Characteristics of Bibliometric Analyses of the Complementary,Alternative,and Integrative Medicine Literature: A Scoping Review

Abstract

Introduction:

Research on complementary, alternative, and integrative medicine (CAIM) continues to grow. Bibliometric analyses (BAs) are valuable to assess research trends, identify gaps, and understand the evolution of a body of literature, yet there are no systematic or scoping reviews on how these BAs are conducted. This scoping review aimed to systematically review and summarize BAs on CAIM literature to inform and guide future bibliometric studies in this field and beyond.

Methods:

A scoping review was conducted in accordance with Joanna Briggs Institute guidelines. A systematic search was conducted in MEDLINE, EMBASE, PsycINFO, AMED, CINAHL, Scopus, and Web of Science from database inception to the date of the search on January 5, 2023. Eligible articles were BAs of the CAIM literature. Screening and data extraction were completed independently and in duplicate by at least two reviewers, with findings summarized descriptively.

Results:

The review included 286 articles published between 1995 and 2023, with approximately 75% published in the last 5 years. Studies were conducted in 36 countries, with China (50%) leading in contributions. All articles used performance analysis techniques, whereas 80% also used science-mapping techniques. The most commonly used performance analysis metrics were “total publications” (98%) and “total citations” (67%). Co-word (63%) and co-authorship (55%) analysis were the most common science mapping techniques. VOSviewer and CiteSpace were the predominant visualization softwares employed.

Conclusions:

This review demonstrates large methodological diversity in the conduct of CAIM bibliometrics. As a result of this variability, future research should focus on developing uniform methodologies and incorporating diverse metrics and alternative data sources to enhance the reliability and reproducibility of BAs in the CAIM field.

Keywords

bibliometric analysis bibliometrics complementary and alternative medicine integrative medicine scoping review

Introduction

Complementary, alternative, and integrative medicine (CAIM) is a complex term referring to three distinct concepts related to the use of nonconventional medicine.^1,2 “Complementary medicine” describes nonconventional therapeutic approaches used together with conventional therapies.¹ “Alternative medicine” describes nonconventional therapeutic approaches used in replacement of conventional therapies.¹ “Integrative medicine” describes the combined use of both conventional and nonconventional therapies in a coordinated manner.^1,2 Each of these approaches may also incorporate elements of “traditional medicine,” which leverages “theories, beliefs, and experiences indigenous to different cultures” to promote health.³

CAIM practitioners have continually emphasized a holistic approach to health, considering sociocultural factors and well-being as an essential part of medical care.^2,4 Users of such therapies often perceive CAIM as better at providing individualized, person-centered care compared with mainstream health approaches.^5,6 The prevalence of CAIM use is increasing worldwide, and accordingly, the body of literature on CAIM research has grown immensely, with the steepest increase in CAIM publications observed between the mid-2000s and mid-2010s.^7,8 Identifying broad trends in CAIM research literature and exploring specific topics (e.g., acupuncture, aromatherapy) are crucial for understanding the evolving focus of this field and guiding future research and policy efforts to address gaps in evidence and optimize patient care.

While some CAIM therapies (e.g., yoga for depressive symptoms⁹ or acupuncture for chronic pain¹⁰) have evidence of safety and efficacy, many other therapies have insufficient evidence on effectiveness or safety.^11,12 Furthermore, even when basic effectiveness and safety are established, questions often remain about key characteristics such as intervention dose and implementation or applicability to different patient populations and settings.^13–15

A bibliometric analysis (BA) can be defined as “the application of mathematics and statistical methods to books and other media of communication.”¹⁶ BAs can be used to detect such knowledge gaps and to identify research trends that help predict whether these knowledge gaps are likely to be met.¹⁷ Conducting a BA involves applying quantitative statistical techniques to bibliometric data (e.g., total number of citations, total number of publications) and can be used for a variety of purposes, such as identifying patterns in a given field of research.^17,18 BA techniques can broadly belong to categories of performance analysis (i.e., techniques measuring contributions of research constituents) or science mapping (i.e., techniques measuring relationships between research constituents).^17,18 Examples of research constituents include authors, countries, institutions, and topics.¹⁷ Performance analysis techniques can further be divided into publication-related metrics (e.g., total number of publications), citation-related metrics (e.g., average citations, total number of citations), and citation- and publication-related metrics (e.g., h-index, g-index, proportion of cited publications).¹⁷ Science mapping techniques can include methods such as citation analysis, co-citation analysis, bibliographic coupling, co-word analysis, and co-authorship analysis.¹⁷ For instance, co-citation analysis examines the frequency of publications being cited together, which may reveal thematic clusters.¹⁷ Furthermore, enrichment techniques of network metrics (i.e., quantitative measures of research constituents’ relative importance), clustering (i.e., grouping of similar objects using clustering algorithms), and visualization (i.e., graphical visualizations of research constituents’ connections) can be employed to enhance understanding of the results of science mapping techniques.¹⁷ For instance, software like VOSviewer can be used to visualize thematic clusters in co-citation analysis graphically.¹⁷

