A meta-model of low back pain to examine collective expert knowledge of the effects of treatments and their mechanisms

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Although personalized treatment is advocated, clear guidance on tailoring interventions is lacking. To help address this gap, we synthesized expert knowledge on treatment effectiveness and underlying mechanisms using a systems-based, collaborative modeling approach. Methods Twenty-nine experts from diverse disciplines created individual fuzzy cognitive maps (FCMs) to represent their understanding of factors affecting pain, disability, and quality of life (QoL), along with treatment mechanisms. These maps were aggregated into a meta-model comprising 142 Components and 1,161 weighted Connections. Centrality was used to identify the most central domains of the meta-model. Simulations with the meta-model based on expert knowledge 1) estimated the relative effectiveness of treatments on pain, disability, and QoL and 2) identified key Mediators and mediating Domains based on their relative contribution to mediating treatment effects. Results Psychological, biomechanical, and social/contextual Domains were central to expert conceptualizations of LBP. Simulation indicated cognitive behavioral therapy was considered the most effective among all interventions. Most interventions were mediated by Components across multiple Domains, with psychological factors frequently serving as mediators. The conceptual meta-model underscored the complexity of LBP, reflecting both its multifactorial nature and the diversity of expert perspectives on factors related to treatment effectiveness. Conclusion The developed meta-model provides a novel, systems-based representation of expert knowledge about LBP, enabling quantitative exploration of treatment effects and underlying mechanisms. This conceptual framework also offers a foundation for advancing research on multi-modal, personalized care. Figures Figure 1 Figure 2 Introduction Multiple biological, psychological, and social factors contribute to low back pain (LBP) [ 1 – 4 ]. This complexity likely underlies the limited progress in reducing the high prevalence of LBP and its impact on disability and quality of life (QoL) [ 5 , 6 ]. No single treatment or simple solution alleviates LBP across all individuals. Heterogeneity in patient responses results in small-to-moderate average treatment effects frequently reported in clinical trials [ 7 – 10 ]. It is reasonable to consider a multimodal approach addressing the biological, psychological, and social contributors to LBP [ 11 , 12 ]. However, systematic reviews show only marginal benefits of multimodal over unimodal treatments [ 13 , 14 ]. A key limitation is the lack of clear guidance on how to tailor multimodal treatment for individual patients - a core principle of "personalized" medicine. Diverse opinions on how to implement personalization have further hindered progress [ 15 – 18 ]. Efforts to address LBP complexity and heterogeneity have included the use of machine learning and "big data" to identify patient phenotypes and match them with multimodal interventions specific to each phenotype [ 19 , 20 ]. These efforts have yielded mixed results, highlighting the challenges of translating phenotypic classifications into effective, personalized care [ 21 ]. A critical step toward improving treatment personalization is the development of a thorough understanding of the factors driving LBP, how these factors interact, and the mechanisms of interventions for LBP. There have been calls for the development of comprehensive, state-of-the-art models of LBP to identify knowledge gaps, guide research, and better understand LBP dynamics [ 4 , 22 ]. Chau et al. [ 4 ] describe such models as "conceptual representations, mental models, or patterns of knowledge" about LBP. Systems science provides tools for addressing complex, multifactorial problems. One approach, “collaborative modeling", integrates diverse interest holder perspectives and has been validated in environmental management to support decision-making [ 23 , 24 ]. We applied this approach to examine individual expert opinions on LBP, treatment effectiveness and mechanisms [ 2 ]. Clinical and research experts identified key contributing factors and modeled their interactions using fuzzy cognitive maps (FCMs) [ 25 ]. These FCMs provided a quantitative description of how experts conceptualize LBP, i.e., mental models [ 2 ]. Here we aimed to: (i) aggregate individual FCMs into a single meta-model representing collective expert knowledge, and (ii) use this meta-model to simulate and compare treatment effectiveness and underlying mechanistic pathways, with the goal of informing future research on personalized LBP management. Methods Part 1: Building the meta-model The meta-model was constructed by aggregating individual FCMs previously collected from experts in LBP. The detailed methodology for obtaining these FCMs is described elsewhere [ 2 ]. Briefly, 29 clinicians and researchers with expertise in LBP (e.g., publications, contributions to professional societies [ 2 ]) participated. They represented diverse disciplines (basic science (n = 7), chiropractic (n = 4), spine surgery (n = 2), physical medicine & rehabilitation (n = 2), physical/exercise therapy (n = 12), and psychology (n = 2)), including those active in research and clinical practice. Each participant completed a structured interview to construct an FCM using the Mental Modeler platform ( www.mentalmodeler.org ) [ 26 ]. These FCMs captured the participants' conceptual understanding (mental model) of factors involved in LBP, their interactions, and the effects of various interventions on patient-reported primary Outcomes (Pain, Disability, QoL). Participants listed all relevant factors (Components), identified relationships (Connections) between them, and assigned Weights (from − 1 to 1) to indicate the direction and strength of each Connection. Participants also listed all treatments (Treatments/Interventions) they believed could affect Outcomes and mapped out the experts’ knowledge of pathways of their effects (Connections and Weights). After refining and consolidating similar terms, a total of 147 unique Components from the 29 FCMs were categorized into ten Domains based on the International Classification of Diseases (ICD) framework [ 27 ]: (1) Outcomes, (2) Behavioral/Lifestyle, (3) Biomechanical, (4) Individual, (5) Comorbidities, (6) Tissue injury or pathology, (7) Psychological, (8) Nociceptive detection and processing, (9) Social/Work/Contextual factors, and (10) Treatment/Intervention. Further refinement of terms in the present study reduced the total to 142 Components (Online Resource 1 outlines minor changes from our previous study). For this study, each participant's FCM was transformed into a 142×142 adjacency matrix to standardize dimensions and to include the weighting of the connections between the 142 unique Components identified across all models. Instead of leaving missing values, Connections not specified by a participant were assigned a weight of zero, indicating the participant did not consider the connection meaningful. In the absence of data to weigh the credibility of individual FCMs, a simple averaging method, including zeros, was used to aggregate the matrices [ 28 , 29 ]. The aggregated adjacency matrix was imported into Gephi 0.10.1 ( https://gephi.org ) [ 30 ] for visualization. Table 1 shows metrics computed to describe the meta-model’s structure. Table 1 Metrics describing structure of the meta-model. Metric Definition Total Components (N) Number of Components included the meta-model Total Connections (C) Total number of Connections in either direction included in the meta-model Density (D) Number of Connections as a proportion of the number of all possible Connections in both directions Connections per Component Average number of Connections in either direction per Component Number of Driver Components Total number of Components that only have outputs Number of Receiver Components Total number of Components that only have inputs Number of Ordinary Components Number of Components with both inputs and outputs Complexity Score Calculated as the ratio of Receiver/Driver Components and provides a measure of the degree to which effects of Drivers are considered Centrality of Domains Calculated as a sum of the absolute values of all Connections in and out of all Components classified into a given Domain Part 2: Evaluating the relative effects of treatments To evaluate the relative effects of treatments on pain, disability, and QoL, we conducted simulations using the meta-model and a custom Python-based software employing a sigmoid transfer function (PyFCM [ 31 ], Python Software Foundation, www.python.org ). Each Treatment/Intervention was independently initialized to a state value of 1. The state of each Component was then iteratively updated by propagating the initial input through the meta-model network, based on Connection Weights and the transfer function, until all values converged to a steady state [ 32 ]. Final state values of the outcome Components (Pain, Disability, QoL) were then recorded. These simulation results should be interpreted in relative terms (i.e., ordinal ranking), as the chosen transfer function was selected to ensure model convergence rather than to represent exact relationships between Components [ 33 ]. Part 3: Examining mechanisms mediating treatment effects To explore the mechanisms underlying each treatment, we identified the Components and Domains that served as primary Mediators between treatments and outcomes. Although Treatments/Interventions may affect outcomes through complex pathways involving multiple intermediary Components, our analysis focused on first-level (direct) Connections from Treatments/Interventions to other Components to identify primary Mediators of treatment effects. For each Treatment/Intervention, the Component (excluding Outcomes) with the highest absolute Connection weight was the primary Mediator. To determine the most influential Domain mediating each treatment, we summed the absolute Weights of all direct Connections from Treatments/Interventions to Mediators within Domains. These sums were used to rank the Domains by their relative contribution to mediating treatment effects. Results Part 1: Building the meta-model The meta-model had 142 Components including 3 representing the primary Outcomes (Pain, Disability, QoL) and 37 representing Treatments/Interventions (Table 2 ). There were 1,161 Connections (interactions) between Components, underscoring the complexity of LBP and the breadth of expert perspectives. The meta-model's structure reflects the expert group's collective understanding of LBP (Fig. 1 A, also available in high resolution and as an adjacency matrix in Online Resources 2 and 3). For clarity, Outcomes are at the meta-model’s center with Treatments/Interventions at the periphery. Component and Connection colors represent the Domains. The size of each circle reflects the Component’s Centrality. The three Domains with the highest Centrality were Psychological, Social/Work/Contextual, and Biomechanical (Fig. 1 B), indicating that Components and Connections within these Domains were most strongly emphasized by participants. Table 2 Summary of meta-model parameters describing its structure. Parameter Meta-model value Total Components (N) 142 Total Connections (C) 1161 Density (D) 0.058 Connections per Component 8.176 Number of Driver Components 50 Number of Receiver Components 0 Number of Ordinary Components 92 Complexity Score 0 Part 2: Evaluating the relative effects of treatments on outcomes Simulation of treatment scenarios identified the most effective interventions based on collective expert opinion. Although treatment rankings varied slightly across Outcomes, treatments combined under the heading of cognitive behavioral therapy (CBT) were consistently ranked as the most effective for improving pain, disability, and QoL (Table 3 ). Pain medication was second for reducing pain, whereas exercise therapy ranked second for reducing disability and improving QoL. Other top-ranked treatments included physical treatment, posture and movement training, advice/education, and acceptance and commitment therapy, though their relative effectiveness varied by Outcomes. The least effective treatments were either proposed by few participants, perceived as having limited effectiveness or viewed as beneficial only for specific patient subgroups. Table 3 Simulation results, using the meta-model based on the experts' knowledge of LBP, showing the relative effectiveness of Treatments/Interventions for each Outcome: Pain, Disability, and Quality of Life (QoL). Treatments/Interventions are ranked from most to least effective. Results are presented on an ordinal scale, as the numerical values reflect rankings only and should not be interpreted as interval magnitudes of effects. Rank Pain Disability Quality of Life 1 Cognitive behavioral therapy Cognitive behavioral therapy Cognitive behavioral therapy 2 Pain medication Exercise therapy Exercise therapy 3 Physical treatment Advice/Education Acceptance and commitment therapy 4 Exercise therapy Physical treatment Posture and movement training 5 Posture and movement training Posture and movement training Advice/Education 6 Acceptance and commitment therapy Spinal manipulation/Manual therapy Physical treatment 7 Advice/Education Acceptance and commitment therapy Spinal manipulation/Manual therapy 8 Spinal manipulation/Manual therapy Spinal surgery Nutritional counseling 9 Spinal surgery Multidisciplinary treatments (biopsychosocial treatments) Biopsychosocial risk management 10 Pain relieving intervention Pain relieving intervention Spinal surgery 11 Acupuncture Biopsychosocial risk management Pain relieving intervention 12 Massage Treatment of addiction Treatment of addiction 13 Multidisciplinary treatments (biopsychosocial treatments) Graded activity Sleep restoration 14 Anti-inflammatory medication Psychological intervention Acupuncture 15 Biopsychosocial risk management Pain medication Graded activity 16 Nutritional counseling Nutritional counseling Massage 17 Sleep restoration Sleep restoration Multidisciplinary treatments (biopsychosocial treatments) 18 Graded activity Weight loss Pain medication 19 Treatment of addiction Wait and see (monitoring) Weight loss 20 Psychological intervention Acupuncture Psychological intervention 21 Spinal injections Massage Public health/ Occupational interventions 22 Anti-epileptic and anti-depressant drugs Spinal stimulators Anti-epileptic and anti-depressant drugs 23 Weight loss Complementary treatments Anti-inflammatory medication 24 Spinal stimulators Anti-inflammatory medication Spinal injections 25 Slow movement and stretching (e.g., yoga) Anti-epileptic and anti-depressant drugs Slow movement and stretching (e.g., yoga) 26 Complementary treatments Public health/ Occupational interventions Wait and see (monitoring) 27 Wait and see (monitoring) Spinal injections