Format

Send to

Choose Destination
See comment in PubMed Commons below
Complement Ther Clin Pract. 2018 Feb;30:38-43. doi: 10.1016/j.ctcp.2017.12.002. Epub 2017 Dec 7.

Inter-expert agreement and similarity analysis of traditional diagnoses and acupuncture prescriptions in textbook- and pragmatic-based practices.

Author information

1
Laboratory of Computational Simulation and Modeling in Rehabilitation, Postgraduate Program in Rehabilitation Sciences, Augusto Motta University Center, Praça das Nações 34, Bonsucesso, Rio de Janeiro, RJ, 21041-010, Brazil.
2
Laboratory of Computational Simulation and Modeling in Rehabilitation, Postgraduate Program in Rehabilitation Sciences, Augusto Motta University Center, Praça das Nações 34, Bonsucesso, Rio de Janeiro, RJ, 21041-010, Brazil. Electronic address: arthurde@unisuamdoc.com.br.

Abstract

This study examined (1) the agreement of acupuncture experts with textbook prescriptions and among themselves, and (2) the association between similar traditional diagnoses and textbook acupuncture prescriptions, examining whether pragmatic practice (i.e., modifying prescriptions according to personal clinical practice) alters such an association. A computational analysis quantified the diagnosis-prescription association from a textbook. Eight acupuncture experts were independently interviewed. Experts modified the textbook prescriptions according to their pragmatic practice. Experts mostly agreed (19-90%) or strongly agreed (0-29%) with the textbook prescriptions, with no-better-than-chance agreement on their ratings (Light's κ = 0.036, CI95% = [0.003; 0.081]). The number of manifestations in traditional diagnoses weakly explains the variability (Spearman's ρ = 0.260, p = 0.038) of the number of acupoints in prescriptions. The association between similar traditional diagnoses and acupuncture prescriptions is strong in the textbook (γ = 0.720, CI95% = [0.658, 0.783]), whereas pragmatic practice had little effect on this association (γ = 0.724-0.769).

KEYWORDS:

Acupuncture; Complementary medicine; Medical education and training; Rehabilitation medicine; Statistics and research methods

PMID:
29389477
DOI:
10.1016/j.ctcp.2017.12.002
PubMed Commons home

PubMed Commons

0 comments

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Support Center