Advantages of BAs include facilitating the examination of large datasets that are not feasible for investigation by manual review.¹⁷ Furthermore, the relatively low cost and rapidity of conducting BAs allow for replicable methods.^17,19 For such reasons, the use of bibliometric techniques across different scientific fields, including CAIM, is becoming increasingly popular.^20,21 However, the explosive growth of BAs outside of the field of information and library sciences (ILS) has been characterized by publications that make little reference to bibliometric models, theories, and laws.²¹ This weaker theoretical grounding is particularly problematic in the field of life sciences and biomedicine (LSB), even among other non-ILS fields (e.g., physical sciences, social sciences, arts and humanities).²¹ Accordingly, there is a growing gap in the number of non-ILS BA articles citing other non-ILS BA articles, compared with the number of non-ILS BA articles citing articles within the ILS field, likely attributable to poorer awareness of bibliometric methods outside of the ILS community.²⁰ The misuse of bibliometric research results and “inaccurate dissemination of concepts, results, and methods outside of the bibliometric field” presents a concern to research integrity, with criticism levied toward simple and low-quality BAs.^22,23 These concerns likely extend to the CAIM field as a subset of LSB. All the while, the impact and productivity of CAIM research faces challenges compared with non-CAIM topics, where publications on acupuncture, chiropractic, homeopathy, and osteopathy tend to be cited at below average rates in most broad fields.²⁴

To the best of their knowledge, no systematic or scoping reviews have been conducted on BAs of CAIM therapies or on BAs of any subfield of medicine. A scoping review, which involves mapping the current literature and identifying gaps in research, is a more appropriate methodology to summarize the literature on CAIM BAs than a systematic review, which has a narrower focus.²⁵ The rationale for this work is grounded in the idea that synthesizing BAs on CAIM will provide insight into trends such as the types of CAIM literature typically analyzed from a bibliometric lens, statistical techniques that BAs on CAIM utilize, and, more broadly, suggest methods or topics that may have been underutilized or overlooked, thus signaling how to advance BAs in CAIM. Furthermore, while there are some guidelines on how to conduct BAs,¹⁷ there is no universal standard or consensus in the literature on what a BA should entail. Accordingly, this review will also improve understanding of how BAs are currently conducted and on what topics. Thus, the purpose of this review is to understand the characteristics of BAs of CAIM research literature, which can inform future work at the intersection of bibliometrics and CAIM.

Methods

Approach

The study was conducted using established scoping review methods outlined in Chapter 11 of the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis.²⁶ A previously published protocol describes the objective, eligibility criteria, and proposed methods of this study.²⁷ The Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews checklist was also completed. The Open Science Framework (OSF) was also used to share study materials and raw data, which can be found at https://doi.org/10.17605/OSF.IO/JSQWY.

Study objective

The objective of this scoping review was to systematically review and summarize BAs on CAIM literature to inform and guide future bibliometric studies in this field and beyond.

Inclusion criteria

The only eligible study design was BAs (encompassing terms for “bibliometric analysis,” “scientometric analysis,” and “citation analysis”) or articles that include both a BA and another study design (e.g., BA and systematic review) published in peer-reviewed journals. All included BAs focused on one or more CAIM therapies, as defined by a published operational definition of CAIM.²⁵ This operational definition was created using a systematic search of four peer-reviewed or other quality-assessed resource types: (1) peer-reviewed articles from seven major bibliographic databases, (2) “Aims and Scope” webpages of peer-reviewed CAIM journals, (3) entries containing CAIM therapies in highly accessed online encyclopedias, and (4) highly ranked websites resulting from Health On the Net Code of Conduct searches.²⁸ To date, this operational definition includes the greatest number of evidence sources and is the only one that captures the concept of “integrative medicine”, alongside “complementary medicine” and “alternative medicine.”^2,28 Notably, however, this all-inclusive list contains items that could be applied in a mainstream medicine or CAIM context.²⁹ For the purpose of this review, the authors only included articles which discussed therapies applied in a general or CAIM-specific context and not explicitly as a mainstream treatment. For example, a BA focused on vitamin D for rickets disease (a conventional, first-line treatment)³⁰ would be excluded for the purpose of this review, whereas a BA focused on vitamin D for COVID-19 treatment would be included,³¹ as it reflects a CAIM application. Another example includes stem cell therapy, which is considered a conventional treatment for blood cancers and blood disorders,³² but is increasingly being applied in CAIM contexts, such as in the treatment of chronic conditions such as diabetes mellitus or chronic heart failure.³³ Gray literature (i.e., difficult to find literature) sources were excluded as BA studies are unlikely to be found outside of traditional academic publishing channels. Conference abstracts and study protocols were also excluded as they were unlikely to contain adequate information required to describe the characteristics of BAs on CAIM literature. Finally, all non-English publications were excluded due to the language constraints of the authors.

