Development of a collaborative model of low back pain: report from the 2017 NASS consensus meeting

Cholewicki, Jacek; Popovich, John M.; Aminpour, Payam; Gray, Steven; Lee, Angela S.; Hodges, Paul W.

doi:10.1016/j.spinee.2018.11.014

Cited by 22 publications

(26 citation statements)

References 24 publications

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“…This was done to enable aggregation of FCMs contributed by individual experts. The standardized terms were defined based on outcomes from several phases of consultations and a consensus meeting with the participants in the similar study concerning LBP . As a result of this process, the structure of the original FCMs (structural features such as the number of components and connections ) or composition (the issues represented by the components ) did not change, but the components with similar meaning in different FCMs were combined to form a smaller number of standardized unique terms (from the original 312 to 89).…”

Section: Methodsmentioning

confidence: 99%

“…Adapted from Cholewicki et al ICF = International Classification of Functioning, Disability and Health …”

Section: Methodsmentioning

confidence: 99%

“…First, the metamodel clusters all presentations of PGP together (eg, ankylosing spondylitis, pregnancy‐related conditions, and so on), and although specific treatments may be expected to be effective for specific groups, this cannot be reflected in this model. Second, we collapsed some similar terms from individual FCMs into a smaller group of components that were established via extensive consultation with experts (including some who participated in this study) during the development of a collaborative model of LBP . In some cases, the final terminology and grouping may require further consideration.…”

Section: Limitationsmentioning

confidence: 99%

“…Although the main objective of collaborative modeling is to synthesize and share knowledge, the analysis of the structure, composition, and functionality of FCM models enables identification of core assumptions, evaluation of the relative importance placed on different concepts and testing of various scenarios, such as the impact of a treatment. This approach has recently been used to build a collaborative model of LBP using opinions of a broad range of experts . The resultant model has highlighted that despite various disciplinary backgrounds of contributors, psychological features are considered to have the strongest importance in LBP.…”

Section: Introductionmentioning

confidence: 99%

“…This approach has recently been used to build a collaborative model of LBP using opinions of a broad range of experts. 22 The resultant model has highlighted that despite various disciplinary backgrounds of contributors, psychological features are considered to have the strongest importance in LBP.…”

Section: Introductionmentioning

confidence: 99%

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

Hodges

Cholewicki

Popovich

et al. 2019

PM&R

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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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Section: Methodsmentioning

confidence: 99%

“…Adapted from Cholewicki et al ICF = International Classification of Functioning, Disability and Health …”

Section: Methodsmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Hodges

Cholewicki

Popovich

et al. 2019

PM&R

Self Cite

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An exploration of knowledge‐organizing technologies to advance transdisciplinary back pain research

Lotz,

Ropella,

Anderson

et al. 2023

JOR Spine

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Chronic low back pain (LBP) is influenced by a broad spectrum of patient‐specific factors as codified in domains of the biopsychosocial model (BSM). Operationalizing the BSM into research and clinical care is challenging because most investigators work in silos that concentrate on only one or two BSM domains. Furthermore, the expanding, multidisciplinary nature of BSM research creates practical limitations as to how individual investigators integrate current data into their processes of generating impactful hypotheses. The rapidly advancing field of artificial intelligence (AI) is providing new tools for organizing knowledge, but the practical aspects for how AI may advance LBP research and clinical are beginning to be explored. The goals of the work presented here are to: (1) explore the current capabilities of knowledge integration technologies (large language models (LLM), similarity graphs (SGs), and knowledge graphs (KGs)) to synthesize biomedical literature and depict multimodal relationships reflected in the BSM, and; (2) highlight limitations, implementation details, and future areas of research to improve performance. We demonstrate preliminary evidence that LLMs, like GPT‐3, may be useful in helping scientists analyze and distinguish cLBP publications across multiple BSM domains and determine the degree to which the literature supports or contradicts emergent hypotheses. We show that SG representations and KGs enable exploring LBP's literature in novel ways, possibly providing, trans‐disciplinary perspectives or insights that are currently difficult, if not infeasible to achieve. The SG approach is automated, simple, and inexpensive to execute, and thereby may be useful for early‐phase literature and narrative explorations beyond one's areas of expertise. Likewise, we show that KGs can be constructed using automated pipelines, queried to provide semantic information, and analyzed to explore trans‐domain linkages. The examples presented support the feasibility for LBP‐tailored AI protocols to organize knowledge and support developing and refining trans‐domain hypotheses.

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Using artificial intelligence algorithms to identify existing knowledge within the back pain literature

et al. 2020

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Development of a collaborative model of low back pain: report from the 2017 NASS consensus meeting

Abstract: The North American Spine Society (NASS) covered the costs of the meeting. The authors are solely responsible for the contents of this publication and they do not necessarily represent the official views of NASS.

Cited by 22 publications

References 24 publications

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

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

An exploration of knowledge‐organizing technologies to advance transdisciplinary back pain research

Using artificial intelligence algorithms to identify existing knowledge within the back pain literature

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