Pain intensity mediates the state-trait catastrophizing relationship: a path analysis study

Abstract

In accordance with the biopsychosocial model of pain, pain catastrophizing (PCS), fear of pain (FPQ), hyperviligance (somatosensory amplification, SSAS) and negative affect (NA) have all demonstrated significant associations with a variety of experimental and clinical pain conditions. However, the relative influences of state (i.e., situational) versus trait (i.e., dispositional) catastrophizing on pain perception are not well defined. While trait or dispositional catastrophizing can predict subsequent pain and disability, situational or state catastrophizing typically is more strongly correlated with coincident pain report. In accordance with these observations, we assessed several causative pathway models relative to theoretical or experimental pain conditions, in 3 separate studies. We assessed baseline trait PCS, FPQ, SSAS, and NA in all studies and state PCS again following: 1) consideration of three theoretical pain conditions (study 1, N = 193); 2) pain from the cold pressor task (study 2, N = 66); and 3) experimental muscle pain (study 3, N = 156). Using pathway analyses, we assessed the path coefficients for our full model, and two reduced models, testing whether the pain-specific situation (i.e., intensity) mediates the trait and state PCS relationship. The results from both theoretical and experimental studies support our causative model, indicating the pain-related traits influence pain perception and state catastrophzing is influenced by both trait catastrophizing as well as pain intensity. However, the reverse was not well supported, namely that state and trait catastrophizing both influence pain intensity (a significant positive state PCS - pain relationship remained, but the model indicated higher trait PCS actually caused lower pain ratings). Overall, these findings further refine the biopsychosocial model of pain, clarifying the roles of state and trait catastrophizing. This work was supported in part by grants from APS and NIH (K12HD055931; K01AR056134).