Executive functioning at baseline prospectively predicts depression treatment response

Erica L. Dawson, Angela F. Caveney, Kortni K. Meyers, Sara L. Weisenbach, Bruno Giordani, Erich T. Avery, Michael Paul Schallmo, Armita Bahadori, Linas A. Bieliauskas, Matthew Mordhorst, Sheila M. Marcus, Kevin Kerber, Jon Kar Zubieta, Scott A. Langenecker

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Objective: Existing cognitive and clinical predictors of treatment response to date are not of sufficient strength to meaningfully impact treatment decision making and are not readily employed in clinical settings. This study investigated whether clinical and cognitive markers used in a tertiary care clinic could predict response to usual treatment over a period of 4 to 6 months in a sample of 75 depressed adults. Methods: Patients (N = 384) were sequentially tested in 2 half-day clinics as part of a quality improvement project at an outpatient tertiary care center between August 2003 and September 2007; additional subjects evaluated in the clinic between 2007 and 2009 were also included. Diagnosis was according to DSM-IV-TR criteria and completed by residents and attending faculty. Test scores obtained at intake visits on a computerized neuropsychological screening battery were the Parametric Go/No-Go task and Facial Emotion Perception Task. Treatment outcome was assessed using 9-item Patient Health Questionnaire (PHQ-9) self-ratings at follow-up (n = 75). Usual treatment included psychotropic medication and psychotherapy. Decline in PHQ-9 scores was predicted on the basis of baseline PHQ-9 score and education, with neuropsychological variables entered in the second step. Results: PHQ-9 scores declined by 46% at follow-up (56% responders). Using 2-step multiple regression, baseline PHQ-9 score (P ≤ .05) and education (P ≤ .01) were significant step 1 predictors of percent change in PHQ-9 follow-up scores. In step 2 of the model, faster processing speed with interference resolution (go reaction time) independently explained a significant amount of variance over and above variables in step 1 (12% of variance, P < .01), while other cognitive and affective skills did not. This 2-step model accounted for 28% of the variance in treatment change in PHQ-9 scores. Processing speed with interference resolution also accounted for 12% variance in treatment and follow-up attrition. Conclusions: Use of executive functioning assessments in clinics may help identify individuals with cognitive weaknesses at risk for not responding to standard treatments.

Original languageEnglish (US)
Article number16m01949
JournalPrimary Care Companion to the Journal of Clinical Psychiatry
Issue number1
StatePublished - 2017
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by National Institutes of Health grant MH074459, Brain and Behavior Research NARSAD Young Investigator Award to Dr Langenecker, and Rachel Upjohn Clinical Scholars Award and internal support from the Depression and Neuropsychology Sections of the Department of Psychiatry at the University of Michigan Medical Center, Ann Arbor


  • Psychiatry: Depression


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