1 Introduction
In the long-term development process, traditional Chinese medicine has accumulated rich experience in diagnosis, treatment and maintenance, emphasizing that healthcare professionals are not divided into different disciplines and three parts treatment, seven parts nourishment, and adhere to the basic principle of prevention over treatment[1]. The concept of “preventive treatment of disease” has a long history, and as early as mentioned in the Suwen·Si Qi Tiaoshen Dalun, which states: “The wise sage does not treat that which is not ill, and does not treat that which is not in disorder.”[2,3] It shows that predecessors have long been aware of the importance of health care and prevention before disease, and the concept has gradually been adopted as the main component of modern Chinese preventive medicine, and has also started to practice in the clinical field of Chinese medicine. In today’s society, people pay more and more attention to their own health, and with the improvement of life quality, a growing number of individuals are turing their attention to preventive treatment of disease. The discussion of “prevent illness before it occurs, prevent complications when illness is present, and prevent relapse after recovery” contained in “preventive treatment of disease” is still consistent with the teachings of Huangdi Neijing, including the states of disease, the states of non-disease, the states of illness and the states after disease[4].
The knowledge graph is structured around the framework of entity-relationship-entity, entity and attribute-value pairs, and the ability of entities to solve problems is analyzed from the perspective of association relationship[5,6]. The concept of knowledge graph was initially proposed by Google in 2012 with the initial purpose of improving the efficiency of search engines and making search results intelligent[7]. In recent years, knowledge graph has been widely concerned by the academic community, which facilitates concept retrieval through reasoning and enhance the understanding of user intentions from the semantic aspect[8], provides users with a complete, systematic and clear knowledge architecture, and thus improves the service quality of information system[9]. According to the search statistics, there are 24,109 applied knowledge map and literature describing relevant contents in the current CNKI database in China, while there are only 7,251 relevant papers on the topic of TCM and preventive treatment of disease, including 1,951 research papers, 141 reviews and 134 information papers. Therefore, this study will use visualization technology, knowledge graph, to understand the research dynamics of TCM in the field of disease prevention and treatment. It aims to visually and clearly present the research context, current hotspots and development trends in this field, and provide objective and reliable data sources for researchers, doctors and therapists of related diseases in the future, so as to promote the research and development of this module.
2 Data and Methods
2.1 Software Introduction
In the comparison of knowledge graph, it is found that VOSviewer can adjust the threshold value, and the visualization effect of the graph is strong, and the amount of suitable data is also relatively large, which can quickly and effectively extract keywords, apply analysis, and display the relationship clearly[10]. Accurately screen keywords and related authors, adjust the size of nodes, to facilitate the viewing of each node, and clearly display the relationships in the form of a network. CiteSpace has a variety of data conversion programs, which can directly transform Chinese data without using additional conversion software[11]. Meanwhile, the time series analysis function can be realized through the method of time slicing to detect unexpected words in literature. It has comparative advantages in presenting the dynamic development rules of disciplines and exploring the research frontiers of fields[12]. Therefore, visualization tools VOSviewer (1.6.19) and CiteSpace (6.2.R2) will be used in this study to analyze and draw the knowledge map of the treatment of non-disease (preventive treatment), and visually analyze the research hotspots and development trends in the field of Chinese treatment of non-disease.
2.2 Data Sources
China National Knowledge Infrastructure (CNKI), VIP, WanFang database and Web of Science are the research data sources for this study. The search topic is set as “TCM and prevent treatment of diseases and knowledge atlas or TCM and prevent treatment of diseases”, and the time span is from 2013 to 2023. A total of 9,541 literatures were retrieved from the three database, 2,226 literatures were de-duplicated and screened, and the final research data was 7,315 literatures. Additionally, 200 papers were retrieved from Web of Science, and 123 literatures were downloaded for analysis.
2.3 Research Methods
The bibliographies of three databases are exported in EndNote format to provide data sources for VOSviewer analysis. Taking authors, keywords and institutions as objects, the literature in the three database is exported in forwords format. The data is summarized and exported by NoteExpress software, and then the data is imported into CiteSpace to draw the scientific knowledge map.
