Background: Low average affect, measured using ecological momentary assessment (EMA), has been consistently linked with depression, generalized anxiety, and social anxiety, supporting trait-like negative affect as a shared underlying feature. However, while theoretical models of emotion regulation would also implicate greater variability in daily affect in these conditions, empirical evidence linking EMA of mood variability with affective disorders is mixed. We used multilevel modeling to test relationships of daily mood and mood variability with depression, generalized anxiety, and social anxiety symptoms.
Methods: Participants (N = 1004; 72.31 % female; Mage = 40.85) responded to EMA of mood 2-3×/day and completed measures of depression (PHQ-8), generalized anxiety (GAD-7), and social anxiety (SPIN) every three weeks.
Results: Lower mean affect predicted all symptoms at both the between-person (PHQ-8: β = -0.486, p < 0.001; GAD-7: β = -0.429, p < 0.001; SPIN: β = -0.284, p < 0.001) and within-person (PHQ-8: β = -0.219, p < 0.001; GAD-7: β = -0.196, p < 0.001; SPIN: β = -0.049, p < 0.001) levels. Similarly, at the between-person level, greater affective variability was linked with all three clinical symptoms (PHQ-8: β = 0.617, p < 0.001; GAD-7: β = 0.703, p < 0.001; SPIN: β = 0.449, p < 0.001). However, within-person, affective variability related to depression (β = 0.144, p < 0.001) and generalized anxiety (β = 0.150, p < 0.001), but not social anxiety (β = 0.006, p = 0.712).
Limitations: The COVID-19 pandemic lockdown period occurred midway through the study.
Conclusion: Findings point to common and specific emotion dynamics that characterize affective symptoms severity, with implications for affective monitoring in a clinical context.
Keywords: Anxiety; Depression; Digital health; Ecological momentary assessment; Personal sensing; Social anxiety.
Copyright © 2024 Elsevier B.V. All rights reserved.