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Predictors of response to problem-solving treatment of depression in primary care
Journal article   Peer reviewed

Predictors of response to problem-solving treatment of depression in primary care

Mark T. Hegel, James E. Barrett, John E. Cornell and Thomas E. Oxman
Behavior therapy, v 33(4), pp 511-527
2002
DOI: https://doi.org/10.1016/S0005-7894(02)80014-4
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Problem-solving treatment of depression is a brief intervention specifically designed for primary care (PST-PC). To date, predictors of an optimal response to PST-PC have not been studied. In primary care, knowing such factors is essential for proper triage decisions. Patient, therapist, and process variables were evaluated for their ability to predict remission of minor depression or dysthymia in patients treated with PST-PC. The most salient predictors of remission were the ability to understand the PST-PC rationale and to apply the PST-PC procedure in early treatment sessions, having a cognitive-behavioral therapist, and, for dysthymia, having a lower depression severity level at baseline. These results provide preliminary evidence of some factors associated with an optimal response to PST-PC and also present challenges for the ability to broadly disseminate the intervention. Modifications to the existing PST-PC training program and directions for future research are discussed.

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3 Record Views
31 citations in Web of Science
35 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Psychiatry
Psychology, Clinical
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