Work

Resilience predicts remission in antidepressant treatment of geriatric depression

Year: 2018

Type: article

Abstract: Objectives With the world population rapidly aging, it is increasingly important to identify sociodemographic, cognitive, and clinical features that predict poor outcome in geriatric depression. Self‐report measures of resilience—ie, the ability to adapt and thrive in the face of adversity—may identify those depressed older adults with more favorable prognoses. Methods We investigated the utility of baseline variables including 4 factors of resilience (grit, active coping self‐efficacy, accommodative coping self‐efficacy, and spirituality) for predicting treatment response and remission in a 16‐week randomized controlled trial of methylphenidate, citalopram, or their combination in 143 adults over the age of 60 with MDD. Results Final logistic regression models revealed that greater total baseline resilience (Waldχ2 = 3.8,P = 0.05) significantly predicted both treatment response and remission. Specifically, a 20% increase in total resilience predicted nearly 2 times greater likelihood of remission (OR = 1.98, 95% CI = [1.01, 3.91]). Examining the individual factors of resilience, only accommodative coping self‐efficacy (Waldχ2 = 3.7,P = 0.05; OR = 1.41 [1.00‐2.01]) was significantly associated with remission. We found no relation between baseline sociodemographic factors (age, sex, race, education level) or measures of cognitive performance and posttreatment depressive symptoms. Conclusions Self‐reported resilience may predict greater responsivity to antidepressant medication in older adults with MDD. Future research should investigate the potential for resilience training—and in particular, interventions designed to increase accommodative coping—to promote sustained remission of geriatric depression.

Source: International Journal of Geriatric Psychiatry

DOI: 10.1002/gps.4953

Authors: Kelsey T. Laird, Helen Lavretsky, Natalie St. Cyr, Prabha Siddarth

Institution: University of California, Los Angeles

Language: English

Topic: Treatment of Major Depression

Subfield: Pharmacology (medical)

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, Allergan, National Institute of Mental Health, National Center for Complementary and Integrative Health