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Building a Collaborative Model of Sacroiliac Joint Dysfunction and Pelvic Girdle Pain to Understand the Diverse Perspectives of Experts
Author(s) -
Hodges Paul W.,
Cholewicki Jacek,
Popovich John M.,
Lee Angela S.,
Aminpour Payam,
Gray Steven A.,
Cibulka Michael T.,
Cusi Mel,
Degenhardt Brian F.,
Fryer Gary,
Gutke Annelie,
Kennedy David J.,
Laslett Mark,
Lee Diane,
Mens Jan,
Patel Vikas V.,
Prather Heidi,
Sturesson Bengt,
Stuge Brit,
Vleeming Andry
Publication year - 2019
Publication title -
pmandr
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 66
eISSN - 1934-1563
pISSN - 1934-1482
DOI - 10.1002/pmrj.12199
Subject(s) - metamodeling , medicine , conceptual model , thematic analysis , meta analysis , physical therapy , psychology , clinical psychology , computer science , qualitative research , pathology , social science , sociology , programming language , database
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.