LONG-TERM PREDICTION OF SELF-REPORTED PROBLEMS FOLLOWING SPINAL-CORD INJURY

Past studies of the long term consequences of spinal cord injury (SCI) have used both univariate and multivariate techniques to identify variables predictive of long term problems. Studies using multiple regression and discriminant analysis, while generating valuable data, have often used insufficient sample sizes and have rarely included cross-validation procedures. In the present study, completed questionnaires were obtained from 347 persons with SCI in 1985, 154 of whom also completed questionnaires in 1974. Factor analysis was first used to identify 3 underlying dimensions of self-reported problems including Emotional Distress, Dependency, and Health Problems. Scores on these 3 dimensions were then used as dependent variables with multiple regression. Three organic variables (age, duration of injury and injury level) and 5 adjustment variables (work status, activity level, medical stability, interpersonal satisfaction and economic satisfaction) were used as predictors. Regression equations were generated on the subjects completing only the 1985 questionnaire (N = 193) and cross-validated on persons completing both questionnaires (n = 154). The highest cross-validated squared multiple correlations were obtained for Dependency (SMC = 0.43), followed by Health Problems (SMC = 0.28) and Emotional Distress (SMC = 0.15). Adjustment variables proved to be the better predictors than organic variables, even though the organic variables were entered first. Organic predictors were somewhat useful in predicting Health Problems and Dependency, but of no value in predicting Emotional Distress. When the 1974 data was used to predict 1985 problems considerably smaller SMCs were noted (Dependence = 0.19; Health Problems = 0.11; Emotional Distress = 0.07), although all SMC’s remained significant (p < 0.01). Implications for counsellors and other rehabilitation professionals are discussed. © 1990 International Medical Society of Paraplegia.