Implementing Physiology in Clinical Assessments of Adult Social Anxiety: A Method for Graphically Representing Physiological Arousal to Facilitate Clinical Decision-Making

Abstract

Low-cost methods exist for taking in vivo assessments of patients’ physiology in response to clinically relevant stimuli. Paradigms that allow assessors without a background in physiology to interpret physiological data might facilitate integrating physiology into clinical decision-making. Having assessors judge graphical depictions of physiological data may allow them to detect data patterns that might go unnoticed if such judgments were based on numerical depictions of physiological data. One method—Chernoff Faces—involves graphically representing data using features on the human face (eyes, nose, mouth, face width); a method that capitalizes on humans’ abilities to detect even subtle variations among facial features. Using adult heart rate (HR) norms and Chernoff Faces, we instructed three naive coders to make judgments about 240 undergraduate participants’ HR in response to emotionally evocative stimuli (i.e., film clips of disgust vs. craving stimuli). We assessed participants’ arousal with wireless, wristwatch HR monitors, and using Chernoff Faces we graphically represented participants’ HR data as well as normative HR values. For each participant, coders compared features of two Chernoff Faces: (a) participant’s HR within laboratory contexts (resting baseline, film clip) and (b) gender-matched normative HR values. Coders reliably and accurately identified elevations in participants’ arousal relative to normative arousal data. Further, participants’ self-reported social anxiety interacted with Chernoff Face judgments, in that participants’ arousal decreased from baseline to film clip exposure, but only for those who self-reported relatively high social anxiety. This study has important implications for implementing physiology to improve decision-making when clinically assessing adult social anxiety.