Development and validation of the Attention Bias Questionnaire (ABQ). Issue 2 (17th March 2022)

• Record Type: Journal Article
• Authors: Azriel, Omer; Britton, Jennifer C.; Gober, Chelsea D.; Pine, Daniel S.; Bar‐Haim, Yair
• Is Part Of: International journal of methods in psychiatric research. Volume 31:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-17
• Subjects: anxiety -- attention bias -- depression -- questionnaire -- social anxiety; Psychiatry -- Research -- Methodology -- Periodicals; Psychiatry -- Periodicals; 616.890072
• DOI: 10.1002/mpr.1905
• Languages: English
• ISSNs: 1049-8931

Abstract

Abstract: Objectives: Various psychopathologies are associated with threat‐related attention biases, which are typically measured using mechanized behavioral tasks. While useful and objective, behavioral measures do not capture the subjective experience of biased attention in daily‐living. To complement extant behavioral measures, we developed and validated a self‐report measure of threat‐related attention bias – the Attention Bias Questionnaire (ABQ). Methods: The ABQ consists of nine items reflecting the subjective experience of attention bias towards threats. To enable personalized relevance in threat‐content, the general term "threat" was used, and respondents were instructed to refer to specific things that threaten them personally. In a set of five studies, the ABQ was developed and validated. Internal consistency, discriminant validity, test‐retest reliability, and convergent validity were tested. Results: The ABQ emerged as a coherent and stable measure with two sub‐scales: Engagement with Threat and Difficulty to Disengage from Threat. ABQ scores were positively correlated with trait anxiety, social anxiety, PTSD, and depression, as well as behaviorally measured attention bias. Conclusion: Assessing the subjective experience of threat‐related attention bias can enrich existing knowledge about the cognitive mechanisms underlying psychopathology and complement extant behavioral bias measures in research and clinical evaluation.