provide a useful overview of the development of the field; they may also serve as a valuable reference and provide guidance for researchers in the digital health field.

Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years

Background

Citation analysis has been increasingly applied to assess the quantity and quality of scientific research in various fields worldwide. However, these analyses on spinal surgery do not provide visualization of results. This study aims (1) to evaluate the worldwide research citations and publications on spinal surgery and (2) to provide visual representations using Kano diagrams onto the research analysis for spinal surgeons and researchers.

Methods

Article abstracts published between 2007 and 2018 were downloaded from PubMed Central (PMC) in 5 journals, including Spine, European Spine Journal, The Spine Journal, Journal of Neurosurgery: Spine, and Journal of Spinal Disorders and Techniques. The article types, affiliated countries, authors, and Medical subject headings (MeSH terms) were analyzed by the number of article citations using x-index. Choropleth maps and Kano diagrams were applied to present these results. The trends of MeSH terms over the years were plotted and analyzed.

Results

A total of 18,808 publications were extracted from the PMC database, and 17,245 were affiliated to countries/areas. The 12-year impact factor for the five spine journals is 5.758. We observed that (1) the largest number of articles on spinal surgery was from North America (6417, 37.21%). Spine earns the highest x-index (= 82.96). Comparative Study has the highest x-index (= 66.74) among all article types. (2) The United States performed exceptionally in x-indexes (= 56.86 and 44.5) on both analyses done on the total 18,808 and the top 100 most cited articles, respectively. The most influential author whose x-index reaches 15.11 was Simon Dagenais from the US. (3) The most cited MeSH term with an x-index of 23.05 was surgery based on the top 100 most cited articles. The most cited article (PMID = 18164449) was written by Dagenais and his colleagues in 2008. The most productive author was Michael G. Fehlings, whose x-index and the author's impact factor are 13.57(= √(13.16*14)) and 9.86(= 331.57/33.64), respectively.

Conclusions

There was a rapidly increasing scientific productivity in the field of spinal surgery in the past 12 years. The US has extraordinary contributions to the publications. Furthermore, China and Japan have increasing numbers of publications on spinal surgery. This study with Kano diagrams provides an insight into the research for spinal surgeons and researchers.

A Study of eHealth from the Perspective of Social Sciences

The field of social sciences has become increasingly important in eHealth. Patients currently engage more proactively with health services. This means that eHealth is linked to many different areas of Social Sciences. The main purpose of this research is to analyze the state-of-the-art research on eHealth from the perspective of social sciences. To this end, a bibliometric analysis was conducted using the Web of Science database. The main findings show the evolution of publications, the most influential countries, the most relevant journals and papers, and the importance of the different areas of knowledge. Although there are some studies on eHealth within social sciences, most of them focus on very specific aspects and do not develop a holistic analysis. Thus, this paper contributes to academia by analyzing the state-of-the-art of research, as well as identifying the most relevant trends and proposing future lines of research such as the potential of eHealth as a professional training instrument, development of predictive models in eHealth, analysis of the eHealth technology acceptance model (TAM), efficient integration of eHealth within public systems, efficient budget management, or improvement in the quality of service for patients.

Bibliometric Analysis and Methodological Review of Mobile Health Services and Applications in India

PURPOSE

The purpose of this research is to analyze the literature published on mobile health (mHealth) in the Indian context. It also reviews the most important research works and presents various methodologies adopted by the researchers in this domain.

DESIGN/METHODOLOGY/APPROACH

The SciVerse SCOPUS database was used for extracting the literature on mobile health. The study used articles published between January 2008 to 28^th June 2019. The keyword used is 'mHealth' and journal articles with studies or interventions carried out in India were selected for bibliometric analysis and methodological review.

FINDINGS

For the keyword search, a total of 7,874 documents have been extracted, of which only 158 have been considered for the analysis. There is an exponential increase in the number of publications from the year 2015 to 2019. The keywords used for representing their articles have been grouped as mobile health devices, gender and age groups, system and software, health and disease condition, management, evidence-based practices (outcome), methods, and importance of the study. The journal PLOS One (87) has the highest number of citations, followed by The Lancet (63). The bibliometric analysis of the literature revealed seven clusters classified as individual's individual's mobile health applications adoption characteristics, need for mobile health and its governance, mobile phone application with the internet of things based framework for healthcare monitoring, mobile health for primary healthcare systems, authentication and security protocol for mobile healthcare, development and experimentation of mobile health application, and development and mobile health for adherence support intervention.

ORIGINALITY/VALUE

The study contributes in analyzing the bibliometrics and provides a methodological review for the journal articles published on mobile health. Previous articles considered systematic analysis of the bibliometric for mHealth, and mobile technology but less adequately discussed specifically towards Indian context which this study has embraced.

