Emotion network density is a potential clinical marker for anxiety and depression: Comparison of ecological momentary assessment and daily diary.

OBJECTIVES: Using two intensive longitudinal data sets with different timescales (90 minutes, daily), we examined emotion network density, a metric of emotional inflexibility, as a predictor of clinical-level anxiety and depression. DESIGN: Mobile-based intensive longitudinal assessments. METHODS: 119 participants (61 anxious and depressed, 58 healthy controls) completed ecological momentary assessment (EMA) to rate a variety of negative (NE) and positive emotions (PE) 9 times per day for 8 days using a mobile phone application. 169 participants (97 anxious and depressed and 72 healthy controls) completed an online daily diary on their NE and PE for 50 days. Multilevel vector autoregressive models were run to compute NE and PE network densities in each data set. RESULTS: In the EMA data set, both NE and PE network densities significantly predicted participants' diagnostic status above and beyond demographics and the mean and standard deviation of NE and PE. Greater NE network density and lower PE network density were associated with anxiety and depression diagnoses. In the daily diary data set, NE and PE network densities did not significantly predict the diagnostic status. CONCLUSIONS: Greater inflexibility of NE and lower inflexibility of PE, indexed by emotion network density, are potential clinical markers of anxiety and depressive disorders when assessed at intra-daily levels as opposed to daily levels. Considering emotion network density, as well as the mean level and variability of emotions in daily life, may contribute to diagnostic prediction of anxiety and depressive disorders. PRACTITIONER POINTS: Emotion network density, or the degree to which prior emotions predict and influence current emotions, indicates an inflexible or change-resistant emotion system. Emotional inflexibility or change resistance over a few hours, but not daily, may characterize anxiety and depressive disorders. Inflexible negative emotion systems are associated with anxiety and depressive disorders, whereas inflexible positive emotion systems may indicate psychological health. Considering emotional inflexibility within days may provide additional information beyond demographics and mean level and variability of emotions in daily life for detecting anxiety and depressive disorders.

Adolescent Emotion Network Dynamics in Daily Life and Implications for Depression.

Emotion network density describes the degree of interdependence among emotion states across time. Higher density is theorized to reflect rigidity in emotion functioning and has been associated with depression in adult samples. This paper extended research on emotion networks to adolescents and examined associations between emotion network density and: 1) emotion regulation and 2) symptoms of depression. Data from a daily diary study (t = 21 days) of adolescents (N = 151; 61.59% female; mean age = 14.60 years) were used to construct emotion network density scores. Emotion regulation was measured using The Difficulties in Emotion Regulation Scale Short Form (DERS-SF). Depression was measured using the Revised Child Anxiety and Depression Scale-Short Version (RCADS-SV). Associations between emotion network density and DERS-SF were examined through Pearson correlations. Multiple regression analyses examined associations between emotion network density and depression. Emotion network density was not associated with the DERS-SF. Follow-up analyses showed that it was positively associated with non-acceptance of emotions (a subscale of the DERS-SF). Emotion network density was positively associated with RCADS-SV depression. Non-acceptance of emotions may encourage the spread of emotion across time and states given that a feature of non-acceptance is to have secondary emotional responses to one's emotions. Emotion networks that are self-predictive may be a risk factor for adolescent depression.