Exploring negative affect dynamics in high resolution: within-person relationship of inertia and instability with depression is mediated by affect intensity

Background: Temporal patterns of affective functioning such as emotional inertia and instability may indicate changes in emotion regulation that predict depression. However, affect dynamics’ incremental validity over affect intensity and exposure to stressors in predicting depression has been questioned.Methods: We collected longitudinal data regarding momentary affective states (measured multiple times a day), perceived stressors and depressive symptoms (measured every three days) from a general population sample during the COVID-19 pandemic’s first wave in Hungary. The final dataset included 7165 affective states surveys from 125 participants, which were aggregated in 464 three-day measurement windows. Using multilevel models, we explored the unique effects of within-person changes in mean level, inertia, and instability of negative affective states (NA), and stressor-exposure on two domains of depression (anhedonia and negative mood and thoughts) within the three-day windows.Results: Within-person increases in NA inertia and NA instability showed significant positive associations with negative mood and thoughts. These effects did not remain significant after adjusting for mean levels of NA. Multilevel mediation analysis revealed that within individuals, NA inertia and instability indirectly predicted negative mood and thoughts through elevated NA mean.Limitations: The application of self-report questionnaires might bias the results, and the overrepresentation of female participants could limit the generalizability of the findings.Conclusions: Specific patterns of temporal affective functioning are indirect predictors of depressive symptoms at the within-individual level. Our findings may facilitate automated depression risk assessment on the basis of simple affective time series.