Spinal stimulators 28 Denervation interventions Slow movement and stretching (e.g., yoga) Complementary treatments 29 Public health/ Occupational interventions Social intervention Social intervention 30 Medication (biologicals) Ergonomic interventions Relaxation 31 Social intervention Relaxation Motivational interviewing 32 Taping and braces Denervation interventions Ergonomic interventions 33 Relaxation Motivational interviewing Denervation interventions 34 Ergonomic interventions Ultrasound biofeedback training Ultrasound biofeedback training 35 Motivational interviewing Medication (biologicals) Medication (biologicals) 36 Ultrasound biofeedback training Taping and braces Taping and braces 37 Dry needling Dry needling Dry needling Part 3: Examining the mechanisms mediating effects of treatments There were 317 Connections between Treatments/Interventions and their Mediators (Online Resource 4). Table 4 lists the highest-ranked Mediator and the highest-ranked mediating Domain for each Treatment/Intervention. Generally, the highest-ranked Mediator belonged to the highest-ranked mediating Domain. However, there were exceptions. For example, the primary Mediator for spinal manipulation was reduced unhealthy expectations, beliefs, and perceptions concerning pain – Psychological Component – despite the Biomechanical Domain being highest ranked for this treatment. Table 4 Top-ranked Mediator Components and top-ranked mediating Domains for each Treatment/Intervention, listed alphabetically. In the event of ties, multiple Mediators or Domains are listed. The results are derived from the meta-model based on collective expert knowledge. Treatment/ Intervention Mediator Direction of Effect Mediating Domain Acceptance and commitment therapy Emotional (e.g., distress, anxiety, depression) Decrease Psychological Acupuncture Tissue damage Decrease Tissue injury or pathology Advice/Education Cognitive (e.g., expectations, beliefs, perceptions concerning pain) Decrease Psychological Anti-epileptic and anti-depressant drugs Emotional (e.g., distress, anxiety, depression) Decrease Psychological Anti-inflammatory medication Inflammation Decrease Tissue injury or pathology Biopsychosocial risk management Evidence based care pathway Decrease Social/Work/Contextual factors Cognitive behavioral therapy Emotional (e.g., distress, anxiety, depression) Decrease Psychological Complementary treatments Positive psychological factors Increase Psychological Denervation interventions Neurological pain generation Decrease Nociceptive detection and processing Dry needling Optimal motor control Increase Biomechanical Ergonomic interventions Negative life social factors Decrease Social/Work/Contextual factors Exercise therapy Negative biological factors (e.g., postural control, genetics, tissue damage, central sensitization) AND Good paraspinal muscle quality Decrease Increase Biomechanical Graded activity Autonomy Increase Social/Work/Contextual factors Massage Tissue damage Decrease Tissue injury or pathology Medication (biologicals) Inflammation Decrease Tissue injury or pathology Motivational interviewing Negative psychological factors AND Negative biological factors (e.g., postural control, genetics, tissue damage, central sensitization) Decrease Decrease Psychological AND Nociceptive detection and processing Multidisciplinary treatments (biopsychosocial treatments) Tissue damage Decrease Tissue injury or pathology Nutritional counseling Positive psychological factors Increase Individual factors Pain medication Negative sensory input Decrease Nociceptive detection and processing Pain relieving intervention Physiological risks Decrease Psychological Physical treatment Motor impairment Decrease Psychological Posture and movement training Cognitive (e.g., expectations, beliefs, perceptions concerning pain) Decrease Biomechanical Psychological intervention Emotional (e.g., distress, anxiety, depression) Decrease Psychological Public health/ occupational interventions General health Increase Social/Work/Contextual factors Relaxation Negative psychological factors Decrease Psychological Sleep restoration Overweight (obesity/BMI) AND Physiological risks Decrease Decrease Comorbidities AND Individual factors Slow movement and stretching (e.g., yoga) Emotional (e.g., distress, anxiety, depression) Decrease Psychological Social intervention Negative life social factors Decrease Social/Work/Contextual factors Spinal injections Neurological pain generation Decrease Nociceptive detection and processing Spinal manipulation/ Manual therapy Cognitive (e.g., expectations, beliefs, perceptions concerning pain) Decrease Biomechanical Spinal stimulators Neurological pain generation Decrease Nociceptive detection and processing Spinal surgery Disc herniation Decrease Tissue injury or pathology Taping and braces Negative sensory input Decrease Nociceptive detection and processing Treatment of addiction Physiological risks Decrease Individual factors Ultrasound biofeedback training Optimal motor control Increase Biomechanical Wait and see (monitoring) N/A N/A N/A Weight loss Overweight (obesity/BMI) Decrease Comorbidities Figure 2 illustrates the relative contribution of each Domain to mediation of treatment effects. For most treatments, Mediators spanned multiple Domains. For example, exercise therapy involved Mediators from all domains with a slight emphasis on Biomechanical Components. In contrast, interventions such as complementary treatments and denervation procedures had more focused pathways, with Mediators arising exclusively from a single Domain: Psychological and Nociceptive detection and processing, respectively. Discussion This study developed a meta-model that synthesizes the diverse perspectives of a multidisciplinary group of LBP experts. The model reflects a shared view of LBP as a complex condition involving numerous contributing factors across eight Domains, a broad range of treatments, and many potential mechanisms by which treatments influence clinical outcomes. This meta-model offers a tool to inform future research to advance the development of personalized LBP care. Complexity of LBP Constructed using a collaborative modeling approach, the meta-model reinforces the well-established understanding that LBP is highly complex [ 1 , 3 , 34 ] and that expert opinions differ, likely reflecting disciplinary backgrounds, research and clinical experiences [ 4 ]. A key advantage of our approach is that it synthesizes this diversity into a coherent framework. Unlike narrative or systematic reviews, which describe complexity qualitatively and propose strategies to address it [ 1 , 3 , 34 ], our meta-model enables simulations of hypothetical scenarios, offering a novel means to inform research on personalized LBP treatment. Related efforts include a meta-model derived from perspectives of people with lived experience of LBP [ 35 ] and another focused on sacroiliac joint (SIJ) pain [ 36 ]. The patient-derived model was substantially simpler and emphasized biomechanical factors, contrasting expert meta-model’s emphasis on psychological factors. Patients favored non-surgical, non-pharmacological, physical treatments (e.g., exercise therapy, and slow movement and stretching), whereas the expert model identified CBT as the most effective treatment. The SIJ model was more biomechanically oriented and emphasized injections or surgery, although exercise was also recognized as beneficial [ 36 ]. Relative effects of treatments Simulations produced treatment rankings that broadly align with published clinical data [ 37 , 38 ], supporting the effectiveness of interventions such as CBT [ 39 ], exercise therapy [ 40 ], acceptance and commitment therapy [ 41 ], counseling and education [ 42 , 43 ], and physical therapy [ 44 ] for managing LBP. General agreement between the expert-derived model and evidence-based recommendations is reassuring. It also underscores the value of incorporating expert opinion into evidence-based practice, particularly in areas where high-quality empirical data are limited [ 45 ]. By synthesizing perspectives across multiple disciplines, this collaborative meta-model facilitates decision-making processes and offers a more balanced and comprehensive foundation for clinical guideline development than reliance on individual expert views alone [ 46 – 48 ]. Treatments combined under the heading of CBT were ranked the most effective treatments for pain, disability, and QoL. CBT's effects in the meta-model were mediated primarily through psychological factors. Key mediators of CBT included emotional factors such as distress, anxiety and depression, which many consider to be main contributors to pain behavior [ 49 – 51 ]. CBT's effectiveness across pain, disability and QoL is reasonable given they are interrelated to some extent [ 52 ]. Mediators of treatment effects The meta-model enabled investigation into how treatment effects are mediated to influence outcomes. Most treatments operated through Mediators spanning multiple Domains, suggesting the involvement of multiple mechanisms of action. Psychological Mediators appeared in the pathways of nearly all interventions, which is unsurprising given that the Psychological Domain exhibited the highest Centrality in our meta-model. These findings underscore the overlap in mechanistic pathways across treatments, which may help explain why combining interventions often yields limited additional benefit for LBP [ 13 , 14 ]. Future research could use this model to examine specific mediating pathways and identify unique features to guide personalized treatment strategies. Limitations Several limitations should be acknowledged. First, we treated missing Connections as zeroes. This assumes participants omitted them because they believed the connections had no effect. Although this approach reduces the influence of uncommon or idiosyncratic opinions, it may attenuate some plausible Connections unintentionally omitted. Second, this meta-model does not account for different presentations of LBP (e.g., different time courses and different diagnoses) and cannot reflect differences in treatment effectiveness based on patient phenotypes. Third, the participant group included a high proportion of physical therapists, potentially biasing the model toward that discipline’s perspectives. Fourth, although this study focused on expert input, incorporating perspectives from individuals with lived experience is increasingly recognized as essential in collaborative research. We have separately collected mental models from these individuals [ 35 ], which can be compared with the current expert-driven meta-model. Fifth, the Connection Weights are based entirely on expert opinion rather than empirical data. One application of this meta-model is to identify knowledge gaps and generate hypotheses to test these opinions. Sixth, despite extensive consultation and careful model aggregation [ 2 ], some terms or Domain assignments may not perfectly reflect participants’ original intentions. Seventh, simulation results are affected by the number of Connections between a treatment and its outcome. Each intervening Connection decreases the state of the subsequent Component based on the assigned weight - treatments with longer or more complex pathways might appear less effective than those with direct pathways to outcomes. Eighth, it is possible that knowledge of experts has increased or changed since the FCMs were collected. Future directions A general objective of this work was to support the development of personalized LBP care. Progress towards this goal must overcome two barriers: (i) precise determination of an individual's phenotype could be difficult because of the unique interplay among many contributing factors in each case, making phenotyping infeasible, and (ii) the possibility of tailoring intervention to match an individual phenotype could be limited, because current treatments for LBP are mediated through multiple overlapping pathways without the necessary precision. Nevertheless, this meta-model can help prioritize research efforts by: (i) identifying high-impact mediators and pathways to optimize treatment combinations for further evaluation, and (ii) highlighting key relationships (Connections) that require empirical data for their precise weighting. Future model enhancements could include the following. First, additional FCMs could be included. Although it might be assumed that additional participants would strengthen the meta-model, it is not clear that > 30 provides additional value [ 53 ]. One exception would be the inclusion of under-represented disciplines that might provide additional treatments and alternative understanding of mechanisms. Second, "big data" could be sought to provide objective Weights for the Connections, as outlined in the theoretical framework by Huie et al. [ 54 ] and attempted by Zhu et al. [ 55 ]. Third, future work could convert this meta-model into a dynamic one [ 56 , 57 ], capturing the time-dependency of treatment effects (e.g., acute vs. chronic LBP) and accounting for changes in certain factors during over the course of this condition. This approach was applied to investigate dynamics between opioid use and chiropractic care for chronic pain [ 58 ]. Fourth, repeating this modeling approach may reveal evolving views among experts and patients [ 59 ]. Conclusion This study presents a systems-based meta-model that synthesizes expert knowledge of LBP, offering a novel framework for exploring the relative effectiveness of treatments and their mechanisms. The model highlights the complexity of LBP, underscores the role of psychological factors, and identifies CBT as a broadly effective intervention across primary outcomes. Although the current model is not designed to establish causal relationships, it provides a valuable foundation for hypothesis generation, empirical testing, and the development of personalized LBP treatments. This model could be used for education and training, communicating with patients, and facilitating interdisciplinary discussion and collaboration. Declarations Competing Interests G.L.M. has received support from: Reality Health, ConnectHealth UK, Institutes of Health California, AIA Australia, Workers’ Compensation Boards and professional sporting organizations in Australia, Europe, South and North America. Professional and scientific bodies have reimbursed him for travel costs related to presentation of research on pain and pain education at scientific conferences/symposia. He has received speaker fees for lectures on pain, pain education and rehabilitation. He receives royalties for books on pain and pain education. He is non-paid CEO of the non-profit Pain Revolution. S.Z.G. receives support from the American Physical Therapy Association in the form of honoraria and travel for his Editor-in-Chief role. J.W.S.V. is supported by the Asthenes research program “From Acute Aversive Sensations to Chronic Bodily Symptoms,” a long-term structural Methusalem funding (METH/15/011) by the Flemish government, Belgium. P.W.H., G.L.M. and M.L.F. were funded by a Leadership Investigator grants from National Health and Medical Research Council (NHMRC) of Australia (1194937; 1178444; 2007741, respectively). L.R.V. was funded by a grant from the National Institutes of Health (NIH R01 HD047709). Author Contribution J.C., P.W.H., and J.M.P. conceptualized and designed the study, and wrote the first draft of the manuscript. Material preparation, data collection and analysis were performed by P.A., S.A.G., and A.S.L. All authors contributed to providing, organizing and classifying the data, and participated in the interpretation of the results. All authors, except the deceased G.N.K., edited earlier versions of the manuscript, and approved its final content. Resources and funding were acquired by P.W.H. and H.P. Data Availability The data are provided in the Online Resource files. References Hartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, Hoy D, Karppinen J, Pransky G, Sieper J, Smeets RJ, Underwood M, Lancet Low Back Pain Series Working G (2018) What low back pain is and why we need to pay attention. Lancet 391:2356–2367. 