3 Data Visualization Analysis
3.1 Author Co-occurrence Analysis
The EndNote documents exported from 2013 to 2023 are summarized and exported again by EndNote software, and the text format is converted to research information systems (RIS) format, which can be imported into VOSviewer (1.6.19) version, and the frequency of occurrence is set to at least 20 times. After data analysis, the software draws the author network view. In this way, we can intuitively see the number of papers published by the author, the influence and the cooperative relationship between various authors, and find the authors with more papers and higher influence in the field of medical treatment and prevention in China and the cooperative relationship between various authors. As shown in Figure 1, each node is an element of the knowledge graph, that is, the author. The lines connecting each node represent the cooperative relationship between the authors. The thickness of the lines indicates the strength of the correlation between the authors.
As can be seen from Figure 1, professor LI Candong has published relatively more papers in the field of medical treatment, with a total of 34 papers, followed by HE Qinghu, GUO Qing, YANG Lei and PENG Jin, with 21, 17, 15 and 12 papers respectively. In Figure 1, the allocation of 6 different colors indicate the cooperative relationship and research focuses among various authors. The same color indicates that the authors have established strong collaborative links with each other and are share similar research interests. The color red associated with LI Candong, denotes a primary focus on traditional Chinese medicine health management. The blue color linked to PENG Jin whose mainly research direction is the status of traditional Chinese medicine in “treatment of disease” equipment; The main research direction of GUO Qing is also contered around traditional Chinese medicine health management, as indicated by the same blue color. The yellow category, linked to YANG Lei, is concerned with the treatment of disease and health management. Purple group led to CHEN Xinyu mainly research direction is to strengthen Yang Qi for the “cure of diseases”; The green cluster represents a focus on the bone sub-health of traditional Chinese medicine.
According to the data derived from CNKI, VIP and WanFang databases, the articles on the knowledge map of CNKI and WanFang were analyzed. The top 20 articles cited most frequently in recent years were obtained, as shown in Table 1. From Table 1, we can see that among the 20 articles, only 6 articles were cited in the time range from 2013 to 2023. This suggests that articles published during this period are less cited, but they also have a certain influence with the acadmic community. In all literatures, the majority of articles cited before 2013 have also garnered substantial citation counts, which shows that the research in this domain is gradually expanding. Among them, three articles were written by professor WANG Qi, followed by two articles written by professor GE Jirong, which were cited by a large number of peers. As a standard, the Classification and Determination of Constitution in TCM (ZYYXH/T157-2009) and other documents play a guiding role in the classification and diagnosis of TCM physique, and are widely cited in relevant literatures. The literature on “treating and preventing disease”, such as “Regulating sub-health state is a new contribution of TCM to human in the 21st century”, has been cited more frequently due to the importance of this concept in TCM preventive medicine and its early publication period. The authoritativeness of authors is also one of the reasons for high citation, such as the literature of professors WANG Qi and GE Jirong, is a contributing factor to the high citation of their respective works.
Table 1
Table 2 shows the top 10 most cited literatures from 2013 to 2023, three of distinguished works were contributed by professor WANG Qi. It can be seen that professor WANG Qi plays an important role in the field of TCM treatment and prevention of diseases. In the researches studied with other professors also proposed that the significance of TCM treatment and prevention of diseases is mainly reflected in reducing the medical and health burden, ensuring people’s health, leveraging of the advantages of TCM, and realizing the dialogue and exchange of traditional Chinese and western medicine[2]. Additionally, professor GE Jirong also has an in-depth understanding of the treatment of prevention of disease. He used the symptoms of osteoporosis to explain the TCM principles of “treatment of disease before its onset, prevention of disease, and protection after disease” as recorded in the Huangdi Neijing, which offer certain advantages in the prevention and treatment of primary osteoporosis[13].
