Alterations in facial expressions of emotion are a hallmark of psychopathology and may be present before the onset of mental illness. Technological advances have spurred interest in examining alterations based on “thin slices” of behavior using automated approaches. However, questions remain. First, can alterations be detected in ultrathin slices of behavior? Second, how do automated approaches converge with human coding techniques? The present study examined ultrathin (i.e., 1-min) slices of video-recorded clinical interviews of 42 individuals at clinical high risk (CHR) for psychosis and 42 matched controls. Facial expressions of emotion (e.g., joy, anger) were examined using two automated facial analysis programs and coded by trained human raters (using the Expressive Emotional Behavior Coding System). Results showed that ultrathin (i.e., 1-min) slices of behavior were sufficient to reveal alterations in facial expressions of emotion, specifically blunted joy expressions in individuals at CHR (with supplementary analyses probing links with attenuated positive symptoms and functioning). Furthermore, both automated analysis programs converged in the ability to detect blunted joy expressions and were consistent with human coding at the level of both second-by-second and aggregate data. Finally, there were areas of divergence across approaches for other emotional expressions beyond joy. These data suggest that ultrathin slices of behavior can yield clues about emotional dysfunction. Further, automated approaches (which do not require lengthy training and coder time but do lend well to mobile assessment and computational modeling) show promise, but careful evaluation of convergence with human coding is needed.
- Automated coding
- Clinical high risk for psychosis
- Facial expressions
- Thin slicing
ASJC Scopus subject areas