ArticleIntegrative medicine research2025
The case for data sharing in traditional, complementary, and integrative medicine research.
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 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Representing Traditional East Asian Medicine in International Health Informatics Standards: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional, complementary, and integrative medicine (TCIM) research encompasses a diverse range of health practices rooted in various cultural, philosophical, and historical frameworks. As global interest in conducting research in this field grows, the need for rigorous research to support the integration of evidence-based TCIM therapies into mainstream healthcare has become essential. Data sharing is critical to advancing TCIM research by enhancing reproducibility, fostering interdisciplinary collaboration, promoting ethical practices, and addressing global health challenges. Despite its benefits, numerous challenges are associated with data sharing in TCIM, including a lack of standardized practices, cultural sensitivity, intellectual property concerns, and technical barriers in resource-limited settings. This editorial explores the unique nature of TCIM research, emphasizing the importance of data sharing while acknowledging the complexities it entails. Implementing the CARE Principles for Indigenous Data Governance, which prioritize collective benefit, authority to control, responsibility, and ethics, offers a framework for ensuring that data sharing respects indigenous knowledge and cultural sensitivities. Strategies for overcoming barriers to data sharing include developing standardized protocols, investing in research infrastructure, and fostering a culture of openness and collaboration within the TCIM community and beyond. By advancing data sharing practices, TCIM research can contribute to evidence-based healthcare solutions and address global health disparities, ultimately improving health outcomes worldwide.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.