Table 2
3.2 Mechanism Co-occurrence Analysis
CiteSpace (6.2.R2) was used to transcode Refwork data and import it to draw the co-presence network map of research institution. Parameters were set as follows: The time zone slice was 2013—2023, and each year was a single time slice, node type, and select mechanism. The data threshold N=10 is set in TopN mode, that is, the top 10 of the occurrence frequency of each time slice, and the displaying nodes are institutions with 30 or more articles. The size of each node corresponds to the volume of publications produced by its respective institution, with larger node signifying a greater number of articles. The thickness of the connections between the nodes indicates the strength and intensity of the cooperation between the institutions, and the intensity of the colors in the nodes indicates the years of publication. As can be seen from Figure 2, research institutions include provincial hospitals and their affiliated hospitals. Beijing University of Chinese Medicine has a large number of publications and is located in the center of the map. Thus, Beijing University of Chinese Medicine is a key presence in the field of Chinese medicine. There are a certain number of connections between each node, but the connection is less, and the degree of cooperation is low. The Orthopedics Department of Dongzhimen Hospital of Beijing University of Chinese Medicine and the Institute of Basic research in Clinical Medicine of China Academy of Chinese Medical Sciences jointly analyzed the characteristics and shortcomings of acupuncture and moxibustion “treatment no disease” technology, and proposed that the later research direction should strengthen the diagnosis and treatment norms and paths of common acupuncture and moxibustion techniques in healthcare[14]. Under the guidance of the Affiliated Hospital of Nanjing University of Chinese Medicine, and in cooperation with the Second Affiliated Hospital of Heilongjiang University of Chinese Medicine and other institutions, the Intervention Plan for the Treatment of Childhood Asthma without Disease has been formulated to standardize the intervention measures for the treatment of childhood asthma without disease and help doctors to better treat it in clinic[15]. Beijing University of Chinese Medicine has more connections with other colleges and universities, and more cooperation with provincial colleges and universities of Chinese medicine and their affiliated hospitals, but the number of cross-provincial exchanges is small, and the cooperation relationship is not close enough. It needs more in-depth cooperation by various institutions to better promote the further development of this field. According to the color depth distribution, it is found that dark green occupies more nodes, indicating that in recent years, various institutions are studying the relevant content of “treating no disease”, and traditional Chinese medicine “treating no disease” has also received more attention. At the same time, in the relevant data statistics of the top 15 institutions with the number of published papers, as shown in Table 3, it can be found that the number of published papers of Beijing University of Chinese Medicine, Shandong University of Chinese Medicine, Chengdu University of Chinese Medicine and other institutions each exceeded 80. These institutions have invested a lot of research energy in the field of TCM “treatment and prevention of disease”, and have achieved quite remarkable research results. Among them, Beijing University of Chinese Medicine and Shandong University of Chinese Medicine stand out as the leading institution in terms of literature publication, securing the first and second positions respectively, indicating that these two universities have strong strength and potential in the field of TCM treatment and prevention of diseases.
Table 3
3.3 Keyword Analysis
3.3.1 Keyword co-occurrence
In the density view of VOSviewer (1.6.19), the closer the color approximates yellow, the greater the amount of literature is. The more terms that cluster around a given point, the higher the weight assigned to neighboring terms, which causes the point’s color to be more yellow. As can be seen from Figure 3, the yellow color is more obvious in the field of preventive treatment of disease. Many researchers in the field of preventive treatment of disease have published a large number of articles. Secondly, it can be seen that there is a close relationship between TCM and preventive treatment of disease, and the correlation between the two areas is relatively strong. Sub-health state is a relatively dangerous state for the human body, but it will gradually improve in the case of timely intervention, it can be seen that good prevention is extremely important. Disease will be accompanied by many unknown factors, good health management can make the body have a certain basis for protection. Diabetes has become a very common chronic disease in the elderly. Daily and timely measurement of blood pressure and control of blood sugar can prevent more serious complications, which is the idea of preventing disease after disease in the treatment of non-disease[16].