10.1016/S0140-6736(18)30480-X Cholewicki J, Popovich JM Jr., Aminpour P, Gray SA, Lee AS, Hodges PW (2019) Development of a collaborative model of low back pain: Report from the 2017 nass consensus meeting. Spine J 19:1029–1040. 10.1016/j.spinee.2018.11.014 O'Sullivan P, Caneiro JP, O'Keeffe M, O'Sullivan K (2016) Unraveling the complexity of low back pain. J Orthop Sports Phys Ther 46:932–937. 10.2519/jospt.2016.0609 Chau A, Steib S, Whitaker E, Kohns D, Quinter A, Craig A, Chiodo A, Chandran S, Laidlaw A, Schott Z, Farlow N, Yarjanian J, Omwanghe A, Wasserman R, O'Neill C, Clauw D, Bowden A, Marras W, Carey T, Mehling W, Hunt CA, Lotz J (2023) Theoretical schemas to guide back pain consortium (bacpac) chronic low back pain clinical research. Pain Med 24:S13–S35. 10.1093/pm/pnac196 Cholewicki J, Pathak PK, Reeves NP, Popovich JM Jr (2019) Model simulations challenge reductionist research approaches to studying chronic low back pain. J Orthop Sports Phys Ther 49:477–481. 10.2519/jospt.2019.8791 Foster NE (2011) Barriers and progress in the treatment of low back pain. BMC Med 9:108. 10.1186/1741-7015-9-108 Hancock MJ, Hill JC (2016) Are small effects for back pain interventions really surprising? J Orthop Sports Phys Ther 46:317–319. 10.2519/jospt.2016.0604 Keller A, Hayden J, Bombardier C, van Tulder M (2007) Effect sizes of non-surgical treatments of non-specific low-back pain. Eur Spine J 16:1776–1788. 10.1007/s00586-007-0379-x Machado LA, Kamper SJ, Herbert RD, Maher CG, McAuley JH (2009) Analgesic effects of treatments for non-specific low back pain: A meta-analysis of placebo-controlled randomized trials. Rheumatology (Oxford) 48:520–527. 10.1093/rheumatology/ken470 Vlaeyen JWS, Milde C (2025) The precarious use of group data to understand individual processes in pain science. Pain 166:1721–1722. 10.1097/j.pain.0000000000003574 Flor H, Noguchi K, Treede RD, Turk DC (2023) The role of evolving concepts and new technologies and approaches in advancing pain research, management, and education since the establishment of the international association for the study of pain. Pain 164:S16–S21. 10.1097/j.pain.0000000000003063 Pincus T, Kent P, Bronfort G, Loisel P, Pransky G, Hartvigsen J (2013) Twenty-five years with the biopsychosocial model of low back pain-is it time to celebrate? A report from the twelfth international forum for primary care research on low back pain. Spine 38:2118–2123. 10.1097/BRS.0b013e3182a8c5d6 Chou R, Huffman LH (2007) Nonpharmacologic therapies for acute and chronic low back pain: A review of the evidence for an american pain society/american college of physicians clinical practice guideline. Ann Intern Med 147:492–504 Kamper SJ, Apeldoorn AT, Chiarotto A, Smeets RJ, Ostelo RW, Guzman J, van Tulder MW (2015) Multidisciplinary biopsychosocial rehabilitation for chronic low back pain: Cochrane systematic review and meta-analysis. BMJ 350:h444. 10.1136/bmj.h444 Foster NE, Hill JC, Hay EM (2011) Subgrouping patients with low back pain in primary care: Are we getting any better at it? Man Ther 16:3–8. 10.1016/j.math.2010.05.013 Saragiotto BT, Maher CG, Hancock MJ, Koes BW (2017) Subgrouping patients with nonspecific low back pain: Hope or hype? J Orthop Sports Phys Ther 47:44–48. 10.2519/jospt.2017.0602 Hodges PW (2019) Hybrid approach to treatment tailoring for low back pain: A proposed model of care. J Orthop Sports Phys Ther 49:453–463. 10.2519/jospt.2019.8774 Chiodo AF, Haley M (2024) Does risk stratification with a matched treatment pathway improve clinical outcomes for adults with acute back pain? A systematic review and meta-analysis. Braz J Phys Ther 28:101116. 10.1016/j.bjpt.2024.101116 Hue TF, Lotz JC, Zheng P, Black DM, Bailey J, Ewing SK, Fields AJ, Mehling W, Scheffler A, Strigo I, Petterson T, Wu LA, O'Neill C, Ucsf Reach Center tCCfP-CMPiCLBP (2024) Design of the comeback and backhome studies, longitudinal cohorts for comprehensive deep phenotyping of adults with chronic low-back pain (clbp): A part of the bacpac research program. medRxiv. 10.1101/2024.04.09.24305574 Quirk DA, Johnson ME, Anderson DE, Smuck M, Sun R, Matthew R, Bailey J, Marras WS, Bell KM, Darwin J, Bowden AE (2023) Biomechanical phenotyping of chronic low back pain: Protocol for bacpac. Pain Med 24:S48–S60. 10.1093/pm/pnac163 Tagliaferri SD, Angelova M, Zhao X, Owen PJ, Miller CT, Wilkin T, Belavy DL (2020) Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: Three systematic reviews. NPJ Digit Med 3:93. 10.1038/s41746-020-0303-x Mauck MC, Lotz J, Psioda MA, Carey TS, Clauw DJ, Majumdar S, Marras WS, Vo N, Aylward A, Hoffmeyer A, Zheng P, Ivanova A, McCumber M, Carson C, Anstrom KJ, Bowden AE, Dalton D, Derr L, Dufour J, Fields AJ, Fritz J, Hassett AL, Harte SE, Hue TF, Krug R, Loggia ML, Mageswaran P, McLean SA, Mitchell UH, O'Neill C, Pedoia V, Quirk DA, Rhon DI, Rieke V, Shah L, Sowa G, Spiegel B, Wasan AD, Wey HM, LaVange L (2023) The back pain consortium (bacpac) research program: Structure, research priorities, and methods. Pain Med 24:S3–S12. 10.1093/pm/pnac202 Gray S, Paolisso M, Jordan R, Gray S (2018) Environmental modeling with stakeholders: Theory, methods, and applications. In. Springer, Cham Gray S, Chan A, Clark D, Jordan R (2012) Modeling the integration of stakeholder knowledge in social–ecological decision-making: Benefits and limitations to knowledge diversity. Ecol Model 229:88–96. 10.1016/j.ecolmodel.2011.09.011 Gray SA, Zanre E, Gray SRJ (2014) Fuzzy cognitive maps as representations of mental models and group beliefs. In: Papageorgiou EI (ed) Fuzzy cognitive maps for applied sciences and engineering: From fundamentals to extensions and learning algorithms. Springer, Berlin Heidelberg, Berlin, Heidelberg, pp 29–48 Gray SA, Gray S, Cox LJ, Henly-Shepard S (2013) Mental modeler: A fuzzy-logic cognitive mapping modeling tool for adaptive environmental management. In: 46th Hawaii International Conference on System Sciences (HICSS), 2013 IEEE, Wailea, Maui, HI. pp. 965–973 WHO (2001) International classification of functioning, disability and health (icf). World Health Organization, Geneva Kosko B (1988) Hidden patterns in combined and adaptive knowledge networks. Int J Approx Reason 2:337–393 Stach W (2010) Learning and aggregation of fuzzy cognitive maps - an evolutionary approach. University of Alberta Bastian M, Heymann S, Jacomy M (2009) Gephi: An open source software for exploring and manipulating networks. In: Proceedings of the international AAAI conference on web and social media. pp. 361–362 Aminpour P (2018) Pyfcm: Python for fuzzy cognitive mapping. https://github.com/payamaminpour/PyFCM/wiki . Accessed October 3, 2018 Iakovidis DK, Papageorgiou E (2011) Intuitionistic fuzzy cognitive maps for medical decision making. IEEE Trans Inf Technol Biomed 15:100–107. 10.1109/TITB.2010.2093603 Kok K (2009) The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from brazil. Glob Environ Change 19:122–133. https://doi.org/10.1016/j.gloenvcha.2008.08.003 Hush JM (2020) Low back pain: It is time to embrace complexity. Pain 161:2248–2251. 10.1097/j.pain.0000000000001933 Hodges PW, Setchell J, Daniel E, Fowler M, Lee AS, Popovich JM Jr., Cholewicki J (2022) How individuals with low back pain conceptualize their condition: A collaborative modeling approach. J Pain 23:1060–1070. 10.1016/j.jpain.2021.12.014 Hodges PW, Cholewicki J, Popovich JM Jr., Lee AS, Aminpour P, Gray SA, Cibulka MT, Cusi M, Degenhardt BF, Fryer G, Gutke A, Kennedy DJ, Laslett M, Lee D, Mens J, Patel VV, Prather H, Sturesson B, Stuge B, Vleeming A (2019) Building a collaborative model of sacroiliac joint dysfunction and pelvic girdle pain to understand the diverse perspectives of experts. PM R 11(Suppl 1):S11–S23. 10.1002/pmrj.12199 Foster NE, Anema JR, Cherkin D, Chou R, Cohen SP, Gross DP, Ferreira PH, Fritz JM, Koes BW, Peul W, Turner JA, Maher CG, Group LLBPSW (2018) Prevention and treatment of low back pain: Evidence, challenges, and promising directions. Lancet 391:2368–2383. 10.1016/S0140-6736(18)30489-6 Mauck MC, Aylward AF, Barton CE, Birckhead B, Carey T, Dalton DM, Fields AJ, Fritz J, Hassett AL, Hoffmeyer A, Jones SB, McLean SA, Mehling WE, O'Neill CW, Schneider MJ, Williams DA, Zheng P, Wasan AD (2022) Evidence-based interventions to treat chronic low back pain: Treatment selection for a personalized medicine approach. Pain Rep 7:e1019. 10.1097/PR9.0000000000001019 Ho EK, Chen L, Simic M, Ashton-James CE, Comachio J, Wang DXM, Hayden JA, Ferreira ML, Ferreira PH (2022) Psychological interventions for chronic, non-specific low back pain: Systematic review with network meta-analysis. BMJ 376:e067718. 10.1136/bmj-2021-067718 Hayden JA, Wilson MN, Stewart S, Cartwright JL, Smith AO, Riley RD, van Tulder M, Bendix T, Cecchi F, Costa LOP, Dufour N, Ferreira ML, Foster NE, Gudavalli MR, Hartvigsen J, Helmhout P, Kool J, Koumantakis GA, Kovacs FM, Kuukkanen T, Long A, Macedo LG, Machado LAC, Maher CG, Mehling W, Morone G, Peterson T, Rasmussen-Barr E, Ryan CG, Sjogren T, Smeets R, Staal JB, Unsgaard-Tondel M, Wajswelner H, Yeung EW, Chronic Low Back Pain IPDM-AG (2020) Exercise treatment effect modifiers in persistent low back pain: An individual participant data meta-analysis of 3514 participants from 27 randomised controlled trials. Br J Sports Med 54:1277–1278. 10.1136/bjsports-2019-101205 Hughes LS, Clark J, Colclough JA, Dale E, McMillan D (2017) Acceptance and commitment therapy (act) for chronic pain: A systematic review and meta-analyses. Clin J Pain 33:552–568. 10.1097/AJP.0000000000000425 Wood L, Hendrick PA (2019) A systematic review and meta-analysis of pain neuroscience education for chronic low back pain: Short-and long-term outcomes of pain and disability. Eur J Pain 23:234–249. 10.1002/ejp.1314 Puri BK, Theodoratou M (2023) The efficacy of psychoeducation in managing low back pain: A systematic review. Psychiatriki 34:231–242. 10.22365/jpsych.2022.104 Severijns P, Goossens N, Dankaerts W, Pitance L, Roussel N, Denis C, Fourre A, Verschueren P, Timmermans A, Janssens L (2024) Physiotherapy-led care versus physician-led care for persons with low back pain: A systematic review. Clin Rehabil:2692155241282987. 10.1177/02692155241282987 Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS (1996) Evidence based medicine: What it is and what it isn't. BMJ 312:71–72. 10.1136/bmj.312.7023.71 Aminpour P, Gray SA, Singer A, Scyphers SB, Jetter AJ, Jordan R, Murphy R Jr, Grabowski JH (2021) The diversity bonus in pooling local knowledge about complex problems. Proceedings of the National Academy of Sciences 118:e2016887118 Giabbanelli PJ, Knox CB, Furman K, Jetter A, Gray S (2024) Defining and using fuzzy cognitive mapping. In: Fuzzy cognitive maps: Best practices and modern methods. Springer. pp. 1–18 Amirkhani A, Papageorgiou EI, Mohseni A, Mosavi MR (2017) A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications. Comput Methods Programs Biomed 142:129–145. 10.1016/j.cmpb.2017.02.021 Vlaeyen JWS, Linton SJ (2000) Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. Pain 85:317–332. 10.1016/S0304-3959(99)00242-0 Leeuw M, Goossens ME, Linton SJ, Crombez G, Boersma K, Vlaeyen JW (2007) The fear-avoidance model of musculoskeletal pain: Current state of scientific evidence. J Behav Med 30:77–94. 10.1007/s10865-006-9085-0 Scholich SL, Hallner D, Wittenberg RH, Hasenbring MI, Rusu AC (2012) The relationship between pain, disability, quality of life and cognitive-behavioural factors in chronic back pain. Disabil Rehabil 34:1993–2000. 10.3109/09638288.2012.667187 Mutubuki EN, Beljon Y, Maas ET, Huygen F, Ostelo R, van Tulder MW, van Dongen JM (2020) The longitudinal relationships between pain severity and disability versus health-related quality of life and costs among chronic low back pain patients. Qual Life Res 29:275–287. 10.1007/s11136-019-02302-w Özesmi U, Özesmi SL (2004) Ecological models based on people’s knowledge: A multi-step fuzzy cognitive mapping approach. Ecol Model 176:43–64 Huie JR, Vashisht R, Galivanche A, Hadjadj C, Morshed S, Butte AJ, Ferguson AR, O'Neill C (2022) Toward a causal model of chronic back pain: Challenges and opportunities. Front Comput Neurosci 16:1017412. 10.3389/fncom.2022.1017412 Zhu ZY, Shan HH, Wang J, Zhu HJ, Liu SG, Lin F (2024) Graph modeling of relational structures among functioning variables with low back pain: An exploratory analysis based on international classification of functioning, disability and health. Eur J Phys Rehabil Med 60:487–495. 10.23736/S1973-9087.24.08089-4 Friston KJ, Harrison L, Penny W (2003) Dynamic causal modelling. NeuroImage 19:1273–1302. 10.1016/s1053-8119(03)00202-7 Luke DA, Stamatakis KA (2012) Systems science methods in public health: Dynamics, networks, and agents. Annu Rev Public Health 33:357–376. 10.1146/annurev-publhealth-031210-101222 McGregor M, Nielsen A, Chung C, Fillery MD, Wakeland W, Mior S (2019) System dynamics to investigate opioid use and chiropractic care for chronic musculoskeletal pain. J Manipulative Physiol Ther 42:237–246. 10.1016/j.jmpt.2018.11.007 Langevin HM (2024) Addressing gaps in pain research from an integrated whole person perspective. Pain 165:S23–S32. 10.1097/j.pain.0000000000003359 Additional Declarations Competing interest reported. G.L.M. has received support from: Reality Health, ConnectHealth UK, Institutes of Health California, AIA Australia, Workers’ Compensation Boards and professional sporting organizations in Australia, Europe, South and North America. Professional and scientific bodies have reimbursed him for travel costs related to presentation of research on pain and pain education at scientific conferences/symposia. He has received speaker fees for lectures on pain, pain education and rehabilitation. He receives royalties for books on pain and pain education. He is non-paid CEO of the non-profit Pain Revolution. S.Z.G. receives support from the American Physical Therapy Association in the form of honoraria and travel for his Editor-in-Chief role. J.W.S.V. is supported by the Asthenes research program “From Acute Aversive Sensations to Chronic Bodily Symptoms,” a long-term structural Methusalem funding (METH/15/011) by the Flemish government, Belgium. P.W.H., G.L.M. and M.L.F. were funded by a Leadership Investigator grants from National Health and Medical Research Council (NHMRC) of Australia (1194937; 1178444; 2007741, respectively). L.R.V. was funded by a grant from the National Institutes of Health (NIH R01 HD047709). Supplementary Files ESM1MetamodelChanges.docx ESM2MetamodelHDFigure.svg ESM3MetamodelMatrix.xls ESM4TreatmentMediators.