Predicting article citations using data of 100 top-cited publications in the journal Medicine since 2011: A bibliometric analysis

BACKGROUND

Publications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations.

RESULTS

The citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients  = 0.49, t = 5.62).

CONCLUSION

The breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.

Integrating Unified Medical Language System and Kleinberg's Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder

Background

The treatment of post-traumatic stress disorder (PTSD) has long been a challenge because the symptoms of PTSD are multifaceted. PTSD is primarily treated with psychotherapy and medication, or a combination of psychotherapy and medication. The present study was designed to analyze the literature on medications for PTSD and explore high-frequency common drugs and low-frequency burst drugs by burst detection algorithm combined with Unified Medical Language System (UMLS) and provide references for developing new drugs for PTSD.

Methods

Publications related to medications for PTSD from 2010 to 2019 were identified through PubMed, Web of Science Core Collection, and BIOSIS Previews. SemRep and SemRep semantic result processing system were performed to extract the set of drug concepts with therapeutic relationship according to the semantic relationship of UMLS. Kleinberg’s burst detection algorithm was applied to calculate the burst weight index of drug concepts by a Java-based program. These concepts were sorted according to the frequency and the burst weight index.

Results

Four hundred and fifty-nine treatment-related drug concepts were extracted. The drug with the highest burst weight index was “Psilocybine”, a hallucinogen, which was more likely to be a hotspot for the pharmacotherapy of PTSD. The highest frequency concept was “prazosin”, which was more likely to be the focus of research in the medications for PTSD.

Conclusion

The present study assessed the medication-related literature on PTSD treatment, providing a framework of burst words detection-based method, a baseline of information for future research and the new attempt for the discovery of textual knowledge. The bibliometric analysis based on the burst detection algorithm combined with UMLS has shown certain feasibility in amplifying the microscopic changes of a specific research direction in a field, it can also be used in other aspects of disease and to explore the trends of various disciplines.

Global scientific research on social participation of older people from 2000 to 2019: A bibliometric analysis

Background

Social participation is an indicator of successful ageing and important determinant of health outcomes. As more studies have been conducted on social participation of older people, a comprehensive and quantitative analysis of the current literature will contribute to a better understanding of the main and novel issues and improve existing geriatric care services in this domain. However, limited bibliometric analysis was employed in this research field. Therefore, we conducted this study to investigate the research trend and quantitatively and comprehensively characterise the landscapes of publications on social participation of older people via bibliometric analysis methods.

Methods

Data were obtained from the Web of Science Core Collection in January 2020. CiteSpace 5.5.R2 and VOSviewer software packages were used to generate knowledge maps and analyse the publication outputs, countries/regions, institutions, journals, research hot spots and research frontiers.

Results

A total of 7,029 publications between 2000 and 2019 were retrieved, and the publication number per year continues to increase. The United States held a leading position in this research field, and Duke University was the most productive institution. Co‐cited reference cluster analysis and keyword co‐occurrence analysis showed that research hot spots contained factors of healthy ageing, quality of life, psychological problems and health status, especially dementia, function (including cognitive function) and frailty. Burst detection of keywords revealed that social participation, social support, instrumental activity, frailty and loneliness have been new research frontiers since 2015.

Conclusions

By analysing publications over the past 20 years, we found publication trends and characteristics in this field. These findings will hopefully provide new insight into the scientific landscapes and further directions in the study of social participation of older people.

Implications for Practice

Social participation is strongly associated with physical and psychological problems and the well‐being of older people. Related professionals, such as social workers, psychologists, nurses and many other health care practitioners, should raise widespread awareness and concern over research hot spots and frontiers on this topic to promote research knowledge translation and adoption into the practice of caring for older people.

Research trends on the relationship between Microbiota and Gastric Cancer: A Bibliometric Analysis from 2000 to 2019

Background: Hundreds of studies have found that the microbiota contributes to the development of gastric cancer in the past two decades. This study aimed to access the research trends of microbiota and gastric cancer.

Materials and Methods: Publications from January 1, 2000 to December 31, 2019 were retrieved from the Web of Science Core Collection database and screened according to inclusion criteria. Different kinds of software, SPSS21.0, HistCite, VOSviewer, CiteSpace, and the online bibliometric analysis platform were used to evaluate and visualize the results.

Results: A total of 196 publications were finally identified, and the annual number of publications showed an increasing trend. These publications were from 44 countries and the USA showed its dominant position in publication outputs, H-index, total citations, and international collaborations. The journal of Helicobacter was the most productive journal. Correa P and Peek RM published the most papers, and the most productive institution was Vanderbilt University. The keyword of “Helicobacter pylori” ranked first in research frontiers and appeared earlier, and the keyword of “microbiota” began to appear in the past 3 to 5 years.

