Bibliometric and visual analysis of transcranial direct current stimulation in the web of science database from 2000 to 2022 via CiteSpace

Abstract

ObjectiveThis study aimed to evaluate the current research hotspots and development tendency of Transcranial Direct Current Stimulation (tDCS) in the field of neurobiology from a bibliometric perspective by providing visualized information to scientists and clinicians.Materials and methodsPublications related to tDCS published between 2000 and 2022 were retrieved from the Web of Science Core Collection (WOSCC) on May 5, 2022. Bibliometric features including the number of publications and citations, citation frequency, H-index, journal impact factors, and journal citation reports were summarized using Microsoft Office Excel. Co-authorship, citation, co-citation, and co-occurrence analyses among countries, institutions, authors, co-authors, journals, publications, references, and keywords were analyzed and visualized using CiteSpace (version 6.1.R3).ResultsA total of 4,756 publications on tDCS fulfilled the criteria we designed and then were extracted from the WOSCC. The United States (1,190 publications, 25.02%) and Harvard University (185 publications, 3.89%) were the leading contributors among all the countries and institutions, respectively. NITSCHE MA and FREGNI F, two key researchers, have made great achievements in tDCS. Brain Stimulation (306 publications) had the highest number of publications relevant to tDCS and the highest number of citations (4,042 times). In terms of potential hotspots, we observed through reference co-citation analysis timeline viewer related to tDCS that “depression”#0, “Sensorimotor network”#10, “working memory”#11, and “Transcranial magnetic stimulation”#9 might be the future research hotspots, while keywords with the strong burst and still ongoing were “intensity” (2018–2022), “impairment” (2020–2022), “efficacy” (2020–2022), and “guideline” (2020–2022).ConclusionThis was the first-ever study of peer-reviewed publications relative to tDCS using several scientometric and visual analytic methods to quantitatively and qualitatively reveal the current research status and trends in the field of tDCS. Through the bibliometric method, we gained an in-depth understanding of the current research status and development trend on tDCS. Our research and analysis results might provide some practical sources for academic scholars and clinicians.

A bibliometric review and visual analysis of orthotic treatment in adolescent idiopathic scoliosis from the Web of Science database and CiteSpace software

“…If it was >0.5, clustering was typically considered acceptable. [ 9 ] Another structural metric used to determine cluster quality is modularity. [ 7 ] The modularity score (Q) indicates the extent to which a network can be divided into modules.…”

“…The WOS is one of the most comprehensive, systematic, and authoritative databases and is one of the most popular databases for scientometric evaluation with complete references and citations. [ 9 , 10 ] Therefore, this study utilized the WOS database for the literature search and employed CiteSpace software to analyze the records. Our findings aim to begin to build a knowledge map of this field and allow scholars and clinicians to better understand the advancement and future directions of this treatment to develop new schemes for higher treatment success rates and to provide better services.…”

Opportunities and obstacles in non-invasive brain stimulation

“…Overly broad exclusion criteria can introduce population bias; insufficient accommodations for individuals who wear head coverings or exhibit sensory processing sensitivity may hinder diverse participation. Many studies, excluding those focusing on disorders prevalent in older adults, predominantly involve young participants and are conducted in a limited number of countries (Sun et al, 2022 ; Medeiros et al, 2023 ; Wang et al, 2023 ).…”

A Scientometric Analysis and Visualization of Prosthetic Foot Research Work: 2000 to 2022

“…Some of the other bibliometric information includes the number of publications, impact factor, H-index, degree of centrality, strength of linkage, year of publication, and occurrence/citation bursts were extracted and analyzed. CiteSpace (6.1.R3) was applied to detect the keywords and references with citation bursts, while the citation bursts included strength and duration and indicated that a paper was highly cited in a certain period [28]. Centrality is based on the theory of social network analysis by counting the number of shortest paths between other nodes in interest [29].…”