Insight into the characteristics of research published in traditional, complementary, alternative, and integrative medicine journals: a bibliometric analysis
Bibliographic record
Abstract
BACKGROUND: Traditional, complementary, alternative and integrative medicine (TCAIM) can be described as diverse medical and healthcare interventions, practices, products, or disciplines that are not considered as part of conventional medicine. Inherent in its definition, TCAIMs are comprised of a wide variety of therapies with highly variable safety and effectiveness evidence profiles. Despite this, the use of many TCAIMs is highly prevalent among patients globally. The present study consists of a bibliometric analysis of TCAIM journals. METHODS: A single search of all International Standard Serial Number (ISSNs) of all journals categorized as "complementary and alternative medicine" (code 2707) based on the All Science Journal Classification (ASJC) was run on Scopus on April 17, 2021. All publication types were included; no further search limits were applied. The following bibliometric data were collected: number of publications (in total and per year), authors and journals; open access status; journals publishing the highest volume of literature and their impact factors; language, countries, institutional affiliations, and funding sponsors of publications; most productive authors; and highest-cited publications. Trends associated with this subset of publications were identified and presented. Bibliometric indicators of production were calculated, and bibliometric networks were constructed and visualized using the software tool VOSviewer. RESULTS: A total of 172,466 publications (42,331 open access), were published by 219,680 authors in 143 journals from 1938 to 2021. Since the 1940s, an upward trend with respect to the volume of publications can be observed, with a steep increase observed between the mid-2000s and mid-2010s. The journal that published the largest number of publications was the Journal of Natural Products (n = 15,144). The most productive countries included China (n = 45,860), the United States (n = 29,523), and Germany (n = 10,120); a number of the most common institutional affiliations and funding sponsors also originated from these three countries. CONCLUSIONS: The number of publications collectively published in TCAIM journals follows an upward trend. Given a high prevalence of TCAIM use among patients, increased acceptance of TCAIM among conventional healthcare providers, and growing interest in the research of TCAIM, future work should continue to investigate and track changes in the publication characteristics of the emerging research on this topic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.021 | 0.034 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".