Conclusion: The annual number of publications would continue to grow. Besides the traditional Helicobacter pylori related researches, future research hotspots will focus on microbiota and its mechanism of action.

Entrepreneurship and Innovation in Soccer: Web of Science Bibliometric Analysis

According to the existing literature, there is growing interest in the sports industry by individuals involved in entrepreneurship and innovation. However, no bibliometric analyses on the importance of and interest that these individuals have in the football industry have been conducted. A total of 220 articles and reviews retrieved from Thomson Reuters Web of Science (Core Collection™) between 1997 and 2019 were analysed. These articles were published in 169 different journals by 609 authors from 340 different institutions in 46 countries. The following basic bibliometric analyses and co-occurrence networks were carried out: co-authorship and co-words. As a result, four clusters that summarise the following four different thematic areas were found: (1) football, entrepreneurship and social development, (2) football, innovation and management, (3) football, efficiency and new technology, and (4) football, injuries and innovation in rehabilitation. A thematic analysis of the four clusters found was carried out. Finally, practical implications and future lines of research were presented.

The Most-Cited Authors Who Published Papers in JMIR mHealth and uHealth Using the Authorship-Weighted Scheme: Bibliometric Analysis

Background

Many previous papers have investigated most-cited articles or most productive authors in academics, but few have studied most-cited authors. Two challenges are faced in doing so, one of which is that some different authors will have the same name in the bibliometric data, and the second is that coauthors’ contributions are different in the article byline. No study has dealt with the matter of duplicate names in bibliometric data. Although betweenness centrality (BC) is one of the most popular degrees of density in social network analysis (SNA), few have applied the BC algorithm to interpret a network’s characteristics. A quantitative scheme must be used for calculating weighted author credits and then applying the metrics in comparison.

Objective

This study aimed to apply the BC algorithm to examine possible identical names in a network and report the most-cited authors for a journal related to international mobile health (mHealth) research.

Methods

We obtained 676 abstracts from Medline based on the keywords “JMIR mHealth and uHealth” (Journal) on June 30, 2018. The author names, countries/areas, and author-defined keywords were recorded. The BCs were then calculated for the following: (1) the most-cited authors displayed on Google Maps; (2) the geographical distribution of countries/areas for the first author; and (3) the keywords dispersed by BC and related to article topics in comparison on citation indices. Pajek software was used to yield the BC for each entity (or node). Bibliometric indices, including h-, g-, and x-indexes, the mean of core articles on g(Ag)=sum (citations on g-core/publications on g-core), and author impact factor (AIF), were applied.

Results

We found that the most-cited author was Sherif M Badawy (from the United States), who had published six articles on JMIR mHealth and uHealth with high bibliometric indices (h=3; AIF=8.47; x=4.68; Ag=5.26). We also found that the two countries with the highest BC were the United States and the United Kingdom and that the two keyword clusters of mHealth and telemedicine earned the highest indices in comparison to other counterparts. All visual representations were successfully displayed on Google Maps.

Conclusions

The most cited authors were selected using the authorship-weighted scheme (AWS), and the keywords of mHealth and telemedicine were more highly cited than other counterparts. The results on Google Maps are novel and unique as knowledge concept maps for understanding the feature of a journal. The research approaches used in this study (ie, BC and AWS) can be applied to other bibliometric analyses in the future.

The Emergence of Technology in Physical Education: A General Bibliometric Analysis with a Focus on Virtual and Augmented Reality

Technology has been gradually introduced into our society, and the field of education is no exception due to technology’s ability to improve the teaching–learning process. Furthermore, within the area of physical education (PE), its importance has been highlighted by the existence of specific apps for physical activity that can be used inside and outside the classroom to assess physical condition, as well as through the potential that virtual and augmented reality can have in such assessment. Therefore, the main objectives for this study were (1) to perform a bibliometric analysis of the articles published in the Web of Science (WoS) on technology in PE and (2) to analyze the articles published on augmented or virtual reality in PE found through this search. The results show that although studies on technology in PE (461 articles) have begun to consolidate over the last five years (there was a turning point in 2015), with the USA being the most influential country in this area, specific research on the use of augmented reality (AR) and virtual reality (VR) is still at a very early stage (22 articles with a small growth in 2017), with Spain being the most influential country; much more research is needed to achieve its consolidation.

Research trends of stem cells in ischemic stroke from 1999 to 2018: A bibliometric analysis

OBJECTIVE

Many studies have evaluated the safety and efficacy of stem cells as therapeutic agents for ischemic stroke. We aimed to quantitatively assess the research trends of stem cell therapy for ischemic stroke.