Search strategy

The following databases were searched from inception to the date of the search execution on January 5, 2023: MEDLINE, Embase, PsycINFO, and AMED (accessed via the OVID research platform), as well as CINAHL (accessed via EBSCOhost), Scopus, and Web of Science. The search strategy included a comprehensive search string of CAIM terms²⁹ encompassing 604 distinct therapies described previously in an operational definition of CAIM.²⁸ The comprehensive search string of CAIM²⁹ was combined with search terms for BAs (e.g., BA, statistical bibliography, citation analysis). Relevant scientific names and/or synonyms were added as a term (i.e., keyword, phrase), alongside relevant Boolean operators. The search strategy, including all identified keywords and equivalent index terms, was also adapted for each included database. The full search strategy for each database has been made available on the OSF at https://osf.io/a723x.

Sources of evidence screening and selection

Following the search, citations were collated, exported into Covidence software,³⁴ and duplicates removed. Title/abstract followed by full-text screenings was conducted independently and in duplicate on Covidence. Prior to each screening stage, pilot screening of 20 titles/abstracts and 10 full texts was completed (H.L., A.Q.S.), and discrepancies were discussed in consultation with J.Y.N. to ensure consistency. Reasons for exclusion at the full-text stage were also recorded. Any disagreements were resolved by discussion with three authors (H.L., A.Q.S., J.Y.N.). Specifically, in cases where the reviewers (H.L., A.Q.S.) were not sure whether the therapy was being applied in a CAIM or conventional context, the decision was discussed with senior authors and CAIM experts (L.S.W., H.C., J.Y.N.). Notably, L.S.W. and J.Y.N. are authors of the original operational definition of CAIM article,^28,29 which informed their inclusion criteria. This process ensured that inclusion decisions were consistent with the intended scope of CAIM. All records screened at the title and abstract stage have been made available on the OSF (https://osf.io/bca3f), as well as records of conflicts at the full-text stage and how they were resolved (https://osf.io/2ny7b).

Data extraction

The data extraction form was developed in two stages and was informed by the overview of Donthu et al.¹⁷ on how to conduct a BA. This is a highly cited guideline that is recognized as an effective resource for conducting BAs with methodological rigor. The use of this guideline also allowed us to standardize their data extraction process, facilitating the identification and easy labeling of key variables, metrics, and analytical techniques relevant to BA studies. In Stage 1, H.L. and A.Q.S. selected 10 articles at random that met the inclusion criteria from a preliminary search of CAIM and BA search terms on Scopus and used the form to independently extract information. H.L. and A.Q.S. then met to resolve discrepancies before meeting with J.Y.N. to discuss adaptations to the form. In Stage 2, H.L. and A.Q.S. identified the 10 most highly cited articles that met the inclusion criteria from a preliminary search on Scopus and independently extracted information from the articles using the latest version of the data extraction form. Another meeting was held between H.L. and A.Q.S., and then with J.Y.N., to discuss and approve the latest version of the extraction form.

The following information was extracted using Excel software, using the specific terminology stated in the included articles: title, author, year, country, study aim, secondary study design (if applicable), type(s) of CAIM, health condition or population addressed, main findings, conclusions, and limitations. In addition, bibliometric details were summarized, including database(s) searched, type of methodology (performance analysis vs. science mapping), number of studies included, metrics used, reporting method, visualization software, and alignment with the BA guidelines from Donthu et al.¹⁷

To ensure consistency and quality, a pilot step was completed where all reviewers (H.T., R.R., S.A., T.C.Y., N.K., M.L., T.P., M.K.) extracted information from the same five articles. A meeting was held between H.L. and A.Q.S. to review the extractions, resolve discrepancies, and provide feedback. Upon completion of the pilot step, reviewers (H.T., R.R., S.A., T.C.Y., N.K., M.L., T.P., M.K.) were divided equally into two teams led by H.L. and A.Q.S. Teams were further divided into pairs of two reviewers to complete independent and duplicate data extraction of the same set of bibliometric full texts. These duplicate extractions were resolved between pairs and reviewed by H.L. and A.Q.S. to ensure consistency. Any conflicts that could not be resolved were discussed with J.Y.N. The complete data extraction table of all included articles has been made available on the OSF (https://osf.io/acyr5).

Data analysis

The results of the scoping review were summarized as frequencies and other descriptive statistics, including mean, median, mode, and interquartile range. Data were also presented in table and figure formats. CAIM therapies included in the BAs were categorized using a two-step approach. First, the authors applied the comprehensive operational definition list of CAIM therapies adopted by the Cochrane Complementary Medicine Field.³⁵ This list is intentionally broad,³⁶ such that not every included therapy (e.g., stem cell therapy) is necessarily always used as a CAIM therapy. To ensure relevance, the authors only included therapies applied in a general or CAIM-specific context, and not as a conventional, first-line treatment. Where possible, the CAIMs were categorized as specifically as possible rather than as part of broad, enumerated therapies (e.g., acupuncture was counted as its own category rather than included in the count for Traditional Chinese Medicine). However, articles that focused on multiple CAIM therapies were counted as part of multiple categories (e.g., “bee venom acupuncture” was categorized as both apitherapy and acupuncture). The authors used terminology consistent with the included article itself and cross-referenced it with the CAIM search string.²⁹ In the second step, the authors grouped therapies into broader domains using the classification system for CAIM³⁷ as adopted by and made available on the National Cancer Institute (NCI), which is a center within the U.S. National Institute of Health. This includes whole medical systems, biologically based practices, mind–body therapies, manipulative and body-based practices, and energy healing.³⁷ Specifically, when analyzing the mean, median, and mode of the total number of performance analysis metrics used in each BA, the authors only assigned values for metrics or techniques that were described in guidance by Donthu et al. (2021). This was due to the large variation in metrics calculated across different BAs, and potentially different interpretations of what may constitute a “distinct” metric.

