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Early change can predict outcome of psychological treatment, especially in cognitive behavior therapy. However, the optimal operationalization of “early change” for maximizing its predictive ability, and differences in predictive ability of disorder-specific versus general mental health measures has yet to be clarified. This study aimed to investigate how well early change predicted outcome depending on the week it was measured, the calculation method (regression slope or simple subtraction), the type of measures used, and the target disorder. During 10–15 weeks of internet-based cognitive behavior therapy for depression, social anxiety disorder, or panic disorder, weekly ratings were collected through both disorder-specific measures and general measures (Outcome Questionnaire-45 (OQ-45) and Clinical Outcomes in Routine Evaluation-10 (CORE-10)). With outcome defined as the disorder-specific measure, change at week four was the optimal predictor. Slope and subtraction methods performed equally well. The OQ-45 explained 18% of outcome for depression, 14% for social anxiety disorder, and 0% for panic disorder. Corresponding values for CORE-10 were 23%, 29%, and 25%. Specific measures explained 41%, 43%, and 34% respectively: this exceeded the ability of general measures also when they predicted themselves. We conclude that a simple calculation method with a disorder-specific measure at week four seems to provide a good choice for predicting outcome in time-limited cognitive behavior therapy.

plos one

Using Early Change to Predict Outcome in Cognitive Behaviour Therapy: Exploring Timeframe, Calculation Method, and Differences of Disorder-Specific versus General Measures