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 datasets with different timescales (90 minutes, daily), we examined emotion network density (a metric of emotional rigidity) as a predictor of clinical levels of anxiety and/or depression. Design: Mobile-based intensive longitudinal assessments. Methods: In study 1, 119 participants (61 anxious and depressed, 58 controls) rated a variety of negative (NE) and positive emotions (PE) 9x/day for 8 days using a mobile phone app. In study 2, 169 participants (97 anxious and depressed, 72 controls) completed an online survey on their NE and PE daily for 50 days. Multilevel vector autoregressive models were run to compute NE and PE network density. Results: Anxious and depressed participants showed higher NE network density, but lower PE network density than controls when emotions were assessed every 90 minutes (study 1). Group differences on emotion network density were not significant when we used daily assessment of emotions (study 2). In study 1, both NE and PE network density also significantly predicted participants’ diagnostic status above and beyond demographics and the mean and standard deviation of NE and PE. In study 2, NE and PE network densities were not significant predictors. Conclusions: Greater rigidity of NE and lower rigidity of PE, indexed by emotion network density, are potential clinical markers of anxiety and depression when assessed at 90-minute intervals (vs daily intervals). 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 depression.