Mapping India’s Scholarly Output and Highly Cited Publications in Traditional, Complementary and Integrative Medicine: A Bibliometric Analysis (2005–2024)
Bibliographic record
Abstract
Background and Aims: Traditional, complementary and integrative medicine (TCIM) comprises diverse medical systems and health practices beyond mainstream medicine, emphasising holistic well-being. Globally, 170 World Health Organization (WHO) Member States use TCIM, integrating policies, regulations and research initiatives. India, endowed with rich indigenous systems such as Ayurveda, Yoga, Unani, Siddha, Sowa-Rigpa and Homoeopathy, has made substantial progress in education, infrastructure and research. We aim to provide a bibliometric assessment of TCIM research output from India between 2005 and 2024 using the Scopus database, identifying trends, collaborations, funding and key contributors. Methods: Publications were retrieved via a structured Scopus query using terms related to TCIM and India. Data (2005–2024) were analysed using Microsoft Excel, VOSviewer and MetaInfoSci. Indicators included total publications (TP), total citations (TC), citations per publication (CPP), funding patterns, collaborative networks, productive institutions and authors and thematic keyword clusters. Results: A total of 207 highly cited publications (HCPs) were identified (TP/year: 10.89), with 39,919 citations (CPP: 192.85). Annual growth averaged 16.42%, with publication peaks in 2011, 2014 and 2018. About 34.78% of articles received funding, mainly from the University Grants Commission (UGC), Department of Science & Technology (DST), Department of Biotechnology (DBT), Council of Scientific & Industrial Research (CSIR) and Indian Council of Medical Research (ICMR). Collaborations involved over 200 foreign institutions, with Iran, Canada, Portugal, Saudi Arabia and the USA as prominent partners. Major research themes linked phytotherapy, plant extracts, metabolic disorders and oxidative stress. Key productive institutions included Jamia Hamdard, Loyola College and Jadavpur University. The top impactful authors were Ayyanar M, Ignacimuthu S and Patwardhan B. Conclusions: TCIM research in India shows sustained growth, strong citation impact and increasing international collaboration. Strategic funding, standardisation and global integration efforts can further enhance research output and evidence-based application.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.086 | 0.085 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".