Temporal Profiles of the Course of Depression During Treatment
- 1 November 1997
- journal article
- research article
- Published by American Medical Association (AMA) in Archives of General Psychiatry
- Vol. 54 (11) , 1016-1024
- https://doi.org/10.1001/archpsyc.1997.01830230050007
Abstract
Background: Predictors of treatment response and recovery from depression in late life remain poorly understood. Previous studies have focused on a narrow range of response and recovery variables; namely, whether patients achieve or do not achieve a defined outcome or time to achieve the outcome. Whether patients vary in their pathways toward those outcomes—and the extent to which such variation can be anticipated by patient characteristics prior to treatment—has not been empirically examined. Methods: Depression symptom levels were monitored for 18 weeks in 95 persons aged 60 years or older who were experiencing a recurrence of major depression. Subjects received standardized combined nortriptyline treatment and interpersonal psychotherapy throughout the period. Cluster analysis was used to identify depression recovery patterns. Multivariate analyses considered whether recovery patterns were predicted by pretreatment psychosocial, clinical, and electroencephalographic sleep characteristics. Results: Four subgroups of elders were identified who differed in rate, stability, and direction of recovery, ie, those showing (1) rapid sustained improvement, (2) delayed but sustained improvement, (3) partial or mixed response, or (4) no response. Pretreatment characteristics reliably predicted subjects' group membership. Higher levels of acute and chronic stressors, poorer social supports, younger age at first depressive episode, endogenous depression, higher current anxiety, older current age, and poorer subjective and objective (electroencephalographic) sleep predicted poorer response profiles. Conclusions: There are multiple pathways by which individuals begin to emerge from depression; these pathways can be identified empirically. Variables from diverse psychobiologic domains can be used to predict which persons are likely to advance along which trajectories toward recovery.Keywords
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