Evidence map›Paper›PMID 41180281›Full record

ArticleBulletin of the World Health Organization2025

Data on the use of traditional and complementary medicine, WHO Region of the Americas.

Natalia Houghton, Herfina Nababan, Ernesto Bascolo

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Natalia HoughtonDepartment of Health Systems and Services, Pan American Health Organization, 525 23rd Street NW, WashingtonDC, 20037, United States of America.
Herfina NababanDepartment of Global Health, University of Bremen, Bremen, Germany.
Ernesto BascoloDepartment of Health Systems and Services, Pan American Health Organization, 525 23rd Street NW, WashingtonDC, 20037, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An understanding of the population-level data available on the use of traditional, complementary and integrative medicine is critical for reducing unmet health needs and improving health outcomes. Although research has shown that the existence of unmet health-care needs among people receiving conventional health care can drive the use of traditional medicine, the motivations for its use are complex and often related to cultural traditions, personal preferences and perceptions of effectiveness. At present, only limited population-based data are available on who uses traditional medicine, the reasons for its use, the context in which it is used (even when traditional medicine is a primary choice) and the outcomes of treatment. To address this data gap, we identified and analysed population-based surveys that reported data on traditional medicine use for perceived health problems in the World Health Organization's Region of the Americas. Based on the findings, we discuss how best to analyse available population-based survey data and how survey questions on traditional medicine can be refined to enhance their usefulness. Strengthened data collection on traditional medicine can inform health-care policy on the integration of traditional practices into the health system, aid efforts to educate both health-care providers and the public on traditional medicine, support culturally responsive and people-centred care, and foster the ethical and effective integration of traditional medicine into health systems.

Indexed as

Complementary TherapiesMedicine, TraditionalAdultAmericasFemaleHumansMaleWorld Health Organization

Identifiers

PMID41180281
PMCPMC12578536

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.