Statistical learning as a predictor of attention bias modification outcome: A preliminary study among socially anxious patients

Yaron Alon*, Gal Arad, Daniel S. Pine, Yair Bar-Haim

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Attention bias modification (ABM) is a novel therapy designed to modulate attentional biases towards threat typically observed among anxious individuals. Bias modification is allegedly achieved via extraction of a statistical regularity embedded within the treatment task. However, no prior study examined prediction of ABM therapeutic response in relation to patients’ capacity to extract statistical properties from the environment, a capacity known as “statistical learning”. Here, 30 treatment-seeking patients with social anxiety disorder completed a gold-standard statistical learning task at baseline and then received six sessions of ABM therapy. Results indicate that baseline statistical learning capacity predicts treatment outcome: the better patients’ statistical learning capacity, the greater their reduction in clinician-rated and self-reported social anxiety symptoms. Restricted capacities for statistical learning could account for the moderate effect sizes of ABM therapy in clinical trials. Poor response may occur in patients who fail to extract the underlying contingency embedded in ABM.

Original languageEnglish
Pages (from-to)36-41
Number of pages6
JournalBehaviour Research and Therapy
Volume112
DOIs
StatePublished - Jan 2019

Funding

FundersFunder number
National Institute of Mental HealthZIAMH002782
Israel Science Foundation1811/17

    Keywords

    • Attention bias modification
    • Social anxiety
    • Statistical learning
    • Treatment outcomes

    Fingerprint

    Dive into the research topics of 'Statistical learning as a predictor of attention bias modification outcome: A preliminary study among socially anxious patients'. Together they form a unique fingerprint.

    Cite this