The number and trend of the articles published each year in a certain field can reflect the scholars’ attention to this field. As shown in Figure 2, the amount of literature can be divided into 3 stages: slow growth, stable growth, and rapid growth. The 1999-2003 period was the first stage, with an average of 12.2 papers published each year. The period from 2004 to 2014 was the second stage, with an average of 36.6 papers published each year. The period from 2015 to 2019 was the third stage. After 2015, the number of articles increased substantially, with an average of 93.4 papers published each year. The volume of published articles peaked in 2019 at 112, with an annual total accounting for 12.0% (112/931) of all literature.

Based on the trend of literature growth, this paper divides the research on CHI into 4 study periods: 1999-2003, the first study period; 2004-2008, the second study period; 2009-2014, the third study period; and 2015-2019, the fourth study period. The number of articles in the 4 study periods is 61, 124, 279, and 467.

An overlapping map uses the number of keywords to represent the number of themes at each period and shows the stability of a research theme in a certain field in the form of a data flow. Figure 3 is an overlapping map of CHI research for the period from 1999 to 2019 and clearly shows the emerging and declining themes in this field. The 4 circles in the figure represent the 4 study periods. Displayed from left to right, they are as follows: the 1999-2003 study period, the 2004-2008 study period, the 2009-2014 study period, and the 2015-2019 study period. The number of themes in the first, second, third, and fourth study periods is 52, 95, 163, and 184, respectively. As can be seen, the number of themes increases rapidly.

From 1999 to 2003, a total of 32 themes were passed to the next study period, and the stability index with the next study period was 14.57. In this study period, the research on CHI remains in a slow-growth stage, which is part of the basic research stage. The number of new themes in the 2004-2008 study period was 63. In the 2009-2014 period, 85 themes were continued from the previous study period, and the stability index between the 2 study periods was 58.06. Reflecting the steady growth of CHI research and the steady increase of research articles in these 2 study periods, many emerging themes and a small number of declining themes were included. There were 40 new themes in the 2015-2019 study period, and the stability index between this and the previous study period was 119.74. At this point, the number of themes is increasing steadily, which reflects that the research area of CHI is gradually expanding, and the research content is becoming increasingly richer.

Six of the top 10 highly cited articles in this field came from the 1999-2003 study period (Table 1), and the cited frequency of the articles is ranked as the first, second, third, fifth, sixth, and tenth. This reflects that the papers published in this period form the basis of the research on CHI and play a fundamental role in the research in this field. The most frequently cited paper (940 times) is an empirical study of the quality evaluation of online consumer health information. The evaluation of health-related websites is quite different due to the differences in research methods, preciseness, quality standards, research population, and subjects. Therefore, the operability of quality standards needs to be defined [12]. The second most frequently cited (804 times) paper is the one by Cline in 2001 [13]. This paper summarizes, from the perspective of communication, the potential benefits and comprehensive quality of online consumer health information searching and identifies and discusses the criteria of online health information evaluation. In 1999, Charnock et al [14] developed a tool named DISCERN, which can be used by health information providers and consumers to judge the quality of written consumer health information about treatment options. This paper was cited 521 times. At present, DISCERN has become a highly useful tool for the quality evaluation of network health information. Many scholars use this tool to evaluate the quality of online health information about different diseases and published in different languages. For example, Cerminara et al [15] used the DISCERN tool to evaluate the reliability, accuracy, and relevance of the top 50 links for childhood epilepsy (online information) displayed by the Google search engine. Alnaim [16] used the DISCERN tool to assess the quality of information published on websites that share breast cancer information online in Arabic.

Four of the top 10 highly cited articles in the field of CHI research came from the 2004-2008 and 2009-2014 study period (Table 1). The paper “eHealth literacy: Essential Skills for Consumer Health in a Networked World” was published in the Journal of Medical Internet Research in 2006. In this article, the concept of eHealth literacy was defined for the first time. The ability to find, discover, understand, and evaluate health information from electronic resources, and the ability to apply the acquired knowledge to solve health problems were also explained in this paper [17]. Ranking fourth in the number of citations, the paper was cited 514 times. eHealth literacy has become a mature research topic, and increasingly more scholars are paying attention to it. For example, Kim et al [18] examined the association among eHealth literacy, perceived benefits, self-efficacy, and health-promoting behaviors in patients with type 2 diabetes. Cherid et al [19] investigated the level of mobile technology acceptance, health literacy, and electronic health literacy of 401 patients aged over 50 years with recent fractures.

