Parsing Affective Dynamics to Identify Risk for Mood and Anxiety Disorders

Emotional dysregulation is thought to underlie risk for both anxiety and depressive disorders. However, despite high rates of comorbidity, anxiety and depression are phenotypically different. Apart from nosological differences (e.g., worry for anxiety, low mood for depression), it remains unclear how the emotional dysregulation inherent in individual differences in trait anxiety and depression severity present on a day-to-day basis. One approach that may facilitate addressing these questions is to utilize Ecological Momentary Assessment (EMA) using mobile phones to parse the temporal dynamics of affective experiences into specific parameters. An emerging literature in affective science suggests that risk for anxiety and depressive disorders may be associated with variation in the mean and instability/variability of emotion. Here we examine the extent to which distinct temporal dynamic parameters uniquely predict risk for anxiety versus depression. Over 10 days, 105 individuals rated their current positive and negative affective state several times each day. Using two distinct approaches to statistically assess mean and instability of positive and negative affect, we found that individual differences in trait anxiety was generally associated with increased instability of positive and negative affect whereas mean levels of positive and negative affect were generally associated with individual differences in depression. These data provide evidence that the emotional dysregulation underlying risk for mood versus anxiety disorders unfolds in distinct ways and highlights the utility in examining affective dynamics to understand psychopathology.