Depression Dynamics across a Decade: Density in Daily Depressive Affect and Yearly Depressive Symptoms

Recent conceptualizations of depression and supporting empirical work suggests that elevations and alleviations of depressive symptoms can be understood from a dynamic systems perspective. In parallel, researchers have turned to network models to study characteristics of the depression system. Many of these studies have focused on individual differences, however, modeling between-person and group-level differences in network models of depression. Given that individual differences do not necessarily elucidate intraindividual change, the present study aimed to further the study of depression as a system by exploring whether density of depressive affect at the daily timescale differs within individuals at five different timepoints across a ten-year span. Further, density of depressive affect was used as a time-varying and time-invariant covariate in a transition model to predict individual’s likelihood of transitioning into or being in a depressive mood state from year to year. Density of the depressive affect cluster was shown to have moderate to low, however, significant stability over time, and majority of the variance in depressive affect density was found to reside within, as opposed to between, individuals. Time-varying depressive affect density in conjunction with individuals time-varying levels of average negative affect was found to be significantly related to the likelihood of being in a depressed mood state at the next wave for individuals who were in a depressive mood state at the previous wave. The results of these individual-level analyses are discussed in terms of a dynamic systems perspective of depression and implications of the results for clinical interventions are considered.