Evidence map›Paper›PMID 40727710›Full record

ArticleIntegrative medicine research2025

Bibliometrics and altmetrics in the context of traditional, complementary, and integrative medicine.

Jeremy Y Ng, Dimity Stephen, Jianping Liu, Thomas Ostermann, Nicola Robinson, Holger Cramer

Abstract read
In one paragraph

Article in Integrative medicine research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jeremy Y NgInstitute of General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany.
Dimity StephenGerman Centre for Higher Education Research and Science Studies, Berlin, Germany.
Jianping LiuCentre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, People's Republic of China.
Thomas OstermannDepartment of Psychology and Psychotherapy, Witten/Herdecke University, Germany.
Nicola RobinsonCentre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, People's Republic of China.
Holger CramerInstitute of General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This educational article explores the utility of bibliometrics and altmetrics in evaluating traditional, complementary, and integrative medicine (TCIM) research. We introduce the concept of bibliometrics and altmetrics, provide an overview of the opportunities and challenges in using these analytical techniques, and highlight their future potential in TCIM research. Bibliometrics, based on publication and citation information, offer insights into TCIM research activity, output, scholarly influence, field structure, and collaboration practices. Altmetrics, including social media mentions, downloads, and online bookmarks, can capture the broader societal engagement with TCIM research beyond traditional academic circles. We discuss challenges and opportunities in utilizing these metrics effectively, such as addressing biases, incorporating cultural nuances, and exploring emerging trends. Additionally, we issue a call to action for researchers, policymakers, and practitioners to collaborate and leverage bibliometric and altmetric data to advance evidence-based healthcare practices to promote integrative approaches to health and wellness. By embracing a multidimensional approach to research evaluation, stakeholders can harness the potential of bibliometrics and altmetrics to improve TCIM research and healthcare delivery worldwide.

Indexed as

AltmetricBibliometricsComplementary medicineIntegrative medicineTraditional metrics

Identifiers

PMID40727710
PMCPMC12303004

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.