The Predicted and Observed Course of Psychotherapy for Anxiety and Mood Disorders

Abstract

By applying hierarchical linear modeling (HLM) techniques, patient clinical characteristics at the beginning of treatment were used to predict individual patient responses (N = 160) to psychotherapy. Four diagnostic groups (mood, anxiety, other, and no diagnosis) were formed among the patients based on intake-administered Structured Diagnostic Interview for the Diagnosis of DSM-III-R axis I Disorders. Patients with mood and anxiety disorders had predicted courses of response to psychotherapy that were similar but different from patients with other disorders and no diagnosis. Predicted and observed courses of response to psychotherapy in a subsample (N = 75) who had provided enough data to model the actual course of treatment showed high levels of congruence, thus supporting the validity of predicting course of response. HLM predictive profiling offers a new approach for assessing treatment effectiveness of psychotherapy with patients having axis I diagnostic conditions by considering an individual patient's clinical characteristics.