Facing ostracism: micro-coding facial expressions in the Cyberball social exclusion paradigm.

Background: Social exclusion is often measured with the Cyberball paradigm, a computerized ball-tossing game. Most Cyberball studies, however, used self-report questionnaires, leaving the data vulnerable to reporter bias, and associations with individual characteristics have been inconsistent.
Methods: In this large-scale observational study, we video-recorded 4,813 10-year-old children during Cyberball and developed a real-time micro-coding method measuring facial expressions of anger, sadness and contempt, in a multi-ethnic population-based sample. We estimated associations between facial expressions and self-reported negative feelings, explored associations of child characteristics such as sex and parental national origin with observed and self-reported feelings during social exclusion, and tested associations of observed and self-reported feelings during social exclusion with behavior problems at age 14.
Results: Facial expressions of sadness and anger were associated with self-reported negative feelings during the game, but not with such feelings after the game. Further, girls reported to have had less negative feelings during the game than boys, but no such sex-differences were found in total observed emotions. Likewise, children with parents of Moroccan origin reported less negative feelings during the game than Dutch children, but their facial expressions did not indicate that they were differently affected. Last, observed emotions related negatively to later internalizing problems, whereas self-report on negative feelings during the game related positively to later internalizing and externalizing problems.
Conclusions: We show that facial expressions are associated with self-reported negative feelings during social exclusion, discuss that reporter-bias might be minimized using facial expressions, and find divergent associations of observed facial expressions and self-reported negative feelings with later internalizing problems.
(© 2023. The Author(s).)