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Published on: February 22, 2018
Factors predicting the long-term illness course in a cohort of depressed inpatients
Christine Kuehner1, Silke Huffziger
1Research Group Longitudinal and Intervention Research, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, PO Box 122120, 68072, Mannheim, Germany. Christine.Kuehner@zi-mannheim.de
Abstract:
Depressed psychiatric inpatients show particularly high rates of recurrence and chronicity. To identify predictors of their long-term illness course is of high importance for tertiary prevention. We followed up 68 unipolarly depressed psychiatric inpatients 1, 6, 42, and 66 months after discharge. Outcomes included time spent in episodes, time to relapse/recurrence, and psychosocial functioning during the prospective 5.5-year interval. Predictors included demographic, clinical, cognitive vulnerability, and social support variables assessed at baseline. During the total observation period, 12 % of patients spent <50 % of time in remission, and 55 % of those remitted at post-discharge baseline suffered a relapse or recurrence. Mean psychosocial functioning was below normal functioning at all assessments. Depression levels after discharge and unsatisfactory relationships within the support network predicted all outcomes. Furthermore, early onset, longer episode duration prior to study entry, and state orientation predicted time spent in episodes. Further predictors of time to recurrence included number of previous hospitalizations and lack of psychotherapy after discharge. Long-term psychosocial functioning was additionally predicted by previous hospitalizations, duration of index episode, and state orientation. Our results demonstrate a highly recurrent and chronic illness course in depressed psychiatric inpatients. Identified predictors point to the need of treating depressive episodes to full remission. Psychological interventions should explicitly address patients' interpersonal needs and possible deficits.
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