Results

Search results

A total of 4461 records were identified through database searching, and after duplicate deletion, 3090 records were screened by title and abstract. After excluding 2560 in the title and abstract screening phase, 527 records were screened by full-text, of which 286 articles were ultimately included. Figure 1 provides an overview of the selection process. The complete reference list of all included articles is available in Supplementary Appendix A1.

FIG. 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analysis flowchart detailing the study selection process.

General article characteristics

The general characteristics of the included articles are shown in Table 1. Included studies were published between 1995 and 2023, with three-quarters (74.83%; n = 214) published in the last 5 years (2019–2023). Studies were conducted in 36 countries, as shown in Figure 2, with the most represented countries being China (50.00%; n = 143), India (4.90%; n = 14), Brazil (4.55%; n = 13), the United States (4.55%; n = 13), and South Korea (4.20%; n = 12). Although all included articles were considered to be BAs, there was variation in how the articles self-described their study design. Most explicitly described themselves as a “bibliometric analysis” (77.97%; n = 223) or a similar descriptor such as “bibliometric profile,” “bibliometric review,” or “bibliometric survey” (6.99%; n = 20). Other labels involved descriptors associated with “visualization” (e.g., visual science mapping, network visualization) (9.79%; n = 28). Some also described their study as a “scientometric analysis” (i.e., studies employing statistical methods to analyze bibliographic data of scientific publications) (4.90%; n = 14) or related terms such as “scientometric review” or “scientometric assessment” (4.20%; n = 12). A minority of studies also incorporated secondary study designs (10.49%; n = 30), including systematic reviews (3.85%; n = 11), literature reviews (2.45%; n = 7), and other review designs (e.g., short review, critical review, review) (2.45%; n = 7).

FIG. 2.

The distribution of the countries of included bibliometric analyses on complementary, alternative, and integrative medicine literature (n = 286).

Table 1.

General Characteristics of Included Bibliometric Analyses (n = 286)

Characteristic	Number of articles	Percent of articles
Year of publication
1995–1999	4	1.40%
2000–2004	4	1.40%
2005–2009	4	1.40%
2010–2014	19	6.64%
2015–2019	60	20.98%
2020–2023	195	68.18%
Top 5 countries of publication
China	143	50.00%
India	14	4.90%
Brazil	13	4.55%
United States	13	4.55%
South Korea	12	4.20%
Self-described study design
Bibliometric analysis and/or related bibliometric terms	239	83.57%
Visualization analysis and/or related visualization terms	28	9.79%
Scientometric analysis and/or related scientometric terms	25	8.74%
Secondary study design
Yes	30	10.49%
Systematic review	11	3.85%
Literature review	7	2.45%
Scoping review	1	0.35%
Meta-analysis	1	0.35%
Other review	7	2.45%
Other design	3	1.05%
No	256	89.51%
Top 10 types of CAIM
Acupuncture	64	22.38%
*CAIM (general)	26	9.09%
Traditional Chinese Medicine	20	6.99%
^αExercise	10	3.50%
^αStem cell therapy	10	3.50%
Mindfulness	9	3.15%
^αVitamin D	8	2.80%
Yoga	8	2.80%
Tai Chi	7	2.45%
Cannabis and cannabinoids	6	2.10%
Turmeric/curcumin	6	2.10%
Focus on health topic of condition
Yes
Neurologic and/or neuropsychiatric conditions	26	9.09%
Cancer	18	6.30%
Analgesia and/or pain in general	14	4.90%
COVID-19	13	4.55%
Cardiovascular conditions	6	2.10%
Diabetes and associated metabolic conditions	6	2.10%
Sexual and reproductive health	5	1.75%
Neuropathic pain	4	1.40%
Insomnia	3	1.05%
Other	41	14.34%
No	150	52.45%

*BAs which included articles focused on CAIM broadly rather than focusing on a specific therapy within CAIM.

Inclusion of BAs focused on these therapies was discussed with CAIM experts (L.S.W., H.C., J.Y.N.) to ensure that they fall under the scope of CAIM and, in particular, address the human health context.

CAIM, complementary, alternative, and integrative medicine.

