Evidence map›Paper›PMID 30949430›Full record

ReviewIntegrative medicine research2019

Treating the patient not the symptoms: Acupuncture to improve overall health - Evidence, acceptance and strategies.

Stephen Birch

Open access · goldAbstract readReview
In one paragraph

Review in Integrative medicine research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% of its field
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. 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

1 author at 1 institution in 1 country.

Stephen BirchDepartment of Health Sciences, Kristiania University College, Oslo, Norway.
Høyskolen Kristiania · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Documented mechanisms of acupuncture suggest the possibility of whole body effects in addition to local and regional effects. Traditional theories of acupuncture predict whole body effects. Does this permit the possibility of applying treatment to target overall health improvement of the patient rather than the symptom? After introducing the term 'health improvement' this paper explores situations where it might be advantageous to do this, giving examples of how health authorities in some countries have proposed broader treatment approaches that focus on health improvement. It also discusses cases where acupuncture has been recommended as a treatment method in a number of these proposals and gives some clinical examples of this kind of whole body 'health improvement' targeted treatment effects. Given that health authorities have already recognised this potential for the application of acupuncture the author then explores evidence of more whole-body 'health improvement' effects from systematic reviews and examples of health experts recommending acupuncture to take advantage of them. Research strategies and foci are then proposed and explored to develop this evidence. What are the best treatment approaches to create these effects? By what mechanisms can 'health improvement' be produced? How can one measure these effects? It is likely that treatments based on 'pattern identification' (PI) may provide the best strategies for producing 'health improvement', thus PI-based acupuncture treatments are likely to be the best strategy for clinical research investigating these effects.

Indexed as

AcupunctureHealthHealth improvementPattern identificationResearch

Identifiers

PMID30949430
PMCPMC6428918
OpenAlexW2887877096

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.