Biobehavioral assessment of the anxiety disorders: Current progress and future directions

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.

Predicting artificial visual field losses: A gaze-based inference study

“…Indeed, cognitive processes can be observed through eye movements and offer a wealth of information related to internal processes (Itti, 2015;Coutrot, Hsiao, & Chan, 2018). Inference from gaze data consists in deducing subjective characteristics solely from ocular data, such as age (Le Meur et al, 2017b), gender (Coutrot, Binetti, Harrison, Mareschal, & Johnston, 2016;Sammaknejad, Pouretemad, Eslahchi, Salahirad, & Alinejad, 2017), mental states and traits (Liao, Zhang, Zhu, & Ji, 2005;Hoppe, Loetscher, Morey, & Bulling, 2015;Yamada & Kobayashi, 2017;Hoppe, Loetscher, Morey, & Bulling, 2018), expertise and skill proficiency (Eivazi & Bednarik, 2011;Boccignone, Ferraro, Crespi, Robino, & de'Sperati, 2014;Tien et al, 2014;Kolodziej, Majkowski, Francuz, Rak, & Augustynowicz, 2018), and neurological disorders (Kupas, Harangi, Czifra, & Andrassy, 2017;Terao, Fukuda, & Hikosaka, 2017).It has proven useful in identifying autism spectrum disorder (Pierce et al, 2016), fetal alcohol spectrum disorder (Tseng, Paolozza, Munoz, Reynolds, & Itti, 2013), dementia (Zhang et al, 2016;Beltrán, García-Vázquez, Benois-Pineau, Gutierrez-Robledo, & Dartigues, 2018), dyslexia (Benfatto et al, 2016), anxiety (Abbott, Shirali, Haws, & Lack, 2017), mental fatigue (Yamada & Kobayashi, 2017), and other disorders. It has also been applied to task detection (Borji & Itti, 2014;Haji-Abolhassani & Clark, 2014;Kanan, Ray, Bseiso, Hsiao, & Cottrell, 2014;Boisvert & Bruce, 2016).…”

Temporal dynamics of autonomic nervous system responses under cognitive‐emotional workload in obsessive‐compulsive disorder

“…For patients with OCD, the alterations in their ANS reactions are less thoroughly studied. Published research describes conflicting results, ranging from significantly increased heart rate to no differences between individuals with OCD and healthy controls (Abbott et al, 2017). Olbrich et al (2022) provides evidence of increased sympathetic tone in individuals with OCD, and (Herzog & Brakoulias, 2022) describes the connection between decreased HRV and symptom severity of OCD.…”

“…Some researchers propose that schizophrenia may result from the convergence of two factors: ANS dysfunction and an environmental immune trigger (Carnac, 2022). Additionally, it has been demonstrated that emotional stress in individuals with mood and anxiety disorders is accompanied by dysfunctional ANS regulation (Abbott et al., 2017), with a predominant sympathetic tone. Individuals with greater social anxiety or even clinical levels of anxiety tend to experience less suppression and poor regulation of heart rate and heart rate variability (Abbott et al., 2017).…”

“…Additionally, it has been demonstrated that emotional stress in individuals with mood and anxiety disorders is accompanied by dysfunctional ANS regulation (Abbott et al., 2017), with a predominant sympathetic tone. Individuals with greater social anxiety or even clinical levels of anxiety tend to experience less suppression and poor regulation of heart rate and heart rate variability (Abbott et al., 2017). Previous studies have indicated that individuals with PTSD exhibit higher heart rate reactivity and increased low‐to‐high frequency heart rate variability in response to unpleasant affective stimuli (Abbott et al., 2017; Bedford et al., 2022; Park et al., 2019).…”

“…Individuals with greater social anxiety or even clinical levels of anxiety tend to experience less suppression and poor regulation of heart rate and heart rate variability (Abbott et al., 2017). Previous studies have indicated that individuals with PTSD exhibit higher heart rate reactivity and increased low‐to‐high frequency heart rate variability in response to unpleasant affective stimuli (Abbott et al., 2017; Bedford et al., 2022; Park et al., 2019). Pupillometry studies have shown that, compared to healthy controls, the pupil area in depressed patients is significantly larger both in darkness and at the peak of constriction (Wang & Munoz, 2014).…”