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Nov, 2025 Reviews received at journal 12 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 03 Nov, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 18 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviewers invited by journal 16 Oct, 2025 Editor assigned by journal 15 Oct, 2025 Submission checks completed at journal 15 Oct, 2025 First submitted to journal 13 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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10:53:46","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":172320,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/c532ce012da8197085b4124d.html"},{"id":94754510,"identity":"f97ebf44-181f-4f3e-8b74-72f5485c0b97","added_by":"auto","created_at":"2025-10-30 10:53:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":448664,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Meta-model representing expert knowledge of LBP. Outcomes (Pain, Disability and Quality of Life) are shown in the center, while Treatments/Interventions are displayed around the periphery. Circle size is proportional to Component Centrality, and Colors indicate the ten Domains based on the ICD framework. (B) Relative Centrality of each Domain (excluding Outcomes and Treatments/Interventions), calculated as the sum of Centrality of all Components within the Domain, and expressed as a percentage of total model Centrality.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/e84f914d23a74d563f7cb5b1.png"},{"id":94754501,"identity":"18711c22-5af0-4226-8bbb-70e2a78ee52a","added_by":"auto","created_at":"2025-10-30 10:53:44","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1183510,"visible":true,"origin":"","legend":"\u003cp\u003eRelative contribution of each Domain to the mediation of treatment effects. For each Treatment/Intervention, the absolute Weights of Connections to Mediators were summed within each Domain and expressed as a proportion of the total Weight of all mediating Connections across Domains (excluding direct Treatment/Intervention-Outcome Connections).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/e73388382b0e22fdd9eb6c5c.jpeg"},{"id":94827163,"identity":"9c3a75a7-7f33-4bc8-9060-15faddf91c7c","added_by":"auto","created_at":"2025-10-31 06:55:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2708899,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/723a1cce-3b65-4a1a-a53b-275a60adaed7.pdf"},{"id":94754514,"identity":"fa314551-359f-49f0-8fde-e674cf7f6d15","added_by":"auto","created_at":"2025-10-30 10:53:44","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":35356,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1MetamodelChanges.docx","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/f720d90fffde7869bc00dcc4.docx"},{"id":94754517,"identity":"d28f44a5-1130-44cf-abc3-1d362ec72e23","added_by":"auto","created_at":"2025-10-30 10:53:45","extension":"svg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":871640,"visible":true,"origin":"","legend":"","description":"","filename":"ESM2MetamodelHDFigure.svg","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/9794899a2fd8fd96d1b3fa22.svg"},{"id":94754529,"identity":"63ea6328-ce6d-46be-b974-ac77a99ec377","added_by":"auto","created_at":"2025-10-30 10:53:46","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":188416,"visible":true,"origin":"","legend":"","description":"","filename":"ESM3MetamodelMatrix.xls","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/9c0935233daddb61068cca69.xls"},{"id":94754533,"identity":"70d97c2f-6d1a-440b-9fc8-fc4d87cdc63a","added_by":"auto","created_at":"2025-10-30 10:53:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":37641,"visible":true,"origin":"","legend":"","description":"","filename":"ESM4TreatmentMediators.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7844247/v1/8bcb9a99a8de8aaf456dfc15.xlsx"}],"financialInterests":"Competing interest reported. G.L.M. has received support from: Reality Health, ConnectHealth UK, Institutes of Health California, AIA Australia, Workers’ Compensation Boards and professional sporting organizations in Australia, Europe, South and North America. Professional and scientific bodies have reimbursed him for travel costs related to presentation of research on pain and pain education at scientific conferences/symposia. He has received speaker fees for lectures on pain, pain education and rehabilitation. He receives royalties for books on pain and pain education. He is non-paid CEO of the non-profit Pain Revolution. S.Z.G. receives support from the American Physical Therapy Association in the form of honoraria and travel for his Editor-in-Chief role. J.W.S.V. is supported by the Asthenes research program “From Acute Aversive Sensations to Chronic Bodily Symptoms,” a long-term structural Methusalem funding (METH/15/011) by the Flemish government, Belgium. P.W.H., G.L.M. and M.L.F. were funded by a Leadership Investigator grants from National Health and Medical Research Council (NHMRC) of Australia (1194937; 1178444; 2007741, respectively). L.R.V. was funded by a grant from the National Institutes of Health (NIH R01 HD047709).","formattedTitle":"A meta-model of low back pain to examine collective expert knowledge of the effects of treatments and their mechanisms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultiple biological, psychological, and social factors contribute to low back pain (LBP) [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This complexity likely underlies the limited progress in reducing the high prevalence of LBP and its impact on disability and quality of life (QoL) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. No single treatment or simple solution alleviates LBP across all individuals. Heterogeneity in patient responses results in small-to-moderate average treatment effects frequently reported in clinical trials [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIt is reasonable to consider a multimodal approach addressing the biological, psychological, and social contributors to LBP [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, systematic reviews show only marginal benefits of multimodal over unimodal treatments [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A key limitation is the lack of clear guidance on how to tailor multimodal treatment for individual patients - a core principle of \"personalized\" medicine. Diverse opinions on how to implement personalization have further hindered progress [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEfforts to address LBP complexity and heterogeneity have included the use of machine learning and \"big data\" to identify patient phenotypes and match them with multimodal interventions specific to each phenotype [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These efforts have yielded mixed results, highlighting the challenges of translating phenotypic classifications into effective, personalized care [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A critical step toward improving treatment personalization is the development of a thorough understanding of the factors driving LBP, how these factors interact, and the mechanisms of interventions for LBP. There have been calls for the development of comprehensive, state-of-the-art models of LBP to identify knowledge gaps, guide research, and better understand LBP dynamics [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Chau et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] describe such models as \"conceptual representations, mental models, or patterns of knowledge\" about LBP.\u003c/p\u003e\u003cp\u003eSystems science provides tools for addressing complex, multifactorial problems. One approach, \u0026ldquo;collaborative modeling\", integrates diverse interest holder perspectives and has been validated in environmental management to support decision-making [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. We applied this approach to examine individual expert opinions on LBP, treatment effectiveness and mechanisms [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Clinical and research experts identified key contributing factors and modeled their interactions using fuzzy cognitive maps (FCMs) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These FCMs provided a quantitative description of how experts conceptualize LBP, i.e., mental models [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Here we aimed to: (i) aggregate individual FCMs into a single meta-model representing collective expert knowledge, and (ii) use this meta-model to simulate and compare treatment effectiveness and underlying mechanistic pathways, with the goal of informing future research on personalized LBP management.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePart 1: Building the meta-model\u003c/h2\u003e\u003cp\u003eThe meta-model was constructed by aggregating individual FCMs previously collected from experts in LBP. The detailed methodology for obtaining these FCMs is described elsewhere [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Briefly, 29 clinicians and researchers with expertise in LBP (e.g., publications, contributions to professional societies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]) participated. They represented diverse disciplines (basic science (n\u0026thinsp;=\u0026thinsp;7), chiropractic (n\u0026thinsp;=\u0026thinsp;4), spine surgery (n\u0026thinsp;=\u0026thinsp;2), physical medicine \u0026amp; rehabilitation (n\u0026thinsp;=\u0026thinsp;2), physical/exercise therapy (n\u0026thinsp;=\u0026thinsp;12), and psychology (n\u0026thinsp;=\u0026thinsp;2)), including those active in research and clinical practice. Each participant completed a structured interview to construct an FCM using the Mental Modeler platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mentalmodeler.org\" target=\"_blank\"\u003ewww.mentalmodeler.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.mentalmodeler.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These FCMs captured the participants' conceptual understanding (mental model) of factors involved in LBP, their interactions, and the effects of various interventions on patient-reported primary Outcomes (Pain, Disability, QoL). Participants listed all relevant factors (Components), identified relationships (Connections) between them, and assigned Weights (from \u0026minus;\u0026thinsp;1 to 1) to indicate the direction and strength of each Connection. Participants also listed all treatments (Treatments/Interventions) they believed could affect Outcomes and mapped out the experts\u0026rsquo; knowledge of pathways of their effects (Connections and Weights).\u003c/p\u003e\u003cp\u003eAfter refining and consolidating similar terms, a total of 147 unique Components from the 29 FCMs were categorized into ten Domains based on the International Classification of Diseases (ICD) framework [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]: (1) Outcomes, (2) Behavioral/Lifestyle, (3) Biomechanical, (4) Individual, (5) Comorbidities, (6) Tissue injury or pathology, (7) Psychological, (8) Nociceptive detection and processing, (9) Social/Work/Contextual factors, and (10) Treatment/Intervention. Further refinement of terms in the present study reduced the total to 142 Components (Online Resource 1 outlines minor changes from our previous study).\u003c/p\u003e\u003cp\u003eFor this study, each participant's FCM was transformed into a 142\u0026times;142 adjacency matrix to standardize dimensions and to include the weighting of the connections between the 142 unique Components identified across all models. Instead of leaving missing values, Connections not specified by a participant were assigned a weight of zero, indicating the participant did not consider the connection meaningful. In the absence of data to weigh the credibility of individual FCMs, a simple averaging method, including zeros, was used to aggregate the matrices [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The aggregated adjacency matrix was imported into Gephi 0.10.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gephi.org\u003c/span\u003e\u003cspan address=\"https://gephi.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] for visualization. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows metrics computed to describe the meta-model\u0026rsquo;s structure.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMetrics describing structure of the meta-model.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetric\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDefinition\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Components (N)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Components included the meta-model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Connections (C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal number of Connections in either direction included in the meta-model\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDensity (D)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Connections as a proportion of the number of all possible Connections in both directions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConnections per Component\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAverage number of Connections in either direction per Component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Driver Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal number of Components that only have outputs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Receiver Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal number of Components that only have inputs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Ordinary Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Components with both inputs and outputs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplexity Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCalculated as the ratio of Receiver/Driver Components and provides a measure of the degree to which effects of Drivers are considered\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentrality of Domains\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCalculated as a sum of the absolute values of all Connections in and out of all Components classified into a given Domain\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePart 2: Evaluating the relative effects of treatments\u003c/h3\u003e\n\u003cp\u003eTo evaluate the relative effects of treatments on pain, disability, and QoL, we conducted simulations using the meta-model and a custom Python-based software employing a sigmoid transfer function (PyFCM [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Python Software Foundation, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mentalmodeler.org\" target=\"_blank\"\u003ewww.python.