(238) Not so great expectations: characteristics associated with negative expectations of physical and emotional recovery in the hours after motor vehicle collision

Abstract

Negative expectations have been found to be powerful predictors of adverse pain outcomes. Individual characteristics associated with negative recovery expectations may provide useful clues regarding the potential etiology of such expectations; however, to date, no studies have evaluated the association between individual characteristics and recovery expectations after motor vehicle collision (MVC). In this study, we evaluated characteristics associated with negative recovery expectations in a large cohort of European Americans ≥18 and < 65 years of age who presented to the emergency department (ED) within 24 hours of MVC. Exclusion criteria included hospital admission after ED evaluation. Enrolled patients completed an ED interview which assessed recovery expectations: certainty of recovery, estimated time to physical recovery (ETPR) and estimated time to emotional recovery (ETER). Consistent with previous studies, individuals uncertain of recovery (UOR, 267/948, 28%), those with longer ETPR (>2 weeks, 263/948, 30%), and those with longer ETER (>4 weeks, 341/948, 45%) had substantially worse outcomes (e.g., each recovery expectation predicted moderate/severe neck pain and posttraumatic stress disorder at 6 months at p < 0.0001 level). Bivariate analyses assessed the relationship of each recovery expectation with sociodemographic factors, pre-MVC physical and mental health factors, MVC characteristics, and post-MVC psychological and somatic symptoms. A number of factors across each of these domains were associated with each expectation, with the exception of MVC-related characteristics, which were generally poorly associated with recovery expectations. Backwards stepwise logistic regression modeling (pin=0.10, pout=0.15) using factors associated at p<0.05 in bivariate analyses yielded sets of characteristics associated with certainty of recovery, ETPR, and ETER. Each of these models contained multiple potential modifiable risk factors. Results of bivariate and multivariate analyses will be presented at the conference. Supported by NIAMS R01AR056328.