Detecting critical decision points in psychotherapy and psychotherapy + medication for chronic depression. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: We sought to quantify clinical decision points for identifying depression treatment nonremitters prior to end-of-treatment. METHOD: Data came from the psychotherapy arms of a randomized clinical trial for chronic depression. Participants (n = 352; 65.6% female; 92.3% White; mean age = 44.3 years) received 12 weeks of cognitive behavioral analysis system of psychotherapy (CBASP) or CBASP plus an antidepressant medication. In half of the sample, receiver operating curve analyses were used to identify efficient percentage of symptom reduction cut points on the Inventory of Depressive Symptoms-Self-Report (IDS-SR) for predicting end-of-treatment nonremission based on the Hamilton Rating Scale for Depression (HRSD). Sensitivity, specificity, predictive values, and Cohen's kappa for identified cut points were calculated using the remaining half of the sample. RESULTS: Percentage of IDS-SR symptom reduction at Weeks 6 and 8 predicted end-of-treatment HRSD remission status in both the combined treatment (Week 6 cut point = 50.0%, Cohen's κ = .42; Week 8 cut point = 54.3%, Cohen's κ = .45) and psychotherapy only (Week 6 cut point = 60.7%, Cohen's κ = .41; Week 8 cut point = 48.7%, Cohen's κ = .49). Status at Week 8 was more reliable for identifying nonremitters in psychotherapy-only treatment. CONCLUSIONS: Those with chronic depression who will not remit in structured, time-limited psychotherapy for depression, either with therapy alone or in combination with antidepressant medication, are identifiable prior to end of treatment. Findings provide an operationalized strategy for designing adaptive psychotherapy interventions.

publication date

  • June 10, 2013

Research

keywords

  • Antidepressive Agents
  • Cognitive Behavioral Therapy
  • Depressive Disorder, Major
  • Triazoles

Identity

PubMed Central ID

  • PMC3925064

Scopus Document Identifier

  • 84884559236

Digital Object Identifier (DOI)

  • 10.1037/a0033250

PubMed ID

  • 23750462

Additional Document Info

volume

  • 81

issue

  • 5