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.python.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Each Treatment/Intervention was independently initialized to a state value of 1. The state of each Component was then iteratively updated by propagating the initial input through the meta-model network, based on Connection Weights and the transfer function, until all values converged to a steady state [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Final state values of the outcome Components (Pain, Disability, QoL) were then recorded. These simulation results should be interpreted in relative terms (i.e., ordinal ranking), as the chosen transfer function was selected to ensure model convergence rather than to represent exact relationships between Components [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003ePart 3: Examining mechanisms mediating treatment effects\u003c/h3\u003e\n\u003cp\u003eTo explore the mechanisms underlying each treatment, we identified the Components and Domains that served as primary Mediators between treatments and outcomes. Although Treatments/Interventions may affect outcomes through complex pathways involving multiple intermediary Components, our analysis focused on first-level (direct) Connections from Treatments/Interventions to other Components to identify primary Mediators of treatment effects. For each Treatment/Intervention, the Component (excluding Outcomes) with the highest absolute Connection weight was the primary Mediator. To determine the most influential Domain mediating each treatment, we summed the absolute Weights of all direct Connections from Treatments/Interventions to Mediators within Domains. These sums were used to rank the Domains by their relative contribution to mediating treatment effects.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003ePart 1: Building the meta-model\u003c/h2\u003e\u003cp\u003eThe meta-model had 142 Components including 3 representing the primary Outcomes (Pain, Disability, QoL) and 37 representing Treatments/Interventions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There were 1,161 Connections (interactions) between Components, underscoring the complexity of LBP and the breadth of expert perspectives. The meta-model's structure reflects the expert group's collective understanding of LBP (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, also available in high resolution and as an adjacency matrix in Online Resources 2 and 3). For clarity, Outcomes are at the meta-model\u0026rsquo;s center with Treatments/Interventions at the periphery. Component and Connection colors represent the Domains. The size of each circle reflects the Component\u0026rsquo;s Centrality. The three Domains with the highest Centrality were Psychological, Social/Work/Contextual, and Biomechanical (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), indicating that Components and Connections within these Domains were most strongly emphasized by participants.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of meta-model parameters describing its structure.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMeta-model value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Components (N)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Connections (C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1161\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDensity (D)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConnections per Component\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Driver Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Receiver Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Ordinary Components\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplexity Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e\u003c/h2\u003e\u003c/div\u003e\n\u003ch3\u003ePart 2: Evaluating the relative effects of treatments on outcomes\u003c/h3\u003e\n\u003cp\u003eSimulation of treatment scenarios identified the most effective interventions based on collective expert opinion. Although treatment rankings varied slightly across Outcomes, treatments combined under the heading of cognitive behavioral therapy (CBT) were consistently ranked as the most effective for improving pain, disability, and QoL (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Pain medication was second for reducing pain, whereas exercise therapy ranked second for reducing disability and improving QoL. Other top-ranked treatments included physical treatment, posture and movement training, advice/education, and acceptance and commitment therapy, though their relative effectiveness varied by Outcomes. The least effective treatments were either proposed by few participants, perceived as having limited effectiveness or viewed as beneficial only for specific patient subgroups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSimulation results, using the meta-model based on the experts' knowledge of LBP, showing the relative effectiveness of Treatments/Interventions for each Outcome: Pain, Disability, and Quality of Life (QoL). Treatments/Interventions are ranked from most to least effective. Results are presented on an ordinal scale, as the numerical values reflect rankings only and should not be interpreted as interval magnitudes of effects.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisability\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQuality of Life\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCognitive behavioral therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCognitive behavioral therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCognitive behavioral therapy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePain medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExercise therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExercise therapy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdvice/Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcceptance and commitment therapy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExercise therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePhysical treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePosture and movement training\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePosture and movement training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePosture and movement training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdvice/Education\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcceptance and commitment therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpinal manipulation/Manual therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePhysical treatment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdvice/Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcceptance and commitment therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpinal manipulation/Manual therapy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpinal manipulation/Manual therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpinal surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNutritional counseling\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpinal surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultidisciplinary treatments (biopsychosocial treatments)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiopsychosocial risk management\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePain relieving intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePain relieving intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpinal surgery\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcupuncture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBiopsychosocial risk management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePain relieving intervention\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMassage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTreatment of addiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTreatment of addiction\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultidisciplinary treatments (biopsychosocial treatments)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGraded activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSleep restoration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnti-inflammatory medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePsychological intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcupuncture\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBiopsychosocial risk management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePain medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGraded activity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNutritional counseling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNutritional counseling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMassage\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSleep restoration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSleep restoration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMultidisciplinary treatments (biopsychosocial treatments)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGraded activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWeight loss\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePain medication\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreatment of addiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWait and see (monitoring)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWeight loss\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePsychological intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcupuncture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological intervention\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpinal injections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMassage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePublic health/ Occupational interventions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnti-epileptic and anti-depressant drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpinal stimulators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAnti-epileptic and anti-depressant drugs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeight loss\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eComplementary treatments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAnti-inflammatory medication\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpinal stimulators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnti-inflammatory medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpinal injections\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlow movement and stretching (e.g., yoga)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnti-epileptic and anti-depressant drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSlow movement and stretching (e.g., yoga)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eComplementary treatments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePublic health/ Occupational interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWait and see (monitoring)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWait and see (monitoring)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpinal injections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpinal stimulators\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenervation interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlow movement and stretching (e.g., yoga)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eComplementary treatments\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePublic health/ Occupational interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSocial intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial intervention\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedication (biologicals)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eErgonomic interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelaxation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRelaxation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMotivational interviewing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTaping and braces\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDenervation interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eErgonomic interventions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRelaxation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMotivational interviewing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDenervation interventions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eErgonomic interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUltrasound biofeedback training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUltrasound biofeedback training\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMotivational interviewing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedication (biologicals)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMedication (biologicals)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUltrasound biofeedback training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTaping and braces\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTaping and braces\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDry needling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry needling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDry needling\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003ePart 3: Examining the mechanisms mediating effects of treatments\u003c/h3\u003e\n\u003cp\u003eThere were 317 Connections between Treatments/Interventions and their Mediators (Online Resource 4). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e lists the highest-ranked Mediator and the highest-ranked mediating Domain for each Treatment/Intervention. Generally, the highest-ranked Mediator belonged to the highest-ranked mediating Domain. However, there were exceptions. For example, the primary Mediator for spinal manipulation was reduced unhealthy expectations, beliefs, and perceptions concerning pain \u0026ndash; Psychological Component \u0026ndash; despite the Biomechanical Domain being highest ranked for this treatment.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop-ranked Mediator Components and top-ranked mediating Domains for each Treatment/Intervention, listed alphabetically. In the event of ties, multiple Mediators or Domains are listed. The results are derived from the meta-model based on collective expert knowledge.