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

Abstract

Facial expressions are an essential component of emotions that may reveal mechanisms maintaining posttraumatic stress disorder (PTSD). However, most research on emotions in PTSD has relied on self-reports, which only capture subjective affect. The few studies on outward emotion expressions have been hampered by methodological limitations, including low ecological validity and failure to capture the dynamic nature of emotions and symptoms. 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 PTSD symptom dynamics. We studied a sample of World Trade Center responders (N = 112) with elevated PTSD pathology who recorded a daily video diary and self-reported symptoms for 90 days (8953 videos altogether). Facial expressions were detected from video recordings with a facial emotion recognition model. In data-driven, 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 of these dynamics had statistically meaningful heterogeneity, with some people's symptoms related to over-expressivity and others to under-expressivity. Our results provide the foundation for a more complete understanding of emotions in PTSD that not only includes subjective feelings but also outward emotion expressions.