CAIM characteristics

There were several types of CAIMs that the included BA articles focused on, as seen in Table 1 and in Figure 3, with the most represented types including acupuncture (n = 64), CAIM generally (n = 26), and Traditional Chinese Medicine (n = 20). The most commonly studied CAIM therapies in BAs, among the most represented countries, were as follows: China (acupuncture, n = 49/143; Supplementary Fig. S1 in Supplementary Appendix A2), India (yoga, n = 3/14; Supplementary Fig. S2 in Supplementary Appendix A2), Brazil (prebiotics and probiotics, n = 3/13; Supplementary Fig. S3 in Supplementary Appendix A2), the United States (yoga, n = 3/13; Supplementary Fig. S4 in Supplementary Appendix A2), and South Korea (acupuncture, n = 6/12; Supplementary Fig. S5 in Supplementary Appendix A2). A completed data extraction form is available on the OSF (https://osf.io/urmnj). These were further classified as part of five general categories of CAIM that are described by the NCI: whole medical systems (e.g., Traditional Chinese Medicine, naturopathy) (n = 94), biologically based practices (e.g., curcumin, St. John’s wort) (n = 85), mind–body therapies (e.g., mindfulness, meditation) (n = 42), and manipulative and body-based practices (e.g., chiropractic, massage) (n = 7). Five articles focused on CAIMs that encompassed two NCI categories. These included mind–body therapies and whole medical systems (n = 2), biologically based practices and whole medical systems (n = 1), manipulative and body-based practices and whole medical systems (n = 1), and mind–body therapies and manipulative and body-based practices (n = 1). Notably, there were no bibliometric studies on energy healing as a type of CAIM therapy (e.g., Reiki, Therapeutic Touch). As previously mentioned, 26 studies focused on CAIM in general. Another 27 studies might not be universally recognized as CAIM and could not be easily categorized (e.g., stem cell therapies).

FIG. 3.

Most represented complementary, alternative, and integrative medicine therapies.

Target health topic or condition

As seen in Table 1 and in Figure 4, over half of the included BAs were not focused on CAIM in relation to a specific health condition or topic (52.45%; n = 150). The remaining articles focused on topics of neurologic and/or neuropsychiatric disorders (e.g., Alzheimer’s disease, depression, epilepsy) (9.09%; n = 26), cancer (6.29%; n = 18), analgesia and/or pain broadly (4.90%; n = 14), COVID-19 (4.55%; n = 13), cardiovascular conditions (2.0%; n = 6), diabetes and associated metabolic conditions (2.10%; n = 6), sexual and reproductive health (1.75%; n = 5), neuropathic pain (1.40%; n = 4), and insomnia (1.05%; n = 3), among other topics.

FIG. 4.

Most represented health conditions.

Sources of bibliometric data

Web of Science (WoS) was the most commonly used source of retrieving bibliometric data (63.29%; n = 181), followed by Scopus (20.98%; n = 60), PubMed (16.08%; n = 46), MEDLINE (7.34%; n = 21), the Cochrane Central Register of Controlled Trials (6.99%; n = 20), and EMBASE (6.64%; n = 19). Regionally focused platforms, such as the China National Knowledge Infrastructure (6.99%; n = 20), Wanfang Data (3.50%; n = 10), China Biomedical Literature, and Indian MEDLARS (1.0%; n = 3), were less frequently accessed. Google Scholar was occasionally used (2.1%; n = 6) for bibliometric studies. The majority of studies used only one source, whereas about a quarter of BAs reported using two or more sources of bibliometric data (24.48%; n = 70). The bibliometric characteristics of the included articles are shown in Table 2.

Table 2.

Bibliometric Characteristics of Included Bibliometric Analyses As on Complementary, Alternative, and Integrative Medicine Literature (n = 286)

Characteristic	Number of articles	Percent of articles
Databases used in BAs
Web of Science	181	63.29%
Scopus	60	20.98%
PubMed	46	16.08%
MEDLINE	21	7.34%
Cochrane	20	6.99%
CNKI	20	6.99%
Embase	19	6.64%
Wanfang Data	10	3.50%
CBM/SinoMed	9	3.15%
PsycINFO	6	2.10%
Google Scholar	6	2.10%
*Number of included documents
Mean (range)	7910.9 (12–797,632)	N/A
Median	869.5	N/A
Mode	100	N/A
Interquartile range	2541.75	N/A
Type of bibliometric technique
Top 5 performance analysis (n = 286)
Total publications	279	97.55%
Total citations	191	66.78%
Impact factor	136	47.55%
Average citations	113	39.51%
Number of contributing authors	87	30.42%
Top 5 science mapping (n = 228)
Co-word analysis	179	62.59%
Co-authorship analysis	158	55.24%
Co-citation analysis	89	31.12%
Citation analysis	82	28.67%
Bibliographic coupling	5	1.75%
Visualization techniques
VOSviewer	111	38.81%
CiteSpace	76	26.57%

*Information missing for four articles.

BAs, bibliometric analysis; CNKI, China National Knowledge Infrastructure; CBM, China Biomedical Literature.

