Exploring the evolution and characteristics of the ischool movement in china

This study examines the evolution of current interests and emerging characteristics in library and information science (LIS) from Chinese iSchools, including an analysis of the LIS landscape, space distribution, citation, emerging characteristics, and collaborations. This study considers a non-parametric approach to outline the structure of the iSchool movement in China, while clustering analysis helped us obtain information about the descriptions generated within unsupervised learning groups. It was found that Chinese iSchools play an intermediary role in the international development of Chinese LIS, which further promotes the dissemination and exchange of knowledge and international cooperation in LIS.</p

Co-word Analysis of Scientific Outputs in the Field of Bibliotherapy in Web of Science

Background and aim: Scientometric studies are one of the most efficient methods of scientific evaluation in a valid scientific database. Therefore, the aim of this study was to analyze the co-word analysis of scientific outputs in the field of bibliotherapy in the Web of Science (WoS). Materials and methods: This scientometric study was conducted using library methods and network analysis. The statistical population of this study included all documents indexed in the WoS with the subject of bibliotherapy from 1975 to 2020. Data were analyzed using Excel, Pajek, UCINET, Netdraw, and VOSviewer softwares. Findings: The results showed that the scientific outputs in the field of bibliotherapy had no appropriate growth rate, and the growth rate of the total scientific outputs in this field was 3%. The field of "psychology" was the most active one with the production of 49% of bibliotherapy studies. Based on the study of the co-word network in the field of bibliotherapy, six thematic clusters were identified. The "Bibliotherapy for children" cluster with 1013 keywords was recognized as the largest cluster, and the "Bibliotherapy" keyword with 543 frequencies was the most frequent keywords. The "Bibliotherapy" and "Depression" keywords with 153 frequencies had the most co-word occurrence. The network density was 1.26. Moreover, the keywords of bibliotherapy, depression, and self-help had the highest rank centrality (100, 85.417, and 82.292), betweenness centrality (11.194, 5.378 and 4.310), and closeness centrality (100, 87.273, and 84.956), respectively. Conclusion: The trend of bibliotherapy studies was poor, and the medical fields had not paid much attention to its use in the treatment of diseases. Therefore, health policy makers must take the necessary plans to improve and strengthen bibliotherapy studies in all areas

Bibliometrics analysis of scientific outputs of Covid-19 disease in Scopus database

Aim: The aim of the present study was to analyze the descriptive and content structure of scientific documents produced by Covid-19 in the Scopus database using scientometrics method. Materials and Methods: The present study was conducted using a scientometrics method. The population of this study consists of 1353 documents in the field of Covid-19 in Scopus Database. The collected data were analyzed using Excel software and the subject maps of this area were mapped using RavarPremap, UCINET, NetDraw and SPSS software. Results: The findings of the study show that a total of 46901 documents are indexed by Covid-19 on the Scopus database. Extracted documents were 8 formats. The results showed the most productive authors of Covid-19 disease show that the three researchers Wang Y, Xia J and Li X had the most scientific output respectively. The results showed authors with high social network centrality. Conclusions: Also clustering analysis of the concepts and words of this new viral disease shows that research by world researchers have included 8 study clusters. These 10 study clusters include: Diagnostic Imaging and Isolation; Symptoms of Coronavirus; Virus Genome and Phylogeny; Pathogenicity; Public health and Outbreak Novel and Coronavirus; Epidemic Coronavirus; Coronavirus Infection and Covid-19; Virus Pneumonia and SARS-cov-2

Scientific mapping of “Social Information” field in Web of Science database: a bibliometric study

Introduction: Access to social information focuses on those technologies that put the users in interaction with the information, to provide the users more accessibility to the information. Objective: The analysis of intellectual structure of the published studies of social information field in the Web of Science (WoS) database according to bibliometric analysis and centrality indicators in WoS database in the period 1983 to 2018, is done through examining the effectiveness and impressionability of this field to recognize its studied fields and effective factors. Methodology: method of the research was descriptive that used bibliometric approaches based on the scientific data in WoS database; The common techniques such as co-word and co-author were used. The social information extracted data were analyzed by social network analysis centrality indicators of VOSviewer, Excel, and UCINET software. Results: The results shown that the most of these articles within social information field were published in USA, Germany, England, France, and China, and also some research outputs have been done in that fields in Korea and Iran. According to the scientific outputs of researchers in the WoS database, on the period 1983 to 2018, USA took the first place with 1496 articles. Authors such as Sheldon, Lalande, Webster, Karius, Nocera, Forceman, and Laaksonen have had the most cooperation in the production of social information field scientific outputs. Based on co-words analysis of web of science category (WC) and subject categories (SC), social information area in this study was divided into four clusters which their topics included social recognition, social behavior confronted with outer environment, social networks, learning and social information processing in human and software. Also, high degree into different centrality measure is related to Psychology, Telecommunication, behavioral sciences, evolutionary biology, and psychology, multidisciplinary in WC and SC

Scientific mapping of “Social Information” field in Web of Science database: a bibliometric study

