A Psychosociomedical Prediction Model of Response to Treatment by Chronically Disabled Workers with Low-Back Pain

摘要

There has been much Interest in identifying variables that can predict which Individuals are susceptible to developing chronic low-back pain. There currently are a number of studies that are evaluating primary predictors (which uninjured workers are likely to develop chronic low-back pain) and secondary predictors (which workers with acute episodes will develop chronic pain). The present study reports the first results from a large-scale investigation of tertiary predictors. Specifically, it addresses the issue of what psychosociomedical variables are predictive of successsol;failure in response to a comprehensive Functional Restoration treatment program by workers who are chronically disabled with low-back pain. Three stages were involved In the development of this prediction model. First, a group of treatment and research professionals who had extensive experience in the area of chronic low-back pain identified an array of 42 variables, from a larger pool of quantified physical, psychosocial, and medical parameters rated to be important' with this patient population. Second, from a sample of chronic low-back pain patients who had undergone a full medical, psychosocial, and functional physical assessment prior to participation in a comprehensive Functional Restoration program, four separate groups of patients were selected on the basis of specific outcome criteriacolon; 1) A "success"group (nequals;125) who had completed the program and were back to work 1 year later; 2) a "failure" group (nequals;121), who had completed the program but were not back to work 1 year later; 3) A "drop-out"group (nequals;40), who dropped out of the program before completing it; and 4) a "failed to enter" group, who did not enter the program after initial evaluation (nequals;40). A series of statistical analyses evaluated which of the 42 variables differentiated among these four groups of patients. These analyses statistically isolated ten separate variablescolon; one demographic, four psychosocial, two Job-related, two physical measures, and one surgery history variable. The third stage of model development Involved entering these ten variables into a multivarlate logistic regression analysis. This analysis developed a model that correctly Identified 70percnt; of patient cases. These initial results show great promise of developing a statistically robust model for predicting those chronic low-back patients who will or will not respond to a Functional Restoration treatment regimen.