A test of the fear avoidance model to predict chronic pain outcomes in a polytrauma sample

Autor: Jennifer Sharpe Potter, Briana Cobos, Donald D. McGeary, Blessen C. Eapen, Cindy A. McGeary, Alan L. Peterson, Stacey Young-McCaughan, David E. Reed, Timothy T. Houle, Carlos A. Jaramillo, Mary Jo Pugh, Paul S Nabity
Rok vydání: 2020
Předmět:
Zdroj: NeuroRehabilitation. 47:35-43
ISSN: 1878-6448
1053-8135
DOI: 10.3233/nre-203084
Popis: Background Chronic musculoskeletal pain is a complex problem, particularly for individuals with head injury and comorbid psychiatric conditions. The Fear Avoidance Model offers one of the strongest opportunities to conceptualize comorbid traumatic injury and pain, but this model is largely untested. Objective This study tests the Fear Avoidance Model of chronic pain using a sample from a study of polytrauma patients in a large Department of Veterans Affairs facility who participated in a federally-funded study of interdisciplinary chronic pain management. Methods The present study comprises a secondary analysis of 93 veterans with chronic pain, head injury, posttraumatic stress symptoms and a history of persistent opioid use. Standardized measures of Fear Avoidance Model risk factors (e.g., pain catastrophizing, fear avoidance beliefs, anxiety, depression) were examined as cross-sectional predictors of pain-related disability. Results Secondary data analysis revealed that Fear Avoidance Model factors accounted for almost 40% of the variance in pain-related disability, with pain catastrophizing and depression demonstrating the strongest relationships with disability. A summary variable combining all four factors revealed a 6% increase in disability for each factor that was clinically significant for the sample patients. Conclusions This study represents the first attempt to examine a complex, theoretical model of pain in a comorbid pain and TBI sample. Findings revealed a strong relationship between this model and pain-related disability that outperforms pain intensity ratings. This model could be used to guide better treatment for comorbid pain and TBI.
Databáze: OpenAIRE
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