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Individual patient data meta-analysis of acupuncture for chronic pain: protocol of the Acupuncture Trialists' Collaboration

Overview of attention for article published in Trials, September 2010
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Title
Individual patient data meta-analysis of acupuncture for chronic pain: protocol of the Acupuncture Trialists' Collaboration
Published in
Trials, September 2010
DOI 10.1186/1745-6215-11-90
Pubmed ID
Authors

Andrew J Vickers, Angel M Cronin, Alexandra C Maschino, George Lewith, Hugh Macpherson, Norbert Victor, Karen J Sherman, Claudia Witt, Klaus Linde, the Acupuncture Trialists' Collaboration

Abstract

The purpose of clinical trials of acupuncture is to help clinicians and patients make decisions about treatment. Yet this is not straightforward: some trials report acupuncture to be superior to sham (placebo) acupuncture while others show evidence that acupuncture is superior to usual care but not sham, and still others conclude that acupuncture is no better than usual care. Meta-analyses of these trials tend to come to somewhat indeterminate conclusions. This appears to be because, until recently, acupuncture research was dominated by small trials of questionable quality. The Acupuncture Trialists' Collaboration, a group of trialists, statisticians and other researchers, was established to synthesize patient-level data from several recently published large, high-quality trials.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 2 1%
Norway 1 <1%
Italy 1 <1%
India 1 <1%
Brazil 1 <1%
Denmark 1 <1%
United States 1 <1%
Unknown 177 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 14%
Student > Master 24 13%
Student > Bachelor 22 12%
Student > Ph. D. Student 15 8%
Student > Doctoral Student 12 6%
Other 57 31%
Unknown 30 16%
Readers by discipline Count As %
Medicine and Dentistry 88 48%
Nursing and Health Professions 19 10%
Agricultural and Biological Sciences 10 5%
Social Sciences 7 4%
Psychology 6 3%
Other 21 11%
Unknown 34 18%