Predicting creativity in everyday life: an additional HRV reduction algorithm simulation and its Bayesian replication

This is the authors' abstract. We don't add key points for this paper.

Creative ideas happen in everyday life; however, some may be better than others, and we know little about the dynamics of idea quality as life unfolds. Research suggests that situations of reduced heart rate variability (HRV) might indicate moments of higher (verbal) creative performance. Therefore, this study investigated appropriate settings of an additional HRV reduction (AddHRVr) algorithm to predict creative performance in everyday life. In the first sample of 76 participants, who worked on verbal creative ideation tasks during five consecutive days, we simulated potential AddHRVr algorithm settings to identify higher creative performance. The simulation showed that short-lived periods of AddHRVr predicted higher creative performance in a given moment. In a second independent sample ( n = 65), the very same algorithm setting predicted higher creative performance, indicating robustness. This study provides first evidence for the predictive value of an AddHRVr algorithm to forecast creative performance in real life. As the next step, real-time field applications of these specific AddHRVr algorithm settings via wearables are needed to establish causality in the relationship between HRV reductions and creativity.