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Building a Collaborative Model of Sacroiliac Joint Dysfunction and Pelvic Girdle Pain to Understand the Diverse Perspectives of Experts

Journal article
Authors P. W. Hodges
J. Cholewicki
J. M. Popovich
A. S. Lee
P. Aminpour
S. A. Gray
M. T. Cibulka
M. Cusi
B. F. Degenhardt
G. Fryer
Annelie Gutke
D. J. Kennedy
M. Laslett
D. Lee
J. Mens
V. V. Patel
H. Prather
B. Sturesson
B. Stuge
A. Vleeming
Published in PM&R
Volume 11
Issue Suppl. 1
Pages S11-S23
ISSN 1934-1482
Publication year 2019
Published at Institute of Neuroscience and Physiology
Pages S11-S23
Language en
Links dx.doi.org/10.1002/pmrj.12199
Keywords low-back-pain, stabilizing exercises, pregnancy, diagnosis, efficacy, movements, validity, reduce, tests, Rehabilitation, Sport Sciences
Subject categories Sport and Fitness Sciences

Abstract

Background: Pelvic girdle pain (PGP) and sacroiliac joint (SIJ) dysfunction/pain are considered frequent contributors to low back pain (LBP). Like other persistent pain conditions, PGP is increasingly recognized as a multifactorial problem involving biological, psychological, and social factors. Perspectives differ between experts and a diversity of treatments (with variable degrees of evidence) have been utilized. Objective: To develop a collaborative model of PGP that represents the collective view of a group of experts. Specific goals were to analyze structure and composition of conceptual models contributed by participants, to aggregate them into a metamodel, to analyze the metamodel's composition, and to consider predicted efficacy of treatments. Design: To develop a collaborative model of PGP, models were generated by invited individuals to represent their understanding of PGP using fuzzy cognitive mapping (FCM). FCMs involved proposal of components related to causes, outcomes, and treatments for pain, disability, and quality of life, and their connections. Components were classified into thematic categories. Weighting of connections was summed for components to judge their relative importance. FCMs were aggregated into a metamodel for analysis of the collective opinion it represented and to evaluate expected efficacy of treatments. Results: From 21 potential contributors, 14 (67%) agreed to participate (representing six disciplines and seven countries). Participants' models included a mean (SD) of 22 (5) components each. FCMs were refined to combine similar terms, leaving 89 components in 10 categories. Biomechanical factors were the most important in individual FCMs. The collective opinion from the metamodel predicted greatest efficacy for injection, exercise therapy, and surgery for pain relief. Conclusions: The collaborative model of PGP showed a bias toward biomechanical factors. Most efficacious treatments predicted by the model have modest to no evidence from clinical trials, suggesting a mismatch between opinion and evidence. The model enables integration and communication of the collection of opinions on PGP.

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