THE PREDICTION OF ALCOHOLIC TREATMENT DROPOUTS AND THE MILLON CLINICAL MULTIAXIAL INVENTORY
The feasibility of using psychological test results to predict treatment outcome from an alcoholic treatment program was studied. Two-hundred and forty male veterans being treated in an inpatient alcohol treatment program of the Zablocki Veterans Administration Medical Center were administered the Millon Clinical Multiaxial Inventory at the beginning of treatment. Those patients who successfully completed treatment were compared to those patients who failed to complete treatment utilizing a stepwise discriminant analysis. Successful completion of treatment was defined as receiving a regular discharge from the program while failure to complete treatment was defined by receiving an irregular discharge. A cross validation sample of forty patients was randomly selected from the original pool of two-hundred and forty patients for classification purposes. A stepwise discriminant analysis was performed on the remaining two-hundred subjects using Rao's V as the selection criteria. The Histrionic, Narcissistic, Schizotypal, Psychotic Delusion and Psychotic Depression scales all contributed to the discrimination among the two discharge types, although only the first two scales achieved statistical significance at the P $<$.05 level. The classification results utilizing the stepwise discriminant analysis with the two-hundred subject sample correctly predicted discharge type 66% of the time. However, when the cross validation sample of 40 subjects was classified by using the discriminant function developed from the original sample of two-hundred subjects, the accuracy of prediction dropped to 45% for each discharge type. It was concluded that the use of the MCMI as a predictor of treatment outcome needs further research and that, for the present, clinical judgements must form the basis for predicting dropouts.
KERRY WAYNE LYNCH,
"THE PREDICTION OF ALCOHOLIC TREATMENT DROPOUTS AND THE MILLON CLINICAL MULTIAXIAL INVENTORY"
(January 1, 1987).
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