• J Crook and H Moldofsky.
• McMaster University, Faculty of Health Sciences, School of Nursing, Hamilton, Ontario, Canada.
• Pain. 1996 Oct 1; 67 (2-3): 427433427-33.

AbstractThe purpose of this paper is to examine the clinical course of musculoskeletal, soft tissue, work-related injury. An analysis of empirically derived sub-groupings of workers based on prognostically important pain and disability variables assessed on enrollment into the study is described. Multidimensional time-dependent profiles are used to characterize stages in the development of pain, impairment, disability and handicap. The clinical course over the 18 months of study of the three subgroups is examined. The conceptual model, used to examine the workers' changing responses over time, is based on the World Health Organization Classification of Impairments, Disabilities and Handicaps (1980). Methodologically, the study employed a prospective longitudinal design. A randomly selected cohort of workers who had not returned to work by 3 months post-injury were identified from the files of the Workers' Compensation Board of Ontario. The workers were interviewed and examined on enrollment into the study at 3 months and subsequently at 9 months, 15 months and 21 months after injury. The outcomes were return to work or continued work disability. The results are based on those 104 workers who attended all four assessment periods. K means clustering was used to identify homogenous subgroups of workers. Repeated measures ANOVAs were used to characterize the stages of development of pain, impairment, disability and handicap. Duncan's multiple range test was used to compare pairs of means at each assessment period. Cluster groupings, based on three prognostically important clinical variables, number of pain sites, pain behavior and functional disability, obtained at the initial assessment were valid predictors of the number of days to return to work and total number of days on work disability. Prognostic stratification can enhance confidence in predictive decisions of clinical practice and improve clinical trials of therapy.

18 keywords...

hide…