A domain-oriented approach to characterizing movement-evoked pain.

INTRODUCTION

Movement-evoked pain (MEP) impacts a substantial proportion of US adults living with chronic pain. Evidence suggests that MEP is influenced by numerous biopsychosocial factors and mediated by mechanisms differing from those of spontaneous pain. However, both characteristic and mechanistic knowledge of MEP remain limited, hindering effective diagnosis and treatment.

OBJECTIVES

We asked (1) can chronic pain, functional, psychosocial, and behavioral measures be grouped into descriptive domains that characterize MEP? and (2) what relationships exist between biopsychosocial factors across multiple domains of MEP?

METHODS

We formed 6 characteristic domains from 46 MEP-related variables in a secondary analysis of data from 178 individuals (aged 45-85 years) with knee pain. Ratings of pain during 3 functional activities (ie, Balance, Walking, Chair Stand) were used as primary MEP variables. Pearson correlations were calculated to show linear relationships between all individual domain variables. Relationships between variables were further investigated through weighted correlation network analysis.

RESULTS

We observed a unique combination of pain characteristics associated with MEP apart from general pain. Notably, minutes doing physical activity were inversely associated with multiple variables within 4 of the 6 domains. Weighted correlation network analysis largely supported our classification of MEP domains. Additional interdomain relationships were observed, with the strongest existing between MEP, Mechanical Pain, and Multiple Pain Characteristics and Symptoms. Additional relationships were observed both within and between other domains of the network.

CONCLUSION

Our analyses bolster fundamental understanding of MEP by identifying relevant mechanistic domains and elucidating biopsychosocial and interdomain relationships.