Do Emotion Intensity, Variability, Differentiation, Co-Occurrence, and Positive-Negative Ratios Make Unique Contributions to Predicting Longitudinal Change in Psychological Distress and Well-Being?

A burgeoning array of affective indices are proposed to capture features of affect that contribute to mental health and well-being. However, because indices are often investigated separately, it is unclear what-if any-unique role they have. The present study addresses this question in a high-stress naturalistic context by prospectively testing the relative contributions of eight affective indices to psychological outcomes during the first acute lockdown phase of the COVID-19 pandemic. Across six fortnightly waves of data collection, participants (N= 613, aged 19 to 87 years) reported howmuch they experienced five positive and five negative emotions in response to images showing the health and social impacts of the pandemic. We used these ratings to calculate participant-level indices of intensity, variability, and differentiation for positive and negative emotions separately, and positive-negative co-occurrence and ratios. Psychosocial outcome measureswere general psychological distress, loneliness, work, and social impairment specifically due to the pandemic, well-being, and coping. On average, psychosocial functioning improved across the lockdown period, and, for most affective indices, bivariate relationships with psychosocial functioning supported existing theory and empirical work. However, multiple regression analyses suggested that the contributions of the individual indices were rarely unique, with most of the change in psychosocial functioning over time being explained by affect intensity and variability. These findings highlight that affective indices should be studied in concert to build a comprehensive and integrated understanding of their role in mental health and well-being.