Affective and physiological predictors of exercise motivation: Evidence from HRV-based profiling

This study examined how experimentally induced psychophysiological states relate to situational motivation during exercise. Twenty-five healthy adults completed repeated 8-min cycling trials under four affective conditions designed to manipulate valence and arousal using audiovisual and verbal stimuli. During each trial, heart rate variability (HRV), perceived exertion, affective states, and situational motivation were assessed at multiple timepoints. Psychophysiological and perceptual variables were integrated using principal component analysis (PCA) to derive latent profiles. These included time-domain (rMSSD), frequency-domain (HF), nonlinear HRV complexity (DFA-α₁), and affective and exertional measures. Three principal components explained over 70% of the variance. Among these, a component reflecting autonomic-perceptual regulatory efficiency, characterized by the coupling between HRV complexity (DFA-α₁) and perceived exertion, emerged as the strongest predictor of situational motivation. A second-degree polynomial model revealed a curvilinear relationship between this regulatory dimension and situational motivation (R² = .82), with cross-validation supporting its relative robustness (cross-validated R² ≈ .67). In contrast, components reflecting general physiological activation and affective valence/arousal demonstrated comparatively weaker explanatory power. Repeated-measures analyses revealed significant condition-by-timepoint interactions for situational motivation, arousal, and perceived exertion, indicating that psychological and perceptual responses varied across induced states during exercise. Overall, these findings suggest that situational motivation during exercise is more strongly associated with integrated psychophysiological patterns, particularly the relationship between perceived effort and autonomic dynamics, than with affective valence or arousal alone.