Friday, September 28, 2018 8:00 AM–9:00 AM interdisciplinary spine forum: abstract presentations: 142. Integrating multidisciplinary knowledge of low back pain through collaborative modeling: results from the NASS think tank workshop

Abstract

BACKGROUND CONTEXT Low back pain (LBP) is a very complex problem with numerous bio-psycho-social factors interacting to impact pain, disability, and quality of life. To understand the dynamics of such a complex problem, it needs to be studied in its entirety (systems approach). Although this concept is accepted by the scientific and clinical communities, much research to date is conducted by specialized teams focusing on isolated factors related to LBP. Such a reductionist approach may be useful in some circumstances, but it also creates barriers for integrating knowledge between disciplines and ultimately precludes the understanding of the dynamics of the entire LBP problem. To leverage the knowledge shared among various stakeholders, an innovative process called collaborative modeling was developed within the field of systems science specifically for enhancing the understanding of complex, multifactorial systems dynamics. This study assessed the feasibility of using this approach for integrating multidisciplinary knowledge of LBP. METHODS Participants (n=29), who have contributed significant knowledge to the area of LBP (eg publications, contributions to societies, etc.), were selectively recruited for this study and represented diverse disciplines: Basic Science (n=7), Chiropractic (n=4), Spine Surgery (n=2), Physical Medicine & Rehabilitation (n=2), Physical or Exercise Therapy (n=12), and Psychology (n=2). Each participant underwent a structured one-on-one interview to construct a fuzzy-logic cognitive map (FCM) (Mental Modeler software, www.mentalmodeler.org ) representing his or her understanding of how factors related to LBP interact and affect patient outcomes (pain, disability and quality of life). All individual FCMs were then converted to adjacency matrices and integrated into one meta-model (Gephi software, www.gephi.org ). To demonstrate the integrated meta-model's potential, various intervention strategies listed in all FCMs were simulated and their relative effects on pain, disability, and quality of life were investigated. RESULTS The meta-model, that integrated the understanding of LBP of all participants, consisted of 272 factors and 1,429 connections representing interactions among these factors. Simulations of individual treatment interventions predicted that combined aerobic exercise, counseling, and education are likely to be the most effective intervention to reduce pain. Meditation, followed by cognitive behavioral therapy, had the greatest impact on reducing disability and improving quality of life. CONCLUSIONS The integration of 29 FCMs, representing diverse participants’ views of LBP dynamics, resulted in a model that was extremely complex, but still feasible to produce meaningful interpretations. The simulations provided outcomes that broadly agreed with data in the literature, which suggests that aerobic exercise, counseling, education, meditation, and cognitive behavioral therapy are effective LBP interventions. Although the selection of participants and the relatively small sample size may influence the results, the findings suggest that it is possible to integrate multidisciplinary knowledge of LBP into one meta-model. This approach could provide the framework for a larger, community-wide platform for further development and refinement of this meta-model. Such a meta-model could then be used to simulate other “what if” scenarios, to identify gaps in knowledge, and to inform new essential research directions to ultimately improve patient care and outcomes for LBP.