Network modeling as a unified framework to understand inter-individual differences in chronic musculoskeletal pain - Summary/Abstract We want to understand inter-individual differences in the clinical trajectory of chronic musculoskeletal pain (cMSKP) and the underlying factors that determine these differences. The research question we want to answer is the following: Can a time-varying network of multidomain symptoms be used to identify clinically-relevant transitions in pain and functional state, and do unique patterns of psychosocial, biomechanical and physiological factors determine these changes? Current management of cMSKP is focused on treating specific diagnoses or/and regional symptoms. There is a lack of diagnostic tools that capture interactions of symptoms across biopsychosocial domains and little guidance about how to interpret the relative contributors to the pain state and functional level. We will use knee osteoarthritis as a case study to test our hypothesis, although our findings can be generalizable for all cMSKP conditions. We will collect data from a prospective observational study of two cohorts recruited from community-based physical therapy (PT) clinics: those managing their knee pain with PT, and those undergoing PT after total knee arthroplasty (TKA). We will utilize a novel approach to integrate clinical measures with patient’s own knowledge and insights about their lived experience of pain and function through the following Aims: Aim 1: Develop network representations of patient’s lived experience of pain using large language models to annotate patient narratives. Aim 2: Develop network representations of patient’s functional state utilizing home-based videos of sit to stand functional tasks. Aim 3: Understand state transitions utilizing time series of daily pain, function, and psychosocial variables, and participant’s views of factors influencing pain and function. Our approach using multidomain network models represents a paradigm change to analyze and interpret data in cMSKP using a complex systems perspective. Our long-term objective is to develop clinically-feasible decision tools that enable whole-person assessment and management of cMSKP and guide personalized primary, secondary and tertiary prevention strategies. Our interdisciplinary team of physicians, physical therapists, engineers, neuroscientists and data scientists is uniquely qualified to tackle this challenging project.