The strategic map is mainly used to describe the relationship between themes and the relationship strength within the theme to reflect the importance of the theme in the development of the whole field and the development of the theme. The node in Figure 4 is a cluster, and the sizes of the nodes indicate the sizes of the theme clusters. The horizontal axis is the centrality, which measures the relevance of the theme to other themes. With higher centrality, the theme is more important in the whole field. The vertical axis is the density, which measures the relational strength of the cluster keywords within a theme. The higher the density of the theme, the more mature the theme. The strategic map is divided into 4 quadrants. Quadrant 1 (Q1) contains motor themes, quadrant 2 (Q2) contains highly developed and isolated themes, quadrant 3 (Q3) contains emerging or declining themes, and quadrant 4 (Q4) contains basic and transversal themes. The strategic map of the 4 study periods, the relevant bibliometrics indicators, and the evolutionary status of the research themes are as follows.

The theme of Q1 is medicine, which has the highest density value and a higher centrality (Table 2 and Figure 4). The keywords closely connected to medicine are search engine, interventions, and challenges (Figure 5). The websites and pages displayed by search engines have become the main source from which people obtain medical and health information [25]. Health information/support systems for health promotion are also emerging, such as the CHESS comprehensive health promotion support system [20].

The theme of Q2 is bibliographic database, which has centrality and density values of 1.25 and 66.67, respectively. The theme is closely related internally and has low relevance with other themes. The amount of relevant literature is the least, as the theme has not attracted the attention of the academic circle. The keywords closely connected to bibliographic database are search interface and women’s health. For the prototype network interface of the women’s health bibliography database, Marton et al [26] performed a comparative analysis from 3 aspects: web interface design, overall visual effect, and hypertext navigation and information organization.

Patient education is located on the centrality axis and has the highest centrality. Patient education has the largest amount of research literature and has been cited the most times, indicating that it is an area of high concern and has had a great impact on later research. Patient education is interconnected with many different keywords, such as world wide web and system, but the connection is not strong. The result of the cluster network shows that the internet and information systems are important tools and approaches in patient education [13] and that individualized customized education can be carried out for patients through computers [27]

Needs is located on the density axis and has centrality and density values of 1.85 and 12.5, respectively. The cluster network shows that needs is connected with population and information seeking. The internal demand for health information drives millions of consumers to search for health information on the internet. If the search terms used by consumers do not match the terms set at the information source, the search results will not meet the needs of consumers. Therefore, consumer health information retrieval needs a full range of terminology support [28].

The themes of Q1 have higher centrality and density (Table 3 and Figure 6) and are world wide web, patient education, eHealth, and medication. World wide web has the largest amount of research literature and has been cited 635 times. The cluster network shows that the relationship between the world wide web and internal keywords is weak. The keywords that are strongly connected to patient education are internet health information, record, and challenges (Figure 7). Patient education is an important part of providing health care services and helps to improve the effect of medical care. Doupi and van der Lei [29] discussed the possibility of integrating electronic medical record data and online health information resources to provide personalized patient education for patients. eHealth has the highest density and a relatively high centrality; the cluster network reveals that it is closely related to health communication, tailored intervention, cell phone, and teleconsultation, which is an important research topic in this field. Tufano and Karras [30] used teleconsultation for an obesity intervention that was expected to achieve mass customization function, interactive function, and national customized electronic health information. The location of medication is far from the centrality axis and close to the density axis. The cluster network shows that it has a strong relationship with health literacy and pharmacist. In the research on drug treatment in the field of CHI, scholars are concerned about the health literacy of consumers and whether they can understand the accompanying instructions of drugs [31]. Webb et al [32] have proposed that the design of patient-centered consumer medication information can improve the comprehensibility of warning labels.

The theme of Q2 is technology, with centrality and density values of 18.49 and 41.2, respectively. The important nodes that are connected internally are tools and adults. The literature corresponding to cluster nodes reveals that scholars began using internet technology to intervene in people’s health activities [22].

The themes of Q3 are terminology, behavior, and disease, which have centralities of 3.85, 2.38 and 16.39, respectively, and density values of 16.67, 17.59, and 8.33, respectively. Terminology is only associated with natural language processing and users. The literature corresponding to terminology reveals that the rapid development of consumer health education websites and other applications has promoted research on consumer health vocabulary and that term recognition [33] is one of the important research directions. Disease has weak internal relations. Behavior is associated with libraries, HIV infection, and information seeking. By studying the literature corresponding to behavior, we found that researchers had analyzed health information searching behavior according to different populations. For example, Hesse et al [34] analyzed the 2005 Administration of the Health Information National Trends Survey data to explore the information searching behavior of survivors of cancer and found that their information searching behavior was very common and would not decrease with time.

The theme of Q4 is patients, with centrality and density values of 33.26 and 16.05, respectively. The internal correlation of the patients theme cluster was not strong. An examination of the literature corresponding to cluster nodes revealed that scholars paid more attention to the research of the patients’ attitude, cognition, and intention regarding health information [35].

The themes of Q1 are information seeking, physicians, and attitudes, which have centralities of 69.64, 67.77, and 64.83, respectively, and density values of 37.42, 19.27, and 28.02, respectively (Table 4 and Figure 8). The cluster network (Multimedia Appendix 1) shows that there are 15 nodes and 25 links in information seeking and that the keywords closely related to information seeking are search interface, management program, and community. The literature corresponding to information seeking revealed that scholars analyzed, from the perspective of consumers, the content of online questions, explored the influencing factors of health information searching, and designed a new connected exploratory navigation interface to improve the effectiveness of health information searching [36]. Attitudes had the highest citation frequency, indicating that it had a great influence on the subsequent research. The cluster network shows that attitudes is associated with a large number of different keywords, but the relationship is not strong; among these different keywords, the closely related nodes are community pharmacies, information and communication techniques, and electronic medical records. The cluster network reveals that the nodes that are close to physicians are interviews, patient centered care, patient–provider relationship, and teleconsultation. The literature corresponding to attitudes and physicians reveals that the consumers’ attitude toward, access to, and use of online information related to diseases [37], medicines, diet, and other health issues are the research hotspots in this period. For example, Amicizia et al [38] believes that information and communications technology provide an opportunity for health care workers to use mobile internet to disseminate vaccine-related knowledge interactively and entertainingly and to monitor adolescent attitudes toward vaccination through social media.

The themes of Q2 are patient education, eHealth, and food labeling, which have centralities of 40.51, 30.79, and 6.56, respectively, and density values of 31.32, 37.44, and 15.62, respectively. The cluster network shows that patient education is closely related to smartphone, pamphlet, resources, and Alzheimer’s disease. Scholars mainly conducted research from 3 aspects: patients’ health education needs [39], the effect of health education materials, and health information technology. For example, Kraschnewski et al [40] studied how pregnant women use the internet and mobile phone technology to acquire health care knowledge. They found that women thought that the educational materials they received during prenatal care were not helpful, and therefore, they turned to the internet and smartphone apps to fill the knowledge gap [40]. There are 9 nodes and 12 connections in the eHealth theme. Compared with the previous study period, in this study period, there are fewer nodes and connections. The research content of the theme is more concentrated. The keywords closely related to eHealth are tailored intervention, and online health information. Scholars are concerned about how to use information and communication technology to help patients improve their health status and strengthen their self-health management skills [41]. For example, as a health literacy intervention for Hispanic patients with AIDS, Jacobs et al [42] developed a Spanish-language computer application, which can provide information about HIV infection, treatment, and drugs. Food labeling is a new theme, for which the cluster network shows the related keywords are consumer opinions, recommendations, and ratings. King et al [43] investigated the consumers’ understanding of common terms used to guide food consumption frequency and quantity and found that some terms are highly subjective and that more simple and clear terms need to be developed.

The themes of Q3 are patients and strategies, which have lower centralities and density values. The cluster network reveals that the keywords strongly related to patients were health information service, information behavior, and conflict of interest. Strategies is an emerging theme. The cluster network shows that the keywords associated with it are only evidence-based practice and task and that the weight of the connection is 0.17.

Having higher centralities and lower density values, the themes of Q4 are websites, technology, and risk. The cluster network shows that the keywords closely related to websites are world wide web, evaluation studies, tools, email. By studying the literature corresponding to websites, it is found that the research on the content evaluation of websites and health information intervention through websites are the research hotspots in this period [44]. Thakor et al [45] investigated the information quality of ecommerce websites selling Hypericum perforatum and found that most sites received poor reviews and lacked information on drug interactions, contraindications, and adverse reactions. The keywords closely related to technology are home telehealth and aging. With the aggravation of the aging of the population, the research on home telehealth for the aged group has attracted much attention. Cimperman et al [46] studied the important factors affecting the elderly’s adoption of home telehealth services and found that the following factors play an important role in the perception of home telehealth: perceived usefulness, expectation, social influence, perceived security, computer anxiety, convenience, and the doctor’s opinion [46,47]. Risk is split from medication. The cluster network shows that the relationship between internal keywords is weak and that the relatively strong ones are costs, patient decision aid, and cardiovascular disease. For veterans with and without multiple sclerosis, Cameron et al [48] studied the relative risk of falling and requiring medical care and found that the adjusted odds ratio of falling was 3 times higher for female veterans with multiple sclerosis than for female veterans without multiple sclerosis.

The themes of Q1 are electronic medical records, health information seeking, attitudes, and breast cancer, with centralities of 53.52, 47.78, 45.18, and 48.08, respectively, and density values of 19.71, 18.14, 8.89, and 7.11, respectively (Table 5 and Figure 9). The cluster network (Multimedia Appendix 2) shows that electronic medical records has a strong relationship with internal keywords, which include personal health information management and care partner. Scholars mainly focus on the patients’ health information management, including the sharing of access to the patients’ health records, personal health data visualization, and other contents. For example, Wolff et al [49] sent the doctor’s medical records to patients and authorized nurses through OpenNotes. The scholars verified the acceptability and effect of this approach, and the results showed that it was acceptable for patients and their nursing staff to view the doctors’ medical records; the results also reflected that this method improved the communication with patients and enhanced the patients’ confidence in cooperating with nurses. Keywords closely related to health information seeking are users, behavior, health information needs, and consumer health information behavior. An examination of the literature corresponding to important nodes revealed that the users of library, online health consultation platform, social media, and other media were often considered research objects and that a discussion of these users’ health information needs and behaviors was a research hotspot in this period [50,51]. For example, taking the online health consultation case on “Taiwan eDoctor,” an online health consultation platform, as the research object, Chiu et al [52] studied the length, time, communication mode, purpose, and identity disclosure of online consultation questions and described the communication mode of patients in the process of health information searching. Attitudes was closely related to internal keywords, such as HPV vaccines, risk, evaluation studies, and physicians. Systematically studying the rankings, quality, and contents of the web pages related to HPV vaccines, Fu et al [53] classified the included web pages into critical and noncritical ones and found that the quality of the critical web pages was poor but that the critical web pages often obtained higher rankings. Keywords closely related to breast cancer are online health communities, support groups, and preferences. The scholars mainly focused on the content analysis of the online health community [54] and its supporting role for patients with cancer. For example, through interviews and questionnaires, Huh et al [55] developed online health community roles to reflect the users’ needs and requirements when using an online health community. These roles can help provide users with customized social support and patient support. The study found that the roles of online health communities can be divided into 4 categories: managers, opportunists, scientists, and adventurers. These roles reveal user interaction behavior and attitude patterns when using online health communities.

The themes of Q2 are pharmacy, online health information, and academic libraries, with centralities of 16.52, 4.52, and 7.82, respectively, and density values of 28.49, 9.03, and 6.49, respectively. A mature professional theme (pharmacy) has the highest density and is close to the density axis. The keyword most closely related to pharmacy is patient medication information. Monkman and Kushniruk [56] studied consumer medication information in pharmacies and found that the organization and presentation of online consumer medication information need to be improved. The content of consumer medication information needs to be improved in order to promote the safety and effective use of drugs [57]. The keywords in the online health information cluster network include video, web 2.0, and world wide web. Scholars mainly pay close attention to the use and quality evaluation of online health information [58]. As an emerging theme, academic libraries has the lowest centrality, the lowest amount of relevant literature, and the lowest citation frequency.

User-centered design, with centrality and density values of 11.9 and 6.3, respectively, is located on the centrality axis. One of the keywords clustering with user-centered design is smartphone apps. An examination of the key literature corresponding to cluster networks reveals that scholars focus on designing user-centered, smartphone-based mobile health apps, such as nutrition education apps that, for example, provide technical support for adolescents with overweight and obesity [59].

Having lower centralities and density values, the themes of Q3 are internet utilization and costs. The internal relationship between internet utilization and costs is weak; both are in an immature development stage and have little impact. The cluster network shows that the keywords in costs include search engine and health records; the keywords in internet utilization include health behavior, systematic review, and patient education as topic. The literature corresponding to internet utilization reveals that the content of relevant literature involved patients using the internet to search for health information for self-care. For example, Jamal et al [60] studied the online health information searching behavior of patients with type 2 diabetes in the Middle East and its influence on their self-care behavior. The results showed that most internet health information searchers had positive changes in their behaviors after searching and had a stronger awareness of diabetes self-care [60].

Natural language processing is located on the density axis, with centrality and density values of 24.1 and 4.18, respectively. The cluster network shows that natural language processing is connected with consumer health vocabulary, state, online support groups, and text. An examination of the core literature corresponding to the cluster shows that most scholars mined and dealt with the health-related contents of consumers through social media, health websites, health forums, and other ways to obtain the users’ health needs, explore the users’ health behaviors, and investigate the application of health information technology [61,62].

The themes of Q4 are health communication, health literacy, and technology, with centralities of 57.98, 50.29, and 54.79, respectively, and density values of 4.7, 3.55, and 3.46, respectively. The technology cluster network formed 15 nodes and 21 wires, but the internal relationship was very weak. Health communication has the highest centrality and has many connections with external themes. It is a key theme with development potential. The cluster network shows that health communication is strongly related to keywords such as medicine, telehealth, and perspectives. Benis et al [63] studied the use of communication channels between patients and health care organizations. By matching the communication channels with the patients’ personal information, the communication between medical institutions and patients can be transformed into a more active mode, and the patient’s participation can be improved. Health literacy is an emerging theme; it has the largest number of related literature and the largest citation frequency sum. The keywords closely related to health literacy include skills, patient education, and public libraries. Health literacy is the ability of individuals to access and understand health information and to use it to maintain and promote their health. An examination of the literature of important nodes reveals that scholars pay more attention to the assessment and intervention of health literacy [64] and the assessment of internet health information quality [65,66].

The theme evolution map shows, through a data flow, the evolution of the 4 study period themes of CHI research. It can analyze and track the dynamic evolution of the themes in the field of CHI research over a period. Figure 10 shows the CHI research field’s theme evolution map. Each column in the figure represents a study period. In the figure, the nodes represent the research themes, and the size of the nodes is proportional to the number of related articles of the research themes. The connection between the nodes represents the theme data flow, the solid line represents the main keywords shared by 2 themes, and the dotted line represents the shared keywords are not the main keywords. The width of the connection is proportional to the Inclusion index [11].

From Figure 10, it can be seen intuitively that patient education and technology appear in 3 study periods, and that eHealth, attitudes, and patients appear in 2 study periods. With time, the circle in the theme evolution map becomes larger, the number of the research themes increases, and the data flow between the research themes becomes increasingly complex. This reflects the emergence of new research themes and contents from 1999 to 2019. According to the theme evolution map, the size of the research theme circle, and the data flow between themes, 10 theme evolution paths of 3 research directions in the field of CHI were determined.

Consumer health education is the process of assisting one to acquire the correct information and understanding so that one will be able to make wise decisions about a certain health item [67]. Patient education → patient education → patient education → health literacy, pharmacy (subpath 1). Patient education → world wide web → websites → health communication (subpath 2). Patient education → eHealth → eHealth → health literacy, breast cancer, health communication (subpath 3).

The 3 subpaths above evolved from the main and branch directions of the patient education theme in the first study period. Over time, the nodes on the evolutionary path become larger, the number of research articles increases, and the data flow from node splitting is greater. The data flow of patient education and intervention research evolution is relatively clear and represents the main path of the evolution theme of CHI. The theme on the path mainly moves between the first quadrant and the fourth quadrant, and the split and fusion of themes are obvious. In the second study period, subpaths 1 and 3 became the focus of research. In the third study period, the theme density increased and the centrality decreased, demonstrating a professional and mature research direction in the field. In the fourth study period, the themes split into several themes with great influence and development potential (health communication and health literacy). In the third study period, the subpath 2 integrated multiple themes, and the density of themes decreased. In the fourth study period, the theme split into several low-density but high centrality themes (natural language processing).

The evolutionary path of consumer demand, attitude, and behavior research consists of 3 subparts. Needs → patients → attitudes, physicians → attitudes, health literacy, health information seeking, internet utilization (subpath 1); medicine, needs → behavior → information seeking → health information seeking, health literacy (subpath 2); and medicine → diseases → patients → electronic medical records (subpath 3).

These 3 subpaths evolved from the main and branch directions of medicine and needs in the first study period. With time, the number of nodes on the evolutionary path increases, the number of research articles increases year by year, and the data flow of node splitting also increases. The themes in the evolutionary path of consumer demand, attitude, and behavior research mainly move between the first, third, and fourth quadrants, and the themes are divided and integrated. The theme of subpath 1 has gone through a stage in which centrality and density rise, and in this field, it finally forms many core themes, such as health information seeking, health literacy, and attitudes. In the second study period, subpath 2 splits to form a new theme (behavior). Later, this theme attracted the attention of many scholars in the field; its density and centrality increased rapidly, and it became the core theme in the field. In the second and third study periods, subpath 3 is an edge theme that is not of high concern. In the fourth study period, some themes (attitudes, physicians, technology, patients, websites) split and merge into a high centrality and density key theme (electronic medical records).

Currently, big data, internet plus, artificial intelligence, and other emerging information technologies have been tightly integrated with traditional medical and health industries. The application of internet and information technology in the field of CHI has attracted more attention from computer science and communication science scholars. The evolution path of internet and information technology application research consists of 4 subpaths. Medicine → technology → technology → technology, health communication (subpath 1); patient education → eHealth → eHealth → online health information (subpath 2); needs, bibliographic database → patients, world wide web → information seeking → natural language processing, user-centered design, academic libraries (subpath 3); and medicine → world wide web, terminology → websites → online health information, natural language processing, breast cancer (subpath 4).

These 4 subpaths evolved from the main directions of bibliographic database in the first study period as well as the branch directions of patient education and medicine. The number of research articles is gradually increasing, and the phenomenon of node splitting and fusion is also obvious. The theme of the evolution path of the internet and information technology application research mainly moves between the first, second, and fourth quadrants. The evolution path is relatively complex, which may be related to the application of information technology in different research directions. Subpath 1 emerged from the theme of the first study period, and the density decreased in the second study period. In the third and fourth study periods, the centrality increased. The density decreased after the split of multiple themes, and some important themes with strong influence and development potential developed. Subpath 2 divides from the theme of patient education in the first study period. In the second study period, a key theme with high centrality and density was formed. In the third and fourth study periods, the centrality decreased, and the density increased; it became a professional theme in the field. The data flow of subpaths 3 and 4 is relatively complex and is formed by the convergence of 2 routes in the first and second study period.