Date of Submission

2002

Degree Type

Dissertation

Degree Name

Doctor of Psychology (PsyD)

Department

Psychology

Department Chair

Arthur Freeman, Ed.D., ABPP

First Advisor

Stephanie H. Felgoise, Ph.D., ABPP, Chairperson

Second Advisor

Robert A. DiTomasso, Ph.D., ABPP

Third Advisor

Grant R. Grissom, Ph.D.

Abstract

Since its inception, the effectiveness of psychotherapy as a treatment for psychological distress has been challenged vigorously. During the past 5 decades, increasingly sophisticated research studies have demonstrated psychotherapy effective in treating a variety ofpsychological disorders in the majority of individuals who avail themselves of treatment. Moreover, despite fierce competition among proponents of various psychotherapy models attempting to prove their model of choice most effective, research findings suggest the major models of psychotherapy are all equally effective in treating most individuals. Some have therefore shifted their research focus to determining the factors common to major psychotherapies that promote treatment success. Few, however, have examined the contributing factors involved in treatment failure. The present study investigates the factors predictive of treatment nonresponse (failure to change significantly from baseline global functioning, as a measure of overall functional psychological status) and negative response (deterioration from baseline global functioning) in a large sample of adult (ages 18-65) psychotherapy outpatients treated in naturalistic settings. Predictor variables were selected and drawn from archival questionnaire data monitoring changes in 900 patients' functioning in several specific and one global domain. The patient sample was randomly divided into two groups. Scores of Group 1 on predictors were submitted to a discriminant function analysis, and a predictive model for treatment outcome group classification was successfully derived. The veracity of the model was then substantiated with the data of participants assigned to Group 2. Results indicated that the linear combination of patient's scores on specific predictor variables successfully predicted the assignment of patients to one of three discrete outcome groups treatment responder, treatment nonresponder, and negative treatment responder. Findings suggest a small group of individuals is at high risk for negative treatment response. Others are highly likely to improve during treatment; however, an equal number are likely to experience no significant change during the treatment process. Further investigation into the risk factors involved in treatment nonresponse and negative response is key to a complete understanding of this phenomenon, to creating a method for the early identification of those at risk, and to developing specific interventions to increase the rate of treatment success in those at risk of experiencing suboptimal treatment outcome.

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