The number of included documents in BAs

There was a large range in the number of documents that each BA of CAIM literature included, between 12³⁸ and 797,632³⁹ documents. The mean, median, and mode values of the number of documents analyzed were 7910.9, 869.5, and 100, respectively. The interquartile range was 2541.75. Four studies did not specify the number of documents analyzed.

Performance analysis techniques

All included articles used performance analysis metrics in their BA of CAIM literature. The two most commonly calculated performance analysis metrics employed were total publications (97.55%; n = 279) and total citations (66.78%; n = 191). This was followed by average citations (39.51%; n = 113), number of contributing authors (30.42%; n = 87), h-index (23.78%; n = 68), and sole-authored publications (8.39%; n = 24). The total number of Donthu-aligned metrics employed in BAs ranged from 1 to 9, and the mean, median, mode, and interquartile range values of the number of metrics used were 2.9, 3, 1, and 2, respectively. Other very commonly used metrics, which were not described in the guidance article by Donthu et al. on BAs, included journal impact factor (47.55%; n = 136), citation burst strength (26.92%; n = 77), and journal quartile rank (9.79%; n = 28).

Science mapping techniques

The majority of included articles (77.97%; n = 223) also used science mapping techniques in their analyses. Of these science mapping techniques, co-word analysis (62.59%; n = 179) and co-authorship analysis (55.24%; n = 158) were the most frequently conducted, followed by co-citation analyses (31.12%; n = 89) and citation analyses (28.67%; n = 82). Bibliographic coupling (1.75%; n = 5) was rarely employed. The mean, median, mode, and interquartile range values of the number of science mapping techniques employed were 2.1, 2, 3, and 3, respectively. Science mapping techniques were most often presented using visualization softwares such VOSviewer (38.81%; n = 111) and CiteSpace (26.57%; n = 76).

Discussion

To our knowledge, this is the first scoping review that systematically examines the characteristics of BAs on CAIM literature. Overall, their findings highlight that an increasing number of researchers, particularly in the last 5 years, have been employing BA methodology to analyze CAIM literature. A large number of these studies are concentrated on therapies such as acupuncture and other Traditional Chinese Medicine practices. Identifying underexplored areas of research is important, and the authors have attempted to do so within the scope of their review by reporting which CAIM therapies and health conditions have been the focus of BAs.

For example, the authors found no BAs on energy healing modalities such as Reiki or Therapeutic Touch. Given the lack of high-quality evidence for the efficacy of Reiki or energy healing modalities for pain, depression, anxiety, and other conditions,^36,40 as well as having implausible putative mechanisms of action,⁴¹ potential reasons for this absence of BAs may include a lack of interest in these therapies by trained bibliometricians or CAIM researchers. Four international surveys of the perception of CAIM therapies among researchers and clinicians in the fields of oncology, cardiology, surgery, and pain research all found biofield therapies (e.g., Reiki, Therapeutic Touch) to be the least promising CAIM category, with a majority of respondents not being comfortable in recommending biofield therapies to patients.^42–45

Regarding the most studied CAIM categories, where all four surveys found that respondents perceived mind–body therapies to be the most promising CAIM research areas,^42–45 this present review found BAs to be most commonly conducted on CAIM therapies belonging to the category of whole medical systems. This may reflect differences in areas of interest among researchers within the CAIM field versus other fields, where an international survey of CAIM journal authors found the most and least represented areas of CAIM research to be whole medical systems (37.1%) and biofield therapy (4.3%), respectively.⁴⁶ Similarly, one survey of patients and health care professionals on CAIM use in oncology found rates of energy healing use (9.1%) to be uncommon among patients.⁴⁷

With regard to the most represented health topics or conditions of interest, a systematic review of CAIM use among the general population and medical professionals found that CAIM therapies were most frequently used for back pain problems, depression, insomnia/sleeping troubles, headache/migraine, and stomach or intestinal illnesses,⁴⁸ having limited overlap with this present review’s most represented health condition categories of neurologic and/or neuropsychiatric disorders, cancer, and analgesia/pain. A survey of CAIM professional organizations found that the most common medical conditions thought to benefit from CAIM therapies included anxiety/stress, headaches/migraine, back pain, respiratory problems, and insomnia.⁴⁹

However, we caution against overinterpreting the absence of BAs in particular domains. We believe that several other plausible explanations may exist for such gaps: there may be insufficient primary literature to support a BA; researchers with the interest, funding, or capacity to conduct a BA may be lacking; relevant methodological expertise may be limited; or there may be little perceived value or demand for such analyses. Given their study design, the authors are unable to determine the specific reasons for these gaps and thus cannot recommend particular CAIM topics for future BAs. Furthermore, the number of BAs on a given topic should not be taken as a proxy for research maturity, as a few methodologically rigorous BAs may be more informative than numerous weaker ones. This review also identifies considerable methodological variability across BAs in CAIM, such as diversity in the number of documents analyzed, the number and type of databases used, the number and types of metrics used, and the ways in which the data are presented. While qualitative data were also extracted, including main findings, conclusions, and limitations of each article (available on the OSF), the variability in reporting across studies limited our ability to conduct a formal qualitative synthesis.