PATIENTS AND METHODS

We searched the Web of Science Core Collection to identify relevant publications between 1999 and 2018. We used HistCite to summarize the critical information, including yearly records, authors, countries/regions, and institutions. VOSviewer was applied to map the collaborations between studies. Based on the title and abstract of each publication, MeSH terms were obtained using Medical Text Indexer to demonstrate evolutions of topic hotspots.

RESULTS

From 1999-2018, there were a total of 3,741 publications exploring the prospect of stem cells in ischemic stroke. Annual publication outputs grew from six records to 366 records. Stroke was the most high-profile journal because of its ranking first on the top productive and co-cited journal lists. The United States of America and China were the two most contributive countries of stem-cell research of ischemic stroke. Researchers were supposed to follow studies from productive institutions because of their consistent and systematic investigations in this field. Neural stem cells and mesenchymal stem cells were the most recognized cells for clinical translation.

CONCLUSION

With the growth of publications concerning the role of stem cells in ischemic stroke treatment, bibliometrics helps researchers to get insights of academic collaborations, research trends, and hot topics in the study field.

Whether productive authors using the national health insurance database also achieve higher individual research metrics: A bibliometric study

BACKGROUND

Many researchers use the National Health Insurance Research Database (HIRD) to publish medical papers and gain exceptional outputs in academics. Whether they also obtain excellent citation metrics remains unclear.

METHODS

We searched the PubMed database (http://www.ncbi.nlm.nih.gov/pubmed) using the terms Taiwan and HIRD. We then downloaded 1997 articles published from 2012 to 2016. An authorship-weighted scheme (AWS) was applied to compute coauthor partial contributions from the article bylines. Both modified x-index and author impact factor (AIF) proved complementary to Hirsch's h-index for calculating individual research achievements (IRA). The metrics from 4684 authors were collected for comparison. Three hundred eligible authors with higher x-indexes were located and displayed on Google Maps dashboards. Ten separate clusters were identified using social network analysis (SNA) to highlight the research teams. The bootstrapping method was used to examine the differences in metrics among author clusters. The Kano model was applied to classify author IRAs into 3 parts.

RESULTS

The most productive author was Investigator#1 (Taichung City, Taiwan), who published 149 articles in 2015 and included 803 other members in his research teams. The Kano diagram results did not support his citation metrics beyond other clusters and individuals in IRAs.

CONCLUSION

The AWS-based bibliometric metrics make individual weighted research evaluations possible and available for comparison. The study results of productive authors using HIRD did not support the view that higher citation metrics exist in specific disciplines.

Understanding the Function Constitution and Influence Factors on Communication for the WeChat Official Account of Top Tertiary Hospitals in China: Cross-Sectional Study

Background

Widespread adoption and continued developments in mobile health care technologies have led to the improved accessibility and quality of medical services. In China, WeChat, an instant messaging and social networking app released by the company Tencent, has developed a specific type of user account called WeChat official account (WOA), which is now widely adopted by hospitals in China. It enables health care providers to connect with local citizens, allowing them to, among other actions, send regular updates through mass circulation. However, with the diversity in function provided by WOA, little is known about its major constitution as well as the influence factors on the WeChat communication index (WCI). The WCI has been widely used in social media impact ranking with various types of WeChat content to fully reflect the dissemination and coverage of tweets as well as the maturity and impact of WOA.

Objective

There are two typical WOAs available to users, namely, WeChat subscription account (WSSA) and WeChat service account (WSVA). The biggest difference between them is the frequency of messages transmitted. This study aimed to explore the function constitution of WSVA adopted by top tertiary hospitals in China and the major contributors of the WCI score.

Methods

A total of 681 top tertiary hospitals were selected from the Hospital Quality Monitoring System; the WOA of every top tertiary hospital was retrieved in the WeChat app. We divided core functional items of WSVAs using categorical principal component analysis. To elicit the factors that influenced the use of WSVA, quantile regression was employed to analyze the WCI score.

Results

From the 668 WOAs identified, adoption of WSVAs (543/668, 81.3%) was more than that of WSSAs (125/668, 18.7%). Functional items of WSVAs were categorized into four clusters: (1) hospital introduction, (2) medical services, (3) visiting assistants, and (4) others. With regard to the influence factors on the WCI, the impact of the activity index of WSVA and the total visiting number of outpatients and emergencies on WCI were statistically significant and positive in all quantiles. However, the year of certification, the type of hospital, the year of public hospital reform, and the number of beds merely affected the WCI at some quantiles.

Conclusions

Our findings are considered helpful to tertiary hospitals in developing in-depth functional items that improve patient experience. The tertiary hospitals should take full advantage of times of posting and provide high-quality tweets to meet the various needs of patients.