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment/ Intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMediator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDirection of Effect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMediating Domain\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcceptance and commitment therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmotional (e.g., distress, anxiety, depression)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcupuncture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTissue damage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdvice/Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCognitive (e.g., expectations, beliefs, perceptions concerning pain)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-epileptic and anti-depressant drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmotional (e.g., distress, anxiety, depression)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-inflammatory medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInflammation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiopsychosocial risk management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvidence based care pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial/Work/Contextual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive behavioral therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmotional (e.g., distress, anxiety, depression)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplementary treatments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive psychological factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDenervation interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeurological pain generation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDry needling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOptimal motor control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiomechanical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eErgonomic interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative life social factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial/Work/Contextual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExercise therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative biological factors (e.g., postural control, genetics, tissue damage, central sensitization)\u003c/p\u003e\u003cp\u003eAND\u003c/p\u003e\u003cp\u003eGood paraspinal muscle quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiomechanical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGraded activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutonomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial/Work/Contextual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMassage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTissue damage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedication (biologicals)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInflammation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotivational interviewing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative psychological factors\u003c/p\u003e\u003cp\u003eAND\u003c/p\u003e\u003cp\u003eNegative biological factors (e.g., postural control, genetics, tissue damage, central sensitization)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003cp\u003eAND\u003c/p\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultidisciplinary treatments (biopsychosocial treatments)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTissue damage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNutritional counseling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive psychological factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndividual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePain medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative sensory input\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePain relieving intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysiological risks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMotor impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePosture and movement training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCognitive (e.g., expectations, beliefs, perceptions concerning pain)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiomechanical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmotional (e.g., distress, anxiety, depression)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic health/ occupational interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeneral health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial/Work/Contextual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelaxation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative psychological factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep restoration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight (obesity/BMI)\u003c/p\u003e\u003cp\u003eAND\u003c/p\u003e\u003cp\u003ePhysiological risks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eComorbidities\u003c/p\u003e\u003cp\u003eAND\u003c/p\u003e\u003cp\u003eIndividual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlow movement and stretching (e.g., yoga)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmotional (e.g., distress, anxiety, depression)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative life social factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSocial/Work/Contextual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpinal injections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeurological pain generation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpinal manipulation/ Manual therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCognitive (e.g., expectations, beliefs, perceptions concerning pain)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiomechanical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpinal stimulators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeurological pain generation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpinal surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisc herniation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue injury or pathology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTaping and braces\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative sensory input\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNociceptive detection and processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment of addiction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysiological risks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndividual factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUltrasound biofeedback training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOptimal motor control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiomechanical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWait and see (monitoring)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight loss\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight (obesity/BMI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eComorbidities\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the relative contribution of each Domain to mediation of treatment effects. For most treatments, Mediators spanned multiple Domains. For example, exercise therapy involved Mediators from all domains with a slight emphasis on Biomechanical Components. In contrast, interventions such as complementary treatments and denervation procedures had more focused pathways, with Mediators arising exclusively from a single Domain: Psychological and Nociceptive detection and processing, respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study developed a meta-model that synthesizes the diverse perspectives of a multidisciplinary group of LBP experts. The model reflects a shared view of LBP as a complex condition involving numerous contributing factors across eight Domains, a broad range of treatments, and many potential mechanisms by which treatments influence clinical outcomes. This meta-model offers a tool to inform future research to advance the development of personalized LBP care.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eComplexity of LBP\u003c/h2\u003e\u003cp\u003eConstructed using a collaborative modeling approach, the meta-model reinforces the well-established understanding that LBP is highly complex [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and that expert opinions differ, likely reflecting disciplinary backgrounds, research and clinical experiences [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A key advantage of our approach is that it synthesizes this diversity into a coherent framework. Unlike narrative or systematic reviews, which describe complexity qualitatively and propose strategies to address it [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], our meta-model enables simulations of hypothetical scenarios, offering a novel means to inform research on personalized LBP treatment.\u003c/p\u003e\u003cp\u003eRelated efforts include a meta-model derived from perspectives of people with lived experience of LBP [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and another focused on sacroiliac joint (SIJ) pain [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The patient-derived model was substantially simpler and emphasized biomechanical factors, contrasting expert meta-model\u0026rsquo;s emphasis on psychological factors. Patients favored non-surgical, non-pharmacological, physical treatments (e.g., exercise therapy, and slow movement and stretching), whereas the expert model identified CBT as the most effective treatment. The SIJ model was more biomechanically oriented and emphasized injections or surgery, although exercise was also recognized as beneficial [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eRelative effects of treatments\u003c/h2\u003e\u003cp\u003eSimulations produced treatment rankings that broadly align with published clinical data [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], supporting the effectiveness of interventions such as CBT [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], exercise therapy [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], acceptance and commitment therapy [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], counseling and education [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], and physical therapy [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] for managing LBP. General agreement between the expert-derived model and evidence-based recommendations is reassuring. It also underscores the value of incorporating expert opinion into evidence-based practice, particularly in areas where high-quality empirical data are limited [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. By synthesizing perspectives across multiple disciplines, this collaborative meta-model facilitates decision-making processes and offers a more balanced and comprehensive foundation for clinical guideline development than reliance on individual expert views alone [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTreatments combined under the heading of CBT were ranked the most effective treatments for pain, disability, and QoL. CBT's effects in the meta-model were mediated primarily through psychological factors. Key mediators of CBT included emotional factors such as distress, anxiety and depression, which many consider to be main contributors to pain behavior [\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. CBT's effectiveness across pain, disability and QoL is reasonable given they are interrelated to some extent [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eMediators of treatment effects\u003c/h2\u003e\u003cp\u003eThe meta-model enabled investigation into how treatment effects are mediated to influence outcomes. Most treatments operated through Mediators spanning multiple Domains, suggesting the involvement of multiple mechanisms of action. Psychological Mediators appeared in the pathways of nearly all interventions, which is unsurprising given that the Psychological Domain exhibited the highest Centrality in our meta-model. These findings underscore the overlap in mechanistic pathways across treatments, which may help explain why combining interventions often yields limited additional benefit for LBP [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Future research could use this model to examine specific mediating pathways and identify unique features to guide personalized treatment strategies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eSeveral limitations should be acknowledged. First, we treated missing Connections as zeroes. This assumes participants omitted them because they believed the connections had no effect. Although this approach reduces the influence of uncommon or idiosyncratic opinions, it may attenuate some plausible Connections unintentionally omitted. Second, this meta-model does not account for different presentations of LBP (e.g., different time courses and different diagnoses) and cannot reflect differences in treatment effectiveness based on patient phenotypes. Third, the participant group included a high proportion of physical therapists, potentially biasing the model toward that discipline\u0026rsquo;s perspectives. Fourth, although this study focused on expert input, incorporating perspectives from individuals with lived experience is increasingly recognized as essential in collaborative research. We have separately collected mental models from these individuals [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], which can be compared with the current expert-driven meta-model. Fifth, the Connection Weights are based entirely on expert opinion rather than empirical data. One application of this meta-model is to identify knowledge gaps and generate hypotheses to test these opinions. Sixth, despite extensive consultation and careful model aggregation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], some terms or Domain assignments may not perfectly reflect participants\u0026rsquo; original intentions. Seventh, simulation results are affected by the number of Connections between a treatment and its outcome. Each intervening Connection decreases the state of the subsequent Component based on the assigned weight - treatments with longer or more complex pathways might appear less effective than those with direct pathways to outcomes. Eighth, it is possible that knowledge of experts has increased or changed since the FCMs were collected.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eFuture directions\u003c/h2\u003e\u003cp\u003eA general objective of this work was to support the development of personalized LBP care. Progress towards this goal must overcome two barriers: (i) precise determination of an individual's phenotype could be difficult because of the unique interplay among many contributing factors in each case, making phenotyping infeasible, and (ii) the possibility of tailoring intervention to match an individual phenotype could be limited, because current treatments for LBP are mediated through multiple overlapping pathways without the necessary precision. Nevertheless, this meta-model can help prioritize research efforts by: (i) identifying high-impact mediators and pathways to optimize treatment combinations for further evaluation, and (ii) highlighting key relationships (Connections) that require empirical data for their precise weighting.