(PS9-89) Investigating Anxiety and Depression Trajectories in CBT: A Random-Intercept Cross-Lagged Panel Model Approach

Abstract Text:

Background: While the associations and comorbidity between depression and anxiety have been well-established in the current literature, fewer studies have explored how changes in one symptom influence the trajectory of the other over time within structured therapeutic settings. Understanding these bidirectional effects is crucial for refining treatment strategies, as anxiety and depression often exhibit overlapping but distinct mechanisms of change. This study uses RI-CLPM to investigate the bidirectional relationship between anxiety and depression across multiple assessment time points during in-person therapy, with the goal of informing targeted approaches that address symptom interdependence and optimize treatment outcomes.

Methods: A total of 948 participants were recruited from an anxiety treatment center offering cognitive behavioral therapy (CBT) who completed self-report assessments of symptoms at the beginning, middle and end of treatment and were invited to consent to use their clinical information for research purposes. Anxiety was measured using the Generalized Anxiety Disorder-7 (GAD-7), while depression was assessed with the Beck Depression Inventory-II (BDI-II). To examine temporal associations between anxiety and depression, we employed RI-CLPM, which allowed us to differentiate stable, trait-like influences from dynamic, time-dependent symptom fluctuations.

Results: Results indicated significant stability in anxiety across time points (β = 0.316, p = .018; β = 0.432, p = .008), whereas depression showed non-significant stability (β = 0.076, p = .354; β = 0.086, p = .362). Cross-lagged paths revealed that baseline anxiety significantly predicted mid-intervention depression (β = 0.245, p = .006), and mid-intervention anxiety predicted post-intervention depression (β = 0.226, p = .037). However, depression did not significantly predict later anxiety at any time point. Concurrent covariances between anxiety and depression remained significant (p < .001) throughout the intervention, reinforcing their interdependent nature.

