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Introduction Self-reported levels of disability in individuals with low back pain (LBP) have not improved in the last decade. A broader perspective and a more comprehensive management framework may improve disability outcomes. We recently developed and validated the Low Back Pain and Disability Drivers Management (PDDM) model, which aims to identify the domains driving pain and disability to guide clinical decisions. The objectives of this study were to determine the applicability of the PDDM model to a LBP population and the feasibility of conducting a pragmatic trial, as well as to explore clinicians’ perceived acceptability of the PDDM model’s use in clinical settings. Methods This study was an one-arm prospective feasibility trial. Participants included physiotherapists working with a population suffering from LBP and their patients aged 18 years or older presenting with a primary complaint of LBP that sought a new referral and deemed fit for rehabilitation from private and public clinical settings. Clinicians participated in a one-day workshop on the integration of the PDDM model into their clinical practice, and were asked to report various LBP-related outcomes via self-reported questionnaires (i.e., impact of pain on physical function, nervous system dysfunctions, cognitive-emotional factors, work disabilities) at baseline and at six-week follow-up. Physiotherapists’ acceptability of the use of the PDDM model and appreciation of the training were assessed via semi-structured phone interviews. Analyses focused on a description of the model’s applicability to a LBP population, feasibility outcomes and acceptability measures. Results Applicablity of the PDDM model was confirmed since it successfully established the profile of patients according to the elements of each categories, and each of the 5 domains of the model was represented among the study sample. Trial was deemed feasible contingent upon few modifications as our predefined success criteria for the feasibility outcomes were met but feasibility issues pertaining to data collection were highlighted. Twenty-four (24) clinicians and 61 patients were recruited within the study’s timeframe. Patient’s attrition rate (29%) and clinicians’ compliance to the study protocol were adequate. Clinicians’ perceived acceptability of the use of the model in clinical settings and their appreciation of the training and online resources were both positive. Recommendations to improve the model’s integration in clinical practice, content of the workshop and feasibility of data collection methods were identified for future studies. A positive effect for all patients’ reported outcome measures were also observed. All outcome measures except for the PainDetect questionnaire showed a statistically significant reduction post-intervention (p<0.05). Conclusion These findings provide preliminary evidence of the potential of the PDDM model to optimize LBP management as well as conducting a future larger-scale pragmatic trial to determine its effectiveness. Trial registration Clinicaltrial.gov: NCT03949179.

Background:We recently proposed the Pain and Disability Drivers Management (PDDM) model, which was designed to outline comprehensive factors driving pain and disability in low back pain (LBP). Although we have hypothesized and proposed 41 elements, which make up the model's five domains, we have yet to assess the external validity of the PDDM's elements by expert consensus. Research objectives:This study aimed to reach consensus among experts regarding the different elements that should be included in each domain of the PDDM model. Relevance:The PDDM may assist clinicians and researchers in the delivery of targeted care and ultimately enhance treatment outcomes in LBP. Methods:Using a modified Delphi survey, a two-round online questionnaire was administered to a group of experts in musculoskeletal pain management. Participants were asked to rate the relevance of each element proposed within the model. Participants were also invited to add and rate new elements. Consensus was defined by a greater than or equal to 75% level of agreement.Results: A total of 47 (round 1) and 33 (round 2) participants completed the survey. Following the first round, 38 of 41 of the former model elements reached consensus, and 10 new elements were proposed and later rated in the second round. Following this second round, consensus was reached for all elements (10 new + 3 from first round), generating a final model composed of 51 elements. Conclusion: This expert consensus-derived list of clinical elements related to the management of LBP represents a first step in the validation of the PDDM model.

In health care, clinical decision making is typically based on diagnostic findings. Rehabilitation clinicians commonly rely on pathoanatomical diagnoses to guide treatment and define prognosis. Targeting prognostic factors is a promising way for rehabilitation clinicians to enhance treatment decision-making processes, personalize rehabilitation approaches, and ultimately improve patient outcomes. This can be achieved by using prognostic tools that provide accurate estimates of the probability of future outcomes for a patient in clinical practice. Most literature reviews of prognostic tools in rehabilitation have focused on prescriptive clinical prediction rules (pCPR). These studies highlight notable methodological issues and conclude that these tools are neither valid nor useful for clinical practice. This has raised the need to open the scope of research to understand what makes a quality prognostic tool that can be used in clinical practice. Methodological guidance in prognosis research has emerged in the last decade, encompassing exploratory studies on the development of prognosis and prognostic models. Methodological rigor is essential to develop prognostic tools, as only prognostic models developed and validated through a rigorous methodological process should guide clinical decision making. This Perspective argues that rehabilitation clinicians need to master the identification and use of prognostic tools to enhance their capacity to provide personalized rehabilitation. It is time for prognosis research to look for prognostic models that were developed and validated following a comprehensive process before being simplified into suitable tools for clinical practice. New models, or rigorous validation of current models, are needed. The approach discussed in this Perspective offers a promising way to overcome the limitations of most models and provide clinicians with quality tools for personalized rehabilitation approaches.

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