A Bayesian Framework for Examining Heart Rate Variability as a Psychophysiological Correlate of Trait Emotional Intelligence During Acute Mental Stress and Recovery.

This dataset contains psychophysiological and psychological measures from N = 55 healthy adults assessed in a laboratory-based stress paradigm. Trait emotional intelligence (Trait EI) was examined as a predictor of autonomic flexibility indexed by heart rate variability (HRV). RR interval data were collected across three within-subject phases: baseline (T1), acute mental arithmetic stress (T2), and recovery (T3). Time-domain (SDNN, RMSSD, pNN50), frequency-domain (LF, HF, LF/HF), and non-linear indices (e.g., stress index, SD1, SD2 where applicable) were derived following artifact correction. Bayesian repeated-measures modeling was applied to quantify phase effects and Trait EI associations. Results indicate significant phase-dependent HRV modulation, characterized by parasympathetic withdrawal during stress and partial vagal re-engagement during recovery. Trait EI demonstrated associations with attenuated stress reactivity and improved recovery dynamics. The dataset enables secondary analyses using multilevel, Bayesian, or alternative psychophysiological modeling approaches.