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Background: Anxiety and depression symptoms are highly correlated in adults with depression; however, little is known about their interaction and temporal dynamics of change during treatment. Thus, the primary aim of this study was to examine the temporal dynamics of anxiety and depressive symptoms during a 12-week therapist-supported, smartphone-delivered digital health intervention for symptoms of depression and anxiety, the Meru Health Program (MHP).
Method: A total of 290 participants from the MHP were included in the present analyses (age Mean = 39.64, SD = 10.25 years; 79% female; 54% self-reported psychotropic medication use). A variance components model was used to examine whether (1) reporting greater anxiety during the current week relative to anxiety reported in other weeks would be associated with greater reporting of depressive symptoms during the current week, while a time-varying effect model was used to examine whether, (2) consistent with findings reported by Wright et al. (2014), the temporal relationship between anxiety and depressive symptoms during the intervention would be expressed as a quadratic function marked by a weak association at baseline, followed by an increase to a peak before demonstrating a negligible decrease until the end of treatment.
Results: In support of hypothesis 1, we found that reporting greater anxiety symptoms during the current week relative to other weeks was associated with greater depressive symptoms during the current week. Contrary to hypothesis 2, the temporal relationship between anxiety and depressive symptoms evidenced a recurring pattern, with the association increasing during the initial weeks, decreasing during mid-treatment and sharply increasing toward the end of treatment.
Conclusions: The present findings demonstrate that anxiety and depressive symptoms overlap and fluctuate in concert during a smartphone-based intervention for anxiety and depressive symptoms. The present findings may warrant more refined intervention strategies specifically tailored to co-occurring patterns of change in symptoms.
Examining the spatial and temporal relationship between social vulnerability and stay-at-home behaviors in New York City during the COVID-19 pandemic