CiteSpace (6.2.R2) software was used to draw the knowledge map, the node type was keywords, the threshold was set as “TopN=50”, the pruning option was critical path, the combined image was pruned, and keywords were classified according to LLR algorithm to obtain the keyword clustering co-occurrence map. Centrality was used to represent the importance of nodes in the network. The centrality ≥0.10 and frequency >75 were selected, and invalid keywords were obtain were deleted, 9 keywords with high centrality (Table 4). It can be seen from Table 4 that keywords in the field of treating and preventing diseases of TCM, TCM, health management, TCM constitution, prevention and treatment, treating before diseases, etc., have a high frequency of occurrence. These keywords indicate the focus and concern in the process of discussion and research in this field. Health management occupies a central position in TCM treatment and prevention of disease, which indicates that in the field of TCM, continuous monitoring and management of individual health conditions is regarded as a key mean of disease prevention. The concept of TCM constitution emphasizes the importance of individual differences in disease prevention and treatment. The high frequency of these keywords may be driven by several factors. First of all, with the improvement of social awareness of health and disease prevention, the concept of TCM treating no disease has been paid more and more attention. Secondly, as the population ages and the incidence of chronic diseases rises, more people are paying attention to how to prevent and manage these diseases through TCM methods. Finally, policy support and academic circles’ promotion of TCM research on treating and preventing diseases are also one of the reasons for the high frequency of these keywords.
Table 4
3.3.2 Research frontier (keywords emergence)
The concept of research frontier was proposed in 1965 by Derek John de Solla Price, the father of bibliometrics[17]. Kleinberg’s burst detection algorithm in CiteSpace (6.2.R2) has the function of identifying research frontiers, marking specialties and timely detecting emerging trends and bursts, which is suitable for identifying emerging research frontier concepts[18]. Keyword emergence rate depends on its rapid increase in frequency over a period of time, and will become a frontier topic in this field[19]. By running the “burgain” option in the control panel to extract research frontier terms, the keyword emergence map of TCM constitution literature is generated (Table 5), so as to probe the current research mainstream of TCM treating and preventing disease. The study found that sub-health, preventive health care and health care were the hot spots in the study of TCM treatment of disease from 2013 to 2015. From 2020, knowledge graph and data mining have become the mainstream, and the rise of artificial intelligence and big data has allowed more people to analyze the development of traditional Chinese medicine “treating disease” in an intelligent and visual way.
Table 5
4 Discussions
In this paper, CiteSpace (6.2.R2) and VOSviewer (1.6.19) software were used to comb and dig the literature on traditional Chinese medicine physique from 2013 to 2023. The author analysis found that the representative authors in this field were LI Candong, WANG Qi, HE Qinghu, GUO Qing, etc. Among them, professor LI Candong Stands out as a prominent figure. Professor LI has published a relatively large number of articles, and has a considerable influence in the field of treating disease research. He has put forward the new idea of TCM constitution identification and health management, emphasizing the prevention of diseases through constitution identification, which has an important influence in the academic community. He also participated in the compilation of guiding documents such as the Guide to TCM Health Management Services, which provided norms and guidance for the practice of treating non-disease. Professor WANG Qi has also made notable contribtions to the treating disease field. Professor WANG Qi discovered and confirmed the nine constitutions of Chinese people, systematically built the theoretical system of traditional Chinese medicine constitutions, and initiated the Nine-body Medicine Healthy China Plan. He led the team to develop a series of digital and intelligent TCM physical identification equipment and products, providing technical support and modern service means for the treatment of non-disease, chronic disease prevention and control, and active health. Their research has deepened the spread of the concept of preventive treatment of diease in traditional Chinese medicine, and has also laid the groundwork for more researches.
