Day-to-day dynamics of facial emotion expressions in posttraumatic stress disorder

Emotion-related posttraumatic stress disorder (PTSD) symptoms are heterogenous. Efforts to understand these symptoms have been limited by methods that fail to capture the complex, dynamic nature of emotions. Our study addresses these limitations with an approach that has not been applied to psychopathology: person-specific models of day-to-day facial emotion expression and symptom dynamics. We studied a sample of World Trade Center responders (N=112) with PTSD pathology who recorded a daily video diary and self-reported symptoms for 90 days. Facial expressions were detected from video recordings with a facial emotion recognition model. In idiographic network models, most participants (80%) had at least one, reliable expression-symptom link. Six expression-symptom dynamics were significant for >10% of the sample. Each dynamic showed substantial heterogeneity, with some people having symptoms related to over-expressivity and others under-expressivity. Our results reveal novel, clinically relevant individual differences that could not be found using typical nomothetic methods.