Review
Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatr. Sep 22, 2017; 7(3): 133-147
Published online Sep 22, 2017. doi: 10.5498/wjp.v7.i3.133
Biobehavioral assessment of the anxiety disorders: Current progress and future directions
Deah Abbott, Yasmin Shirali, J Kyle Haws, Caleb W Lack
Deah Abbott, Yasmin Shirali, J Kyle Haws, Caleb W Lack, Department of Psychology, University of Central Oklahoma, Edmond, OK 73134, United States
Author contributions: Abbott D, Shirali Y and Haws JK researched and wrote the article; Lack CW supervised and edited.
Conflict-of-interest statement: Authors declare no conflict of interests for this article.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Caleb W Lack, PhD, Department of Psychology, University of Central Oklahoma, 100 N. University Drive, Edmond, OK 73134, United States. clack@uco.edu
Telephone: +1-405-9745456
Received: March 28, 2017
Peer-review started: March 29, 2017
First decision: May 9, 2017
Revised: June 8, 2017
Accepted: June 30, 2017
Article in press: July 3, 2017
Published online: September 22, 2017
Processing time: 174 Days and 18.3 Hours
Abstract

It is difficult to accurately assess and differentially diagnose the anxiety disorders. The current system of assessment relies heavily on the subjective measures of client self-report, clinical observation, and clinical judgment. Fortunately, recent technological advances may enable practitioners to utilize objective, biobehavioral measures of assessment in a clinical setting. The current body of literature on two of these biobehavioral tools (eye-tracking and electrocardiogram devices) is promising, but more validation and standardization research is needed to maximize the utility of these devices. Eye-tracking devices are uniquely capable of providing data that can be used to differentially diagnose anxiety disorders from both other commonly comorbid and misdiagnosed disorders. Both eye-tracking and electrocardiogram devices are able to provide change-sensitive assessment information. This objective, real-time feedback can assist clinicians and researchers in assessing treatment efficacy and symptom fluctuation. Recently developed wearable and highly portable electrocardiogram devices, like the wearable fitness and behavior tracking devices used by many consumers, may be particularly suited for providing this feedback to clinicians. Utilizing these biobehavioral devices would supply an objective, dimensional component to the current categorical diagnostic assessment system. We posit that if adequate funding and attention are directed at this area of research, it could revolutionize diagnostic and on-going assessment practices and, in doing so, bring the field of diagnosis out of the 20th century.

Keywords: Biobehavioral; Assessment; Diagnosis; Anxiety; Electrocardiogram; Electrocardiogram; Eye-tracker

Core tip: Anxiety disorders are some of the most commonly comorbidly- and mis-diagnosed disorders in the DSM-5. The current system of assessment and diagnosis depends on clinician and client report measures, which are subjective and prone to bias. Recent technological advances make it possible to utilize the biobehavioral measures from eye-tracking and electrocardiogram devices in clinical settings. These devices can provide a much needed dimensional, objective, and change-sensitive component to current diagnostic and treatment-efficacy assessment protocols. This article summarizes the status of and outlines future directions for research on this important topic.