Category: Adult Depression / Dysthymia

PS3- #B51 - Modification of Hostile Interpretation Bias in Depression: A Randomized Controlled Trial

Friday, Nov 17
11:00 AM – 12:00 PM
Location: Indigo Ballroom CDGH, Level 2, Indigo Level

Keywords: Depression | Treatment-Other | Anger / Irritability

Interpretation Bias Modification (IBM) is gaining attention in the literature as an intervention that alters cognitive biases and reduces associated symptoms. Hostile interpretation bias is a specific negative cognitive bias that reflects an individual’s tendency to assume hostile or aggressive intent behind the actions of others (Hawkins & Cougle, 2013). Smith and colleagues (2016) published findings showing elevations of hostile interpretation bias in a clinically depressed sample. In the present study, 40 adults with major depressive disorder (MDD) were randomly assigned to receive either IBM targeting hostile interpretation bias (IBM-H) or a healthy video control (HVC) condition. Compared to those in HVC, participants in IBM-H reported more benign interpretations (Wald (1, 40) = 39.54, β = .49, p < .001) and fewer hostile interpretations (Wald (1, 40) = 1.16, β = -.305, p = .026) at post-treatment. No difference in depressive interpretation bias was found between groups at post-treatment (Wald (1, 40) = 6.09, β = .08, p = .62). IBM-H led to greater anger control at post-treatment (Wald (1, 40) = 102.50, β = .733, p = .03) and follow-up (Wald (1, 40) = 4.31, β = .332, p = .006) compared to HVC. The IBM-H group perceived their treatment as less credible than the HVC group (F (1, 40) = 5.56, p = .024, η² = .13). For individuals with high expectancy of treatment success, IBM-H led to lower post-treatment depressive symptoms compared to HVC (Wald (1,40) = 13.62, β= -.35, p = .05), while findings trended in the opposite direction for those with low expectancy of success (Wald (1,40) = 13.24, β= .31, p = .08). Overall, the findings of this study contribute to understanding the efficacy of IBM protocols for anger and depression and highlight potential improvements to be made to future IBM protocols. 

Hillary L. Smith

Graduate Student
Florida State University
Tallahassee, Florida

Kirsten H. Dillon

Duke University

Jesse Cougle

Florida State University