The analysis of institution found that Beijing University of Chinese Medicine is the main force in the field, with relatively close connections with provincial institutions and a large number of published literatures. It can be seen that Beijing University of Chinese Medicine is a representative institution in the field of TCM treatment and prevention of diseases, and has a crucial position. However, due to geographical factors, inter-provincial collaborations of colleges and hospitals are still relatively few. The lack of cross-regional communication and regional differences in human physique, pose limitations to the research and development of TCM physique, and the research on treating and preventing diseases which will also limit the innovation and development of medical treatments to a certain extent.
The analysis of keywords found that TCM, preventive treatment of disease, Chinese materia medica, TCM experience of famous doctors, prevention of disease before are the keywords of high centrality, and also the hotspots of research. Among them, treatment of disease, TCM, health management, TCM constitution, prevention and treatment are the hot topics of concern. From 2013 to 2023, the attention of TCM has been increasing, and the focus of preventive treatment of disease concept has also increased at the end of 2013. During this period, diabetes and tumor are also a direction of research. The concept of treating the disease before it occurs is also getting attention. With the development of science and technology, the improvement of living standards, the concept of “treatment before illness” has become increasingly emphasized, reflecting a heightened awareness and expectation among individuals regarding their physical health.
From the above summary, it can be found that although the treatment of disease of traditional Chinese medicine has always been concerned, there is still a need for continued development to truly treat the disease before its onset. And various institutions should also strengthen their interactions. With the promotion and support of the “Internet +” their interactions policy, artificial intelligence can also be applied in the field of the treatment of disease[20], helping to predict potential diseases and better treat the disease. China’s aging population is serious, residents pay more attention to medical treatment than prevention, the awareness of personal health status is not enough, relying on “Internet +” to promote community home care[21], is also a powerful way of treatment before illness. Although artificial intelligence and Chinese medicine are still in the fusion stage, all fields are gradually intelligent, and it is believed that the combination of the two will definitely promote the detection and diagnosis of preventive treatment of diease more accurate in the future[22].
5 Outlook
Compared with the database, the processing of the complex knowledge graph designed by the algorithm is relatively simple, and the use of graphs to display the relevant information of the data can more intuitively explain the relevant content and visualize the knowledge. This study adopts the form of knowledge graph, and analyzes the literature in the field of physical fitness in the recent 10 years from CNKI, VIP and WanFang databases. This paper probes into the hot spots and frontiers of TCM treating and preventing disease. The sub-health state may become a rising state in today’s society, but the scope of identifying sub-health state is relatively wide. Any discomfort in the physical and psychological aspects of a person can not be definitively diagnosed as a specific disease in a long period of time[23]. Hypertension is the most common chronic disease and the most important risk factor for cardiovascular and cerebrovascular diseases. Its major complications, such as stroke, myocardial infarction, heart failure and chronic kidney disease, not only cause disability and high mortality, but also seriously consume medical and social resources and create a heavy burden on families and the country[24]. Most of hypertension, diabetes and dyslipidemia have no clinical symptoms in the early stage, and the damage to the body is insidious, gradual, progressive and systemic, which is also an important reason why many people do not pay attention to early diagnosis and early treatment. However, the complications caused by cardiovascular and cerebrovascular diseases have become the most disabling and fatal chronic diseases at present. In view of the early characteristics of hypertension, diabetes and dyslipidenia, the theory of treating and preventing diseases has unique advantages in early prevention and treatment[25]. With the growth of the elderly population, the number of patients with hyperglycemia, hypertension and diabetes is increasing. Although there are certain differences in medical aspects and human body conditions, the degree of harm to life is relatively low to some extent, but there are also many cases of death due to such diseases. So there are a variety of products on the market to monitor blood sugar, blood pressure and heart rate, to monitor the physical condition of the elderly to reassure their children. The idea of curing disease is not just an expectation of a part of the population, and most people in the population want to “cure disease” proactively. Both Chinese and western medicine share common ground yet retain distinct approaches. Traditional Chinese medicine pays more attention to gradual, nourishing treatment, and the restoration of the body. It aims to achieve a harmonious balance of the Yin and Yang energies, as well as Qi and blood, which coincides with the principle of treating no disease.
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