Knowledge Mapping of Acupuncture for Cancer Pain: A Scientometric Analysis (2000-2019)

Abstract

Objective: This study aimed to demonstrate the state of the present situation and trends concerning the global use of acupuncture for cancer pain in the past 20 years.

Methods: Searched the Web of Science database from 2000 to 2019 related to acupuncture for cancer pain, and then used CiteSpace to conduct scientometric analysis to acquire the knowledge mapping.

Results: Yearly output has increased year by year, and the growth rate has become faster after 2012. According to the cluster analysis of institutions, authors, cited references, and keywords, 4, 4, 15, and 14 categories were obtained, respectively. The most productive countries, institutions, and authors are the USA, Mem Sloan Kettering Cancer Center, and Mao JJ, whose frequencies are 196, 24, and 17, respectively. However, the most important of them are Australia, Univ. Maryland, and Bao T, owing to their highest centrality, they are 0.90, 0.21, and 0.09 separately. Moreover, cited references that contributed to the most co-citations are Crew KD (2010), however, the most key cited reference is Roscoe JA (2003). Keywords such as acupuncture, pain, breast cancer, palliative care, and quality of life are the most frequently used. But auricular acupuncture is the crucial keyword. In the cluster analysis of institutions, authors, cited references, and keywords, the more convincing research categories are multiple myeloma, placebo effect, neck malignancies, and early breast cancer, with S values of 0.990, 0.991, 0.990, and 0.923, respectively. Therefore, they can be regarded as research hotspots in this field.

Conclusion: Based on the scientometric analysis in the past 20 years, the knowledge mapping of the country, institution, author, cited reference, and the keyword is gained, which has an important guiding significance for quickly and accurately positioning the trend in this field.

Keywords: CiteSpace; acupuncture; cancer pain; knowledge mapping; scientometric analysis.

Figure 1

Line chart of yearly output on acupuncture for cancer pain. The abscissa in the figure represents the year and the ordinate represents the total number of publications.

Figure 2

Network of countries/territories on acupuncture for cancer pain. The purple node in the middle of the annual ring means the influence and the significance of a country/territory. The larger the node and the more purple it exhibits, the greater is the importance of the country/territory.

Figure 3

(A) Cluster map of institutions based on label clusters with title terms. The combination of symbols and numbers delegates the institutions’ study of similar categories. (B) Timeline zone of institutions on acupuncture for cancer pain. The purple node in the middle of the annual ring means the influence and the significance of the institution. Institutions with the homologous research category are on the same time horizon.

Figure 4

(A) Cluster map of authors based on label clusters with title terms. The combination of symbols and numbers delegates the authors’ study of similar categories. (B) Timeline zone of authors on acupuncture for cancer pain.

Figure 5

(A) Cluster map of cited reference based on label clusters with title terms. The combination of symbols and numbers delegates the cited references’ study of similar categories. (B) Timeline zone of cited reference on acupuncture for cancer pain.

Figure 6

(A) Cluster map of keyword based on label clusters with title terms. The combination of symbols and numbers delegates the keywords’ study of similar categories. (B) Timeline zone of keyword on acupuncture for cancer pain.