Introduction: Access to social information focuses on those technologies that put the users in interaction with the information, to provide the users more accessibility to the information. Objective: The analysis of intellectual structure of the published studies of social information field in the Web of Science (WoS) database according to bibliometric analysis and centrality indicators in WoS database in the period 1983 to 2018, is done through examining the effectiveness and impressionability of this field to recognize its studied fields and effective factors. Methodology: method of the research was descriptive that used bibliometric approaches based on the scientific data in WoS database; The common techniques such as co-word and co-author were used. The social information extracted data were analyzed by social network analysis centrality indicators of VOSviewer, Excel, and UCINET software. Results: The results shown that the most of these articles within social information field were published in USA, Germany, England, France, and China, and also some research outputs have been done in that fields in Korea and Iran. According to the scientific outputs of researchers in the WoS database, on the period 1983 to 2018, USA took the first place with 1496 articles. Authors such as Sheldon, Lalande, Webster, Karius, Nocera, Forceman, and Laaksonen have had the most cooperation in the production of social information field scientific outputs. Based on co-words analysis of web of science category (WC) and subject categories (SC), social information area in this study was divided into four clusters which their topics included social recognition, social behavior confronted with outer environment, social networks, learning and social information processing in human and software. Also, high degree into different centrality measure is related to Psychology, Telecommunication, behavioral sciences, evolutionary biology, and psychology, multidisciplinary in WC and SC

Identifying content structure of “Knowledge and Information Science (KIS)” studies based on co-word analysis of articles in “Web of Science (WoS)” database (2009-2013)

This study aimed to identify and analyze the structure of &ldquo;Knowledge and Information Science (KIS)&rdquo; scientific articles using co-word analysis in the &ldquo;Web of Science (WoS)&rdquo; database. Methodology of this study was content analysis of articles. By co-word analysis of the articles, subjects and concepts of KIS were identified, using Between-Groups Linkage algorithm in clustering techniques. The study population was selected using the census sampling of 16475 journals&rsquo; articles in WoS database (2009-2013). Also, statistical analysis regression correlation was used. RaverPremap software, SPSS, and Excel were also used. Findings showed that the words &quot;information&quot;, &quot;web&quot;, &quot;research&quot;, &quot;citation analysis&quot;, &quot;knowledge&quot;, &quot;Library&quot;, &quot;journals&quot;, and&quot; technology&quot; have high impact in studies. Analysis of clusters showed that articles words divide to 13 clusters. The main subjects of clusters includes &ldquo;teaching and learning of KIS; Information literacy&rdquo;, &ldquo;Knowledge & Information Organization&rdquo;, &ldquo;Web resources and social networks&rdquo;, &ldquo;professional ethics in information science&rdquo;, &ldquo;informatics, communication and health information services&rdquo;, &ldquo;information management; information systems; knowledge management and innovation&quot;, &ldquo;indicators of informetrics and scintometrics&rdquo;. Analyzing of clusters&rsquo; concepts indicated emerging some other fields of science studies in KIS is phenomenon. Given the diversity and increases of scientific capital of other disciplines in KIS scientific outputs, interdisciplinarity of KIS knowledge was increased as well. Awareness of the interdisciplinary relation of KIS with other fields enabled experts to strengthen the cooperation with their researchers

Analysis and Comparison of Interdisciplinary Relations of Library Science and Information Science Based on Citation Clustering in The Period of Before and After the Appearance of the Web

The purpose of the present study was to analyze the interdisciplinary relations of &ldquo;Library Science and Information Science&rdquo;. For this purpose the subject categories of citing and cited journals of these fields were investigated in JCR database during the period of 1987-1997 and 2003-2013, and through the comparsion of obtained results the impact of information technology on the development of &ldquo;LIS&rdquo; interdisciplinarity was investigated. Methedology of the research was co-citation analysis of journals in scientometrics studies. Also the research was performed using the conventional techniques of scientometrics including Bradford law, Ward hierarchical clustering approach in statistical software SPSS, and the new measure including Proximity index. Research community includes citing and cited journals of 56 &ldquo;LIS&rdquo; journals during 1987-1997 and 83 journals during 2003-2013 in Journals Ctiation Report (JCR) database. The results showed that &ldquo;LIS&rdquo; has been influenced by other subject categories more than affecting them. For example, the number of journals which &ldquo;LIS&rdquo; cited from 1758 (in the first period) has increased to 5303 (in the second period). Co-occurrence matrix of core citing and cited subject categories was analyzed, and three main clusters in the first period and seven clusters in the second period were drawn. In general, the amount and quality of co-occurrence of subject categories in clusters showed that the domain and variety of affecting and affected subject categories were expanded in the second period. Structural similarity of clusters for affecting and affected subject categories calculated. Results showed that structural similarity of clusters in the second period was %10 higher than in the first period. Also, the Structural similarity of affecting clusters of &ldquo;LIS&rdquo; was more than affected clusters. Assessment of difference between subject categories groups by ANOVA and Tukey Post hoc tests showed that there were differences between all numbers of citing and cited groups

Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

Background: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (−28·4 to −2·9) for all diabetes, and by 21·0% (–33·0 to −5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (−13·6% [–28·4 to 3·4]) and for type 1 diabetes (−13·6% [–29·3 to 8·9]). Interpretation: Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations. Funding: Bill & Melinda Gates Foundation

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding: Bill & Melinda Gates Foundation