Inhaltszusammenfassung

Background: Previous studies have shown that individual differences in affect dynamics during depressed patients' everyday lives allow the prediction of treatment outcome and of symptom reoccurrence in remitted patients. In this study, we analyze whether understanding patients' affective states and their fluctuation patterns helps predict early treatment response (until session 5). Methods: Ecological Momentary Assessment (EMA) strategies allow in-depth analyses of real-time affective states ...Background: Previous studies have shown that individual differences in affect dynamics during depressed patients' everyday lives allow the prediction of treatment outcome and of symptom reoccurrence in remitted patients. In this study, we analyze whether understanding patients' affective states and their fluctuation patterns helps predict early treatment response (until session 5). Methods: Ecological Momentary Assessment (EMA) strategies allow in-depth analyses of real-time affective states and of their dynamics. Repeated assessments were made four times a day during a two-week period to capture real-life affective states (positive affect, PA and negative affect, NA) and dynamics (fluctuations in NA and PA) before the start of outpatient treatment of 39 patients. Due to the nested structure of the data, hierarchical linear models were conducted. Results: PA/NA ratios, as well as fluctuations in NA predicted early treatment response, even when adjusting for initial impairment. In contrast, mean levels of NA or PA, as well as fluctuations in PA did not predict treatment response. Limitations: The time between the EMA assessment and treatment onset varied between patients. However, this variation was not associated with early change. Conclusions: The results suggest that pre-treatment affect dynamics could provide valuable information for predicting treatment response independent of initial impairment levels. Better predictions of early treatment response help to improve treatment choices early in the treatment progress. (C) 2016 Elsevier B.V. All rights reserved. » weiterlesen» einklappen

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