\u003c/p\u003e\u003cp\u003eFuture model enhancements could include the following. First, additional FCMs could be included. Although it might be assumed that additional participants would strengthen the meta-model, it is not clear that \u0026gt;\u0026thinsp;30 provides additional value [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. One exception would be the inclusion of under-represented disciplines that might provide additional treatments and alternative understanding of mechanisms. Second, \"big data\" could be sought to provide objective Weights for the Connections, as outlined in the theoretical framework by Huie et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] and attempted by Zhu et al. [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Third, future work could convert this meta-model into a dynamic one [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], capturing the time-dependency of treatment effects (e.g., acute vs. chronic LBP) and accounting for changes in certain factors during over the course of this condition. This approach was applied to investigate dynamics between opioid use and chiropractic care for chronic pain [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Fourth, repeating this modeling approach may reveal evolving views among experts and patients [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents a systems-based meta-model that synthesizes expert knowledge of LBP, offering a novel framework for exploring the relative effectiveness of treatments and their mechanisms. The model highlights the complexity of LBP, underscores the role of psychological factors, and identifies CBT as a broadly effective intervention across primary outcomes. Although the current model is not designed to establish causal relationships, it provides a valuable foundation for hypothesis generation, empirical testing, and the development of personalized LBP treatments. This model could be used for education and training, communicating with patients, and facilitating interdisciplinary discussion and collaboration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eG.L.M. has received support from: Reality Health, ConnectHealth UK, Institutes of Health California, AIA Australia, Workers\u0026rsquo; Compensation Boards and professional sporting organizations in Australia, Europe, South and North America. Professional and scientific bodies have reimbursed him for travel costs related to presentation of research on pain and pain education at scientific conferences/symposia. He has received speaker fees for lectures on pain, pain education and rehabilitation. He receives royalties for books on pain and pain education. He is non-paid CEO of the non-profit Pain Revolution. S.Z.G. receives support from the American Physical Therapy Association in the form of honoraria and travel for his Editor-in-Chief role. J.W.S.V. is supported by the Asthenes research program \u0026ldquo;From Acute Aversive Sensations to Chronic Bodily Symptoms,\u0026rdquo; a long-term structural Methusalem funding (METH/15/011) by the Flemish government, Belgium. P.W.H., G.L.M. and M.L.F. were funded by a Leadership Investigator grants from National Health and Medical Research Council (NHMRC) of Australia (1194937; 1178444; 2007741, respectively). L.R.V. was funded by a grant from the National Institutes of Health (NIH R01 HD047709).\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.C., P.W.H., and J.M.P. conceptualized and designed the study, and wrote the first draft of the manuscript. Material preparation, data collection and analysis were performed by P.A., S.A.G., and A.S.L. All authors contributed to providing, organizing and classifying the data, and participated in the interpretation of the results. All authors, except the deceased G.N.K., edited earlier versions of the manuscript, and approved its final content. Resources and funding were acquired by P.W.H. and H.P.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data are provided in the Online Resource files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, Hoy D, Karppinen J, Pransky G, Sieper J, Smeets RJ, Underwood M, Lancet Low Back Pain Series Working G (2018) What low back pain is and why we need to pay attention. Lancet 391:2356\u0026ndash;2367. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(18)30480-X\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(18)30480-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCholewicki J, Popovich JM Jr., Aminpour P, Gray SA, Lee AS, Hodges PW (2019) Development of a collaborative model of low back pain: Report from the 2017 nass consensus meeting. Spine J 19:1029\u0026ndash;1040. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.spinee.2018.11.014\u003c/span\u003e\u003cspan address=\"10.1016/j.spinee.2018.11.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eO'Sullivan P, Caneiro JP, O'Keeffe M, O'Sullivan K (2016) Unraveling the complexity of low back pain. J Orthop Sports Phys Ther 46:932\u0026ndash;937. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2519/jospt.2016.0609\u003c/span\u003e\u003cspan address=\"10.2519/jospt.2016.0609\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChau A, Steib S, Whitaker E, Kohns D, Quinter A, Craig A, Chiodo A, Chandran S, Laidlaw A, Schott Z, Farlow N, Yarjanian J, Omwanghe A, Wasserman R, O'Neill C, Clauw D, Bowden A, Marras W, Carey T, Mehling W, Hunt CA, Lotz J (2023) Theoretical schemas to guide back pain consortium (bacpac) chronic low back pain clinical research. Pain Med 24:S13\u0026ndash;S35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/pm/pnac196\u003c/span\u003e\u003cspan address=\"10.1093/pm/pnac196\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCholewicki J, Pathak PK, Reeves NP, Popovich JM Jr (2019) Model simulations challenge reductionist research approaches to studying chronic low back pain. J Orthop Sports Phys Ther 49:477\u0026ndash;481. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2519/jospt.2019.8791\u003c/span\u003e\u003cspan address=\"10.2519/jospt.2019.8791\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoster NE (2011) Barriers and progress in the treatment of low back pain. BMC Med 9:108. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1741-7015-9-108\u003c/span\u003e\u003cspan address=\"10.1186/1741-7015-9-108\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHancock MJ, Hill JC (2016) Are small effects for back pain interventions really surprising? J Orthop Sports Phys Ther 46:317\u0026ndash;319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2519/jospt.2016.0604\u003c/span\u003e\u003cspan address=\"10.2519/jospt.2016.0604\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeller A, Hayden J, Bombardier C, van Tulder M (2007) Effect sizes of non-surgical treatments of non-specific low-back pain. Eur Spine J 16:1776\u0026ndash;1788. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00586-007-0379-x\u003c/span\u003e\u003cspan address=\"10.1007/s00586-007-0379-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMachado LA, Kamper SJ, Herbert RD, Maher CG, McAuley JH (2009) Analgesic effects of treatments for non-specific low back pain: A meta-analysis of placebo-controlled randomized trials. Rheumatology (Oxford) 48:520\u0026ndash;527. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/rheumatology/ken470\u003c/span\u003e\u003cspan address=\"10.1093/rheumatology/ken470\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVlaeyen JWS, Milde C (2025) The precarious use of group data to understand individual processes in pain science. Pain 166:1721\u0026ndash;1722. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/j.pain.0000000000003574\u003c/span\u003e\u003cspan address=\"10.1097/j.pain.0000000000003574\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlor H, Noguchi K, Treede RD, Turk DC (2023) The role of evolving concepts and new technologies and approaches in advancing pain research, management, and education since the establishment of the international association for the study of pain. Pain 164:S16\u0026ndash;S21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/j.pain.0000000000003063\u003c/span\u003e\u003cspan address=\"10.1097/j.pain.0000000000003063\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePincus T, Kent P, Bronfort G, Loisel P, Pransky G, Hartvigsen J (2013) Twenty-five years with the biopsychosocial model of low back pain-is it time to celebrate? A report from the twelfth international forum for primary care research on low back pain. Spine 38:2118\u0026ndash;2123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/BRS.0b013e3182a8c5d6\u003c/span\u003e\u003cspan address=\"10.1097/BRS.0b013e3182a8c5d6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChou R, Huffman LH (2007) Nonpharmacologic therapies for acute and chronic low back pain: A review of the evidence for an american pain society/american college of physicians clinical practice guideline. Ann Intern Med 147:492\u0026ndash;504\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKamper SJ, Apeldoorn AT, Chiarotto A, Smeets RJ, Ostelo RW, Guzman J, van Tulder MW (2015) Multidisciplinary biopsychosocial rehabilitation for chronic low back pain: Cochrane systematic review and meta-analysis. BMJ 350:h444. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.h444\u003c/span\u003e\u003cspan address=\"10.1136/bmj.h444\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoster NE, Hill JC, Hay EM (2011) Subgrouping patients with low back pain in primary care: Are we getting any better at it? Man Ther 16:3\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.math.2010.05.013\u003c/span\u003e\u003cspan address=\"10.1016/j.math.2010.05.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaragiotto BT, Maher CG, Hancock MJ, Koes BW (2017) Subgrouping patients with nonspecific low back pain: Hope or hype? J Orthop Sports Phys Ther 47:44\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2519/jospt.2017.0602\u003c/span\u003e\u003cspan address=\"10.2519/jospt.2017.0602\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodges PW (2019) Hybrid approach to treatment tailoring for low back pain: A proposed model of care. J Orthop Sports Phys Ther 49:453\u0026ndash;463. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2519/jospt.2019.8774\u003c/span\u003e\u003cspan address=\"10.2519/jospt.2019.8774\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChiodo AF, Haley M (2024) Does risk stratification with a matched treatment pathway improve clinical outcomes for adults with acute back pain? A systematic review and meta-analysis. Braz J Phys Ther 28:101116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bjpt.2024.101116\u003c/span\u003e\u003cspan address=\"10.1016/j.bjpt.2024.101116\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHue TF, Lotz JC, Zheng P, Black DM, Bailey J, Ewing SK, Fields AJ, Mehling W, Scheffler A, Strigo I, Petterson T, Wu LA, O'Neill C, Ucsf Reach Center tCCfP-CMPiCLBP (2024) Design of the comeback and backhome studies, longitudinal cohorts for comprehensive deep phenotyping of adults with chronic low-back pain (clbp): A part of the bacpac research program. medRxiv. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/2024.04.09.24305574\u003c/span\u003e\u003cspan address=\"10.1101/2024.04.09.24305574\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuirk DA, Johnson ME, Anderson DE, Smuck M, Sun R, Matthew R, Bailey J, Marras WS, Bell KM, Darwin J, Bowden AE (2023) Biomechanical phenotyping of chronic low back pain: Protocol for bacpac. Pain Med 24:S48\u0026ndash;S60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/pm/pnac163\u003c/span\u003e\u003cspan address=\"10.1093/pm/pnac163\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTagliaferri SD, Angelova M, Zhao X, Owen PJ, Miller CT, Wilkin T, Belavy DL (2020) Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: Three systematic reviews. NPJ Digit Med 3:93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41746-020-0303-x\u003c/span\u003e\u003cspan address=\"10.1038/s41746-020-0303-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMauck MC, Lotz J, Psioda MA, Carey TS, Clauw DJ, Majumdar S, Marras WS, Vo N, Aylward A, Hoffmeyer A, Zheng P, Ivanova A, McCumber M, Carson C, Anstrom KJ, Bowden AE, Dalton D, Derr L, Dufour J, Fields AJ, Fritz J, Hassett AL, Harte SE, Hue TF, Krug R, Loggia ML, Mageswaran P, McLean SA, Mitchell UH, O'Neill C, Pedoia V, Quirk DA, Rhon DI, Rieke V, Shah L, Sowa G, Spiegel B, Wasan AD, Wey HM, LaVange L (2023) The back pain consortium (bacpac) research program: Structure, research priorities, and methods. Pain Med 24:S3\u0026ndash;S12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/pm/pnac202\u003c/span\u003e\u003cspan address=\"10.1093/pm/pnac202\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGray S, Paolisso M, Jordan R, Gray S (2018) Environmental modeling with stakeholders: Theory, methods, and applications. In. Springer, Cham\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGray S, Chan A, Clark D, Jordan R (2012) Modeling the integration of stakeholder knowledge in social\u0026ndash;ecological decision-making: Benefits and limitations to knowledge diversity. Ecol Model 229:88\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ecolmodel.2011.09.011\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolmodel.2011.09.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGray SA, Zanre E, Gray SRJ (2014) Fuzzy cognitive maps as representations of mental models and group beliefs. In: Papageorgiou EI (ed) Fuzzy cognitive maps for applied sciences and engineering: From fundamentals to extensions and learning algorithms. Springer, Berlin Heidelberg, Berlin, Heidelberg, pp 29\u0026ndash;48\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGray SA, Gray S, Cox LJ, Henly-Shepard S (2013) Mental modeler: A fuzzy-logic cognitive mapping modeling tool for adaptive environmental management. In: 46th Hawaii International Conference on System Sciences (HICSS), 2013 IEEE, Wailea, Maui, HI. pp. 965\u0026ndash;973\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO (2001) International classification of functioning, disability and health (icf). World Health Organization, Geneva\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKosko B (1988) Hidden patterns in combined and adaptive knowledge networks. Int J Approx Reason 2:337\u0026ndash;393\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStach W (2010) Learning and aggregation of fuzzy cognitive maps - an evolutionary approach. University of Alberta\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBastian M, Heymann S, Jacomy M (2009) Gephi: An open source software for exploring and manipulating networks. In: Proceedings of the international AAAI conference on web and social media. pp. 361\u0026ndash;362\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAminpour P (2018) Pyfcm: Python for fuzzy cognitive mapping. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/payamaminpour/PyFCM/wiki\u003c/span\u003e\u003cspan address=\"https://github.com/payamaminpour/PyFCM/wiki\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed October 3, 2018\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIakovidis DK, Papageorgiou E (2011) Intuitionistic fuzzy cognitive maps for medical decision making. IEEE Trans Inf Technol Biomed 15:100\u0026ndash;107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1109/TITB.2010.2093603\u003c/span\u003e\u003cspan address=\"10.1109/TITB.2010.2093603\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKok K (2009) The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from brazil. Glob Environ Change 19:122\u0026ndash;133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.gloenvcha.2008.08.003\u003c/span\u003e\u003cspan address=\"10.1016/j.gloenvcha.2008.08.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHush JM (2020) Low back pain: It is time to embrace complexity. Pain 161:2248\u0026ndash;2251. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/j.pain.0000000000001933\u003c/span\u003e\u003cspan address=\"10.1097/j.pain.0000000000001933\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodges PW, Setchell J, Daniel E, Fowler M, Lee AS, Popovich JM Jr., Cholewicki J (2022) How individuals with low back pain conceptualize their condition: A collaborative modeling approach. J Pain 23:1060\u0026ndash;1070. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpain.2021.12.014\u003c/span\u003e\u003cspan address=\"10.1016/j.jpain.2021.12.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodges PW, Cholewicki J, Popovich JM Jr., Lee AS, Aminpour P, Gray SA, Cibulka MT, Cusi M, Degenhardt BF, Fryer G, Gutke A, Kennedy DJ, Laslett M, Lee D, Mens J, Patel VV, Prather H, Sturesson B, Stuge B, Vleeming A (2019) Building a collaborative model of sacroiliac joint dysfunction and pelvic girdle pain to understand the diverse perspectives of experts. PM R 11(Suppl 1):S11\u0026ndash;S23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/pmrj.12199\u003c/span\u003e\u003cspan address=\"10.1002/pmrj.12199\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoster NE, Anema JR, Cherkin D, Chou R, Cohen SP, Gross DP, Ferreira PH, Fritz JM, Koes BW, Peul W, Turner JA, Maher CG, Group LLBPSW (2018) Prevention and treatment of low back pain: Evidence, challenges, and promising directions. Lancet 391:2368\u0026ndash;2383. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(18)30489-6\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(18)30489-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMauck MC, Aylward AF, Barton CE, Birckhead B, Carey T, Dalton DM, Fields AJ, Fritz J, Hassett AL, Hoffmeyer A, Jones SB, McLean SA, Mehling WE, O'Neill CW, Schneider MJ, Williams DA, Zheng P, Wasan AD (2022) Evidence-based interventions to treat chronic low back pain: Treatment selection for a personalized medicine approach. Pain Rep 7:e1019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/PR9.0000000000001019\u003c/span\u003e\u003cspan address=\"10.1097/PR9.0000000000001019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHo EK, Chen L, Simic M, Ashton-James CE, Comachio J, Wang DXM, Hayden JA, Ferreira ML, Ferreira PH (2022) Psychological interventions for chronic, non-specific low back pain: Systematic review with network meta-analysis. BMJ 376:e067718. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj-2021-067718\u003c/span\u003e\u003cspan address=\"10.1136/bmj-2021-067718\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHayden JA, Wilson MN, Stewart S, Cartwright JL, Smith AO, Riley RD, van Tulder M, Bendix T, Cecchi F, Costa LOP, Dufour N, Ferreira ML, Foster NE, Gudavalli MR, Hartvigsen J, Helmhout P, Kool J, Koumantakis GA, Kovacs FM, Kuukkanen T, Long A, Macedo LG, Machado LAC, Maher CG, Mehling W, Morone G, Peterson T, Rasmussen-Barr E, Ryan CG, Sjogren T, Smeets R, Staal JB, Unsgaard-Tondel M, Wajswelner H, Yeung EW, Chronic Low Back Pain IPDM-AG (2020) Exercise treatment effect modifiers in persistent low back pain: An individual participant data meta-analysis of 3514 participants from 27 randomised controlled trials. Br J Sports Med 54:1277\u0026ndash;1278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjsports-2019-101205\u003c/span\u003e\u003cspan address=\"10.1136/bjsports-2019-101205\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes LS, Clark J, Colclough JA, Dale E, McMillan D (2017) Acceptance and commitment therapy (act) for chronic pain: A systematic review and meta-analyses. Clin J Pain 33:552\u0026ndash;568. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/AJP.0000000000000425\u003c/span\u003e\u003cspan address=\"10.1097/AJP.0000000000000425\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWood L, Hendrick PA (2019) A systematic review and meta-analysis of pain neuroscience education for chronic low back pain: Short-and long-term outcomes of pain and disability. Eur J Pain 23:234\u0026ndash;249. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ejp.1314\u003c/span\u003e\u003cspan address=\"10.1002/ejp.1314\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePuri BK, Theodoratou M (2023) The efficacy of psychoeducation in managing low back pain: A systematic review. Psychiatriki 34:231\u0026ndash;242. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22365/jpsych.2022.104\u003c/span\u003e\u003cspan address=\"10.22365/jpsych.2022.104\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeverijns P, Goossens N, Dankaerts W, Pitance L, Roussel N, Denis C, Fourre A, Verschueren P, Timmermans A, Janssens L (2024) Physiotherapy-led care versus physician-led care for persons with low back pain: A systematic review. Clin Rehabil:2692155241282987. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/02692155241282987\u003c/span\u003e\u003cspan address=\"10.1177/02692155241282987\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS (1996) Evidence based medicine: What it is and what it isn't. BMJ 312:71\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.312.7023.71\u003c/span\u003e\u003cspan address=\"10.1136/bmj.312.7023.71\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAminpour P, Gray SA, Singer A, Scyphers SB, Jetter AJ, Jordan R, Murphy R Jr, Grabowski JH (2021) The diversity bonus in pooling local knowledge about complex problems. Proceedings of the National Academy of Sciences 118:e2016887118\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiabbanelli PJ, Knox CB, Furman K, Jetter A, Gray S (2024) Defining and using fuzzy cognitive mapping. In: Fuzzy cognitive maps: Best practices and modern methods. Springer. pp. 1\u0026ndash;18\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmirkhani A, Papageorgiou EI, Mohseni A, Mosavi MR (2017) A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications. Comput Methods Programs Biomed 142:129\u0026ndash;145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cmpb.2017.02.021\u003c/span\u003e\u003cspan address=\"10.1016/j.cmpb.2017.02.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVlaeyen JWS, Linton SJ (2000) Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. Pain 85:317\u0026ndash;332. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0304-3959(99)00242-0\u003c/span\u003e\u003cspan address=\"10.1016/S0304-3959(99)00242-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeeuw M, Goossens ME, Linton SJ, Crombez G, Boersma K, Vlaeyen JW (2007) The fear-avoidance model of musculoskeletal pain: Current state of scientific evidence. J Behav Med 30:77\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10865-006-9085-0\u003c/span\u003e\u003cspan address=\"10.1007/s10865-006-9085-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScholich SL, Hallner D, Wittenberg RH, Hasenbring MI, Rusu AC (2012) The relationship between pain, disability, quality of life and cognitive-behavioural factors in chronic back pain. Disabil Rehabil 34:1993\u0026ndash;2000. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/09638288.2012.667187\u003c/span\u003e\u003cspan address=\"10.3109/09638288.2012.667187\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMutubuki EN, Beljon Y, Maas ET, Huygen F, Ostelo R, van Tulder MW, van Dongen JM (2020) The longitudinal relationships between pain severity and disability versus health-related quality of life and costs among chronic low back pain patients. Qual Life Res 29:275\u0026ndash;287. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11136-019-02302-w\u003c/span\u003e\u003cspan address=\"10.1007/s11136-019-02302-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ouml;zesmi U, \u0026Ouml;zesmi SL (2004) Ecological models based on people\u0026rsquo;s knowledge: A multi-step fuzzy cognitive mapping approach. Ecol Model 176:43\u0026ndash;64\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuie JR, Vashisht R, Galivanche A, Hadjadj C, Morshed S, Butte AJ, Ferguson AR, O'Neill C (2022) Toward a causal model of chronic back pain: Challenges and opportunities. Front Comput Neurosci 16:1017412. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fncom.2022.1017412\u003c/span\u003e\u003cspan address=\"10.3389/fncom.2022.1017412\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu ZY, Shan HH, Wang J, Zhu HJ, Liu SG, Lin F (2024) Graph modeling of relational structures among functioning variables with low back pain: An exploratory analysis based on international classification of functioning, disability and health. Eur J Phys Rehabil Med 60:487\u0026ndash;495. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.23736/S1973-9087.24.08089-4\u003c/span\u003e\u003cspan address=\"10.23736/S1973-9087.24.08089-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFriston KJ, Harrison L, Penny W (2003) Dynamic causal modelling. NeuroImage 19:1273\u0026ndash;1302. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s1053-8119(03)00202-7\u003c/span\u003e\u003cspan address=\"10.1016/s1053-8119(03)00202-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuke DA, Stamatakis KA (2012) Systems science methods in public health: Dynamics, networks, and agents. Annu Rev Public Health 33:357\u0026ndash;376. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev-publhealth-031210-101222\u003c/span\u003e\u003cspan address=\"10.1146/annurev-publhealth-031210-101222\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcGregor M, Nielsen A, Chung C, Fillery MD, Wakeland W, Mior S (2019) System dynamics to investigate opioid use and chiropractic care for chronic musculoskeletal pain. J Manipulative Physiol Ther 42:237\u0026ndash;246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jmpt.2018.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.jmpt.2018.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangevin HM (2024) Addressing gaps in pain research from an integrated whole person perspective. Pain 165:S23\u0026ndash;S32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/j.pain.0000000000003359\u003c/span\u003e\u003cspan address=\"10.1097/j.pain.0000000000003359\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7844247/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7844247/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eLow back pain (LBP) is a complex, multifactorial condition with diverse contributors across biopsychosocial domains. Although personalized treatment is advocated, clear guidance on tailoring interventions is lacking. To help address this gap, we synthesized expert knowledge on treatment effectiveness and underlying mechanisms using a systems-based, collaborative modeling approach.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eTwenty-nine experts from diverse disciplines created individual fuzzy cognitive maps (FCMs) to represent their understanding of factors affecting pain, disability, and quality of life (QoL), along with treatment mechanisms. These maps were aggregated into a meta-model comprising 142 Components and 1,161 weighted Connections. Centrality was used to identify the most central domains of the meta-model. Simulations with the meta-model based on expert knowledge 1) estimated the relative effectiveness of treatments on pain, disability, and QoL and 2) identified key Mediators and mediating Domains based on their relative contribution to mediating treatment effects.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePsychological, biomechanical, and social/contextual Domains were central to expert conceptualizations of LBP. Simulation indicated cognitive behavioral therapy was considered the most effective among all interventions. Most interventions were mediated by Components across multiple Domains, with psychological factors frequently serving as mediators. The conceptual meta-model underscored the complexity of LBP, reflecting both its multifactorial nature and the diversity of expert perspectives on factors related to treatment effectiveness.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe developed meta-model provides a novel, systems-based representation of expert knowledge about LBP, enabling quantitative exploration of treatment effects and underlying mechanisms. This conceptual framework also offers a foundation for advancing research on multi-modal, personalized care.\u003c/p\u003e","manuscriptTitle":"A meta-model of low back pain to examine collective expert knowledge of the effects of treatments and their mechanisms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 10:53:19","doi":"10.21203/rs.3.rs-7844247/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-18T13:52:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-12T18:07:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T17:27:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-03T14:16:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76883014101963257342380801341594644377","date":"2025-10-21T15:12:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339152027114134062442981098034587311307","date":"2025-10-18T13:36:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275512092472920900446329199452142573107","date":"2025-10-16T13:49:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-16T08:02:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-15T13:57:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-15T13:54:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Spine Journal","date":"2025-10-13T04:02:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c581401a-5b31-4112-b7f8-376a00fa0864","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-04T07:40:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 10:53:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7844247","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7844247","identity":"rs-7844247","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}