Detecting sudden gains during treatment of major depressive disorder: Cautions from a Monte Carlo analysis

Sudden gains are relatively large, quick, stable drops in symptom scores during treatment of depression that may (or may not) signal important therapeutic events. We review what is known and unknown currently about the prevalence, causes, and outcomes of sudden gains. We argue that valid identification of sudden gains (vs. random fluctuations in symptoms and gradual gains) is prerequisite to their understanding. In Monte Carlo simulations, three popular criterion sets showed inadequate power to detect sudden gains and many false positives due to (a) testing multiple intervals for sudden gains, (b) finite retest reliability of symptom measures, and (c) failure to account for gradual gains. Sudden gains in published clinical datasets appear similar in form and frequency to false positives in the simulations. We discuss the need to develop psychometrically sound methods to detect sudden gains and to differentiate sudden from random and gradual gains.