Do emotion intensity, variability, differentiation, co-occurrence, and positive–negative ratios make unique contributions to predicting longitudinal change in psychological distress and well-being?

Summary

This longitudinal study asked whether several distinct properties of everyday emotion each add unique predictive value for mental health beyond one another. Across six fortnightly waves during the first acute COVID-19 lockdown, 613 Australian adults aged 19 to 87 reported their emotions, and the authors derived indices of emotional intensity, variability, differentiation, co-occurrence, and positive-to-negative ratios. They then tested how these indices predicted longitudinal change in psychological distress and well-being. When examined together, most indices offered little unique prediction, with mean emotional intensity carrying the bulk of the predictive weight. The findings caution that the more elaborate emotion-dynamics measures may be largely redundant with simpler intensity measures when forecasting change in mental health.