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Fullproof: Towards the Detection of Impostor Syndrome Using Smartphone Sensors

Impostor syndrome is a psychological pattern characterized by doubts in one’s capabilities or achievements despite evident success. In this paper, we demonstrate the potential of a smartphone-aided solution for impostor syndrome detection among high-achieving college students by presenting some initial findings from our 3-week user study. We collected GPS, Bluetooth, light, screen and app usage data along with Clance Impostor Phenomenon Scale (CIPS) survey results from 37 students. We conducted a correlation analysis between CIPS scores and features extracted from sensor data. Then we grouped the features into three categories that reflect the behavioral characteristics of individuals with impostor syndrome, namely social avoidance, sense of obligation, and restlessness. Based on these findings, we suggest further examination of the use of behavioral sensing data in detecting impostor syndrome.