Mood induction through imitation of full-body movements with different affective intentions

Theories of human emotion, including some emotion embodiment theories, suggest that our moods and affective states are reflected in the movements of our bodies. We used the reverse process for mood regulation; modulate body movements to regulate mood. Dancing is a type of full-body movement characterized by affective expressivity and, hence, offers the possibility to express different affective states through the same movement sequences. We tested whether the repeated imitation of a dancer performing two simple full-body dance movement sequences with different affective expressivity (happy or sad) could change mood states. Computer-based systems, using avatars as dance models to imitate, offer a series of advantages such as independence from physical contact and location. Therefore, we compared mood induction effects in two conditions: participants were asked to imitate dance movements from one of the two avatars showing: (a) videos of a human dancer model or (b) videos of a robot dancer model. The mood induction was successful for both happy and sad imitations, regardless of condition (human vs. robot avatar dance model). Moreover, the magnitude of happy mood induction and how much participants liked the task predicted work-related motivation after the mood induction. We conclude that mood regulation through dance movements is possible and beneficial in the work context.