<p>Valence is central to affective experience yet remains poorly operationalized in emotion science. Most research infers valence by categorizing discrete emotions as positive or negative, which may conflate distinct aspects of emotional experience. On the other hand, direct bipolar valence measurement—asking individuals “How do you feel?” on a continuum from negative to positive—allows participants to integrate contextual complexity into their affective reports. Critically, this approach also enables the detection and quantification of transitions between positive and negative affective states, opening new possibilities for studying affect dynamics. We tested whether metrics quantifying these directional transitions predict psychological well-being more effectively than traditional intensity-based measures. Across three ecological momentary assessment datasets with 345 participants and over 30,000 assessments, the positive to negative affect shift ratio—quantifying the propensity to transition from positive to negative affect—showed stronger predictive associations with well-being outcomes than means and standard deviations derived from the same valence scale. This pattern persisted across LASSO regression, hierarchical regression, and relative importance analyses, and remained robust even with only 3 daily assessments. These findings demonstrate that direct valence measurement offers both theoretical advantages by respecting participant-integrated experience and empirical advantages by enabling more predictive dynamics metrics, while remaining practical for clinical applications.</p>