Abstract

Pain, distress, and depression are predictors of posttrauma pain and recovery. We hypothesized that pretrauma characteristics of the person could predict posttrauma severity and recovery. Sex, age, body mass index, income, education level, employment status, pre-existing chronic pain or psychopathology, and recent life stressors were collected from adults with acute musculoskeletal trauma through self-report. In study 1 (cross-sectional, n=128), pain severity was captured using the Brief Pain Inventory (BPI), distress through the Traumatic Injuries Distress Scale (TIDS) and depression through the Patient Health Questionnaire-9 (PHQ-9). In study 2 (longitudinal, n=112) recovery was predicted using scores on the Satisfaction and Recovery Index (SRI) and differences within and between classes were compared with identify pre-existing predictors of posttrauma recovery. Through bivariate, linear and nonlinear, and regression analyses, 8.4% (BPI) to 42.9% (PHQ-9) of variance in acute-stage predictors of chronicity was explainable through variables knowable before injury. In study 2 (longitudinal), latent growth curve analysis identified 3 meaningful SRI trajectories over 12 months. Trajectory 1 (start satisfied, stay satisfied [51%]) was identifiable by lower TIDS, BPI, and PHQ-9 scores, higher household income and less likely psychiatric comorbidity. The other 2 trajectories (start dissatisfied, stay dissatisfied [29%] versus start dissatisfied, become satisfied [20%]) were similar across most variables at baseline save for the "become satisfied" group being mean 10 years older and entering the study with a worse (lower) SRI score. The results indicate that 3 commonly reported predictors of chronic musculoskeletal pain (BPI, TIDS, PHQ-9) could be predicted by variables not related to the injurious event itself. The 3-trajectory recovery model mirrors other prior research in the field, though 2 trajectories look very similar at baseline despite very different 12-month outcomes. Researchers are encouraged to design studies that integrate, rather than exclude, the pre-existing variables described here.

Full Text
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