Prediction of Therapeutic Outcome in a Naturalistic Setting Using Pretreatment Psychological Distress Indicators

Background: Outcome predictions allow to improve psychotherapy and to increase economic benefit. The efficient translation into practice requires simple prediction methods. The present study evaluates the prediction of treatment outcome based on initial distress level. Methods: Routine data of a university psychotherapy outpatient clinic were used (N = 3,145, Mage = 35.8, 67% female). Low versus high distress patients (classified by overall psychological distress, symptomatology, and previous treatment) were compared on total reduction in psychopathology, (early) response, remission, and premature treatment discontinuation using t tests and logistic regressions. Response and remission were assessed via relative (percentage improvement) and absolute measures (Reliable Change Index; RCI). Results: Distress level was inversely related to percentage improvement (OR = 0.62) and remission (OR = 0.34). It was positively related to total reduction in psychopathology (d = 0.63), RCI response (OR = 2.37), and treatment discontinuation (OR = 2.15). Early response and treatment discontinuation partially mediated the relationship between distress level and treatment outcome. Conclusions: Treatment success tends to be lower when initial distress is high, but this finding appears contingent on the operationalization of treatment outcome. The presented classification approach is easy to implement in practice and may be useful in order to counter an excessive workload in psychotherapy trainees.