At present and without a validated quality appraisal tool for BAs, it is currently not possible to systematically assess the methodological rigor of these studies. However, given the relatively low number of performance analysis metrics employed in BAs (with mean and mode values of 2.9 and 1) and the considerable proportion of BAs not using any science mapping techniques (22.03%; n = 63), there is likely a considerably number of articles of limited complexity or analytical depth, with potentially poor quality of conduct. We also cautiously suggest that the low proportion of BAs using more than one database (24.48%; n = 70) in its analysis may also hint toward relatively basic conduct of BAs; while combining databases offers superior coverage of bibliographic data, data cleaning is a time-consuming step and there exists a relative gap in published literature comprehensively discussing preprocessing steps for bibliographic data.⁵⁰ Furthermore, given that BA study designs are typically more applicable for handling large quantities of bibliographic data (compared with systematic or literature reviews),¹⁷ the methodological appropriateness of some included BAs that analyzed a very limited number of documents may be questionable.

Following comprehensive literature searches by multiple authors (A.Q.S., L.S.W., H.C., J.Y.N.) after the completion of the present scoping review, no similar studies in the CAIM field or other health fields were found; to our knowledge, this is the first study of its kind. The increasing use of bibliometrics globally⁵¹ is mirrored in the CAIM literature, where the authors have captured a notable surge in the number of BAs on the topic in the last 5 years. This rise not only reflects the growing recognition of bibliometrics as a valuable tool for mapping research trends and evaluating scientific output⁵² but also a broader shift toward more data-informed, multidimensional approaches to research evaluation in the context of CAIM.^53,54 Bibliometric methods are increasingly recognized for their ability to assess the reach, visibility, and societal impact of CAIM research.⁵⁴ They offer a strategic approach to legitimize and strengthen the evidence base of CAIM through more rigorous and transparent research assessment practices.^53,54 Furthermore, improved access to bibliometric software and visualization tools has made these methods more accessible for researchers.³⁹

Our review shows how bibliometrics can illuminate potential research areas, identify influential authors, and reveal the impact of key studies, providing a comprehensive understanding of developments in the CAIM field. Specifically, performance analysis metrics quantify research output and influence, enhancing understanding of research trends and impact.¹⁷ Science mapping techniques visualize the intellectual structure and development of research fields, providing insights into how key topics evolve and relationships between studies.¹⁷ In our review, it is noted that all of the included studies employed performance analysis metrics, underscoring their fundamental role in evaluating research productivity and impact. These metrics, such as publication counts, citation counts, and average citations per publication, are widely used in BAs due to their simplicity and accessibility.^17,55,56 This ubiquity reflects their perceived importance and ease of application. However, while these basic metrics provide valuable information about the volume and visibility of research output, they offer only a partial view of the quality and sustained influence of scholarly work. In contrast, performance metrics like the h-index, which considers both productivity and citation impact, may provide a more nuanced assessment of research performance,⁴² but were far less commonly used among the examined BAs. Performance analysis alone may not account for all aspects of research impact, such as the influence of specific articles on the field or relationships between research constituents, which science mapping can offer. While a large majority of examined BAs (n = 228) utilized science mapping techniques, not all studies included these methods. The choice to employ science mapping may be influenced by several factors, including the complexity and resource demands associated with these techniques.^17,55,56

However, this review also echoes concerns regarding the lack of standardized variables used across bibliometric studies in CAIM.^18,57–60 Their review shows significant variability in the methodologies employed by different studies, particularly concerning the metrics used and the scope of data analyzed. For instance, some BAs focused on relatively small subsets of documents, whereas others encompassed large-scale datasets, analyzing hundreds of thousands of publications. Similarly, the number of databases consulted varied widely—from a single database to multiple sources. This variability highlights the absence of a universally accepted standard or formal evaluation framework for BAs, which complicates the interpretation and comparison of results across studies. A promising step toward addressing these concerns is the development of the Guidance List for the repOrting of Bibliometric AnaLyses (GLOBAL).⁶⁰ The GLOBAL initiative aims to provide minimum guidelines for the reporting of BAs.⁶⁰ By creating a consensus-based framework for reporting, GLOBAL can help ensure that bibliometric results can be more reliably interpreted and compared across studies.⁶⁰ The project, informed by a scoping review of bibliometric reporting recommendations,⁶⁰ has undergone its Delphi process to refine a 32-item checklist.⁶¹ Established sets of bibliometric standards, particularly to guide researchers outside the ILS field, can help to promote transparency, robustness, and completeness in the reporting of BAs.^62–64

Concerns have especially been raised over the increasing conduct of BAs outside the ILS field and a potential lack of quality control and research standards.^21–23 While the number of WoS-indexed bibliometric studies published in ILS journals is lower than the number published in non-ILS journals, non-ILS articles have a lower average rate of citations per article.²² Ellegaard and Wallin posited that there exists “a slower awareness of bibliometric methods in the community outside the information professionals,”²⁰ contributing to inconsistencies in the reported findings and limiting the generalizability of bibliometric insights. González-Alcaide had further examined the extent to which non-ILS BAs were theoretically grounded in the bibliometric sciences.²¹ Compared with ILS BAs, a lower proportion of bibliometric studies in the LSB field made reference to models (11.42% vs. 13.63%), theories (2.39% vs. 4.92%), or laws (1.38% vs. 3.29%).²²

