Early improvement in positive rather than negative emotion predicts remission from depression after pharmacotherapy
Geschwind, Nicole × Nicolson, Nancy A Peeters, Frenk van Os, Jim Barge-Schaapveld, Daniela Wichers, Marieke #
European Neuropsychopharmacology vol:21 issue:3 pages:241-247
Knowledge on mechanisms involved in early prediction of response to antidepressant medication may help optimize clinical decision making. Recent studies regarding response to pharmacotherapy implicate resilience-like mechanisms and involvement of positive, rather than negative emotions. The aim of the current study is to examine the contribution of early change in positive affect to the prediction of response to pharmacotherapy. Positive and negative emotions were measured at baseline and during the first week of pharmacotherapy, using experience sampling techniques. The association between early change in positive and negative emotions and severity of depressive symptoms at week six was examined in a sample of 49 depressed patients. The added benefits of measuring early change in positive emotions compared to early Hamilton Depression Rating Scale (HDRS) change alone were evaluated through model comparisons. Early improvement in positive affect during the first week of treatment predicted the continuous HDRS score (beta=-0.64, p < 0.001), response (50% reduction; OR=4.32, p<0.01), and remission (HDRS <= 7; OR=9.29, p < 0.001) at week six with moderate to large effect sizes. Effects of early change in negative emotions were only half as large and disappeared when evaluated simultaneously with early change in positive emotions. When early change in positive emotions was added to the models including early HDRS change only, all three models improved significantly. In conclusion, early change in positive rather than negative emotions best predicted response to treatment, supporting the notion that antidepressants activate resilience-like mechanisms. Moreover, monitoring of positive emotions in early stages of treatment may improve clinical decision making. (C) 2010 Elsevier B.V. and ECNP. All rights reserved.