An additional consideration is that the majority of included BAs on CAIM literature relied on data from WoS, a product of Clarivate Analysis. This finding draws attention to the central role that Clarivate Analytics has in shaping methodological standards for BAs. The heavy reliance on a single data source raises questions about the standardization and uniformity of bibliometric methodologies. While WoS offers comprehensive coverage and well-established metrics, the reliance on this single database suggests a potential bias toward research sources and metrics indexed to this database, which may not fully represent the diversity of CAIM research.^65–68 Furthermore, not all researchers or institutions have access to WoS due to its subscription-based model, which may skew research evaluations and impact the fairness of bibliometric assessments.^65–68

This lack of standardization of BAs also complicates the comparison of results across studies, as differences in methodology can lead to varying conclusions about the state and development of research trends.^62,69,70 This variability can diminish the reproducibility and robustness of bibliometric studies, as different approaches may yield inconsistent findings. Standardization would address these issues by establishing clear guidelines for the selection and application of metrics, ensuring that analyses are conducted consistently and comparably. Such standardization could enhance the credibility of bibliometric studies and improve their utility for researchers, policymakers, and funding agencies. This would be particularly valuable in interdisciplinary research areas like CAIM, where diverse methodologies and research outputs need to be integrated to inform practice and policy effectively.

Implications and future directions

The insights gained from this review have important implications for the field of bibliometrics in the context of CAIM literature and beyond. First, the predominance of performance analysis metrics such as total publications or total citations, while beneficial for assessing research output and impact, provides an incomplete picture of the quality and relevance of CAIM research. Future bibliometric studies should incorporate a broader range of metrics to conduct evaluations of research impact, such as g-, h-, and i-indices. The findings also point to a need for more inclusive and varied data sources to ensure comprehensive evaluations of research topics. Finally, the variability observed in the conduct of BAs draws attention to a need for greater standardization and methodological rigor in the field, such as a formal evaluation framework, to enhance the reproducibility and reliability of bibliometric assessments.

Strengths and limitations

Strengths of this study include adherence to the JBI framework for scoping reviews, as well as the use of a comprehensive systematic search strategy across several bibliographic databases, which allowed us to identify a large number of eligible articles. Furthermore, interpretation of the findings was strengthened by the fact that a total of eight authors extracted articles independently and in duplicate, and all extractions were then reviewed by a third reviewer. However, there are some limitations that must be acknowledged. First, the authors included studies that were only written in the English language, and accordingly, the authors might be missing important international work. This is particularly relevant because CAIM may be practiced more frequently in some regions of the world where English is not the primary language, such as Traditional Chinese Medicine in China, and the authors were not able to assess this literature. However, this issue is mitigated to an extent by the fact that the authors included BAs that largely did not have restrictions by language. Another limitation is that the present review's eligibility criteria included any BAs that focused on CAIMs, which were part of the comprehensive list adopted by the Cochrane Complementary Medicine group.^25,26 This is considered to be an all-inclusive list, where not all items listed are necessarily always applied in a CAIM context (e.g., stem cell therapy, physical therapy, photodynamic therapy). As such, the authors may have included some BAs that were focused on topics that were part of this list, but that may not have been intended to be considered as “CAIM” therapies. This limitation was addressed through their consultation with CAIM experts (L.S.W., H.C., J.Y.N.) to ensure that all the authors made well-informed and careful decisions on which BAs were appropriately aligned with their inclusion criteria, particularly focusing on topics which were perceived to be reasonably applicable within a human health context. Finally, there is the limitation of a lack of standard quality assessment tools or frameworks for assessing the quality conduct of BAs, as well as standards for reporting the results of BAs, which limits the evaluation of methodological rigor of included studies. However, initiatives are underway on guidelines for the minimum reporting completeness of BAs, which may be applied in future BAs.⁶⁰

Conclusions

The present scoping review provides a comprehensive overview of the characteristics of BAs on CAIM literature. The substantial increase in BAs over the last 5 years indicates growing interest in understanding and evaluating the impact of CAIM research through quantitative measures. The predominance of performance analysis techniques and science mapping techniques such as total publications or co-word analysis underscores their importance to assess research productivity and impact. However, the variability in the way that BAs were conducted, including differences in data sources and metrics, points to a need for greater standardization and methodological rigor.

Footnotes

Acknowledgment

The authors gratefully acknowledge Khadija Farooq for her support in the data extraction process.

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

No funding was received for this article.

Ethics Approval and Consent to Participate

This study involved a scoping review of peer-reviewed literature only; it did not require ethics approval or consent to participate.

Consent for Publication

All authors consent to this article’s publication.

Availability of Data and Materials

All relevant data included in this article are available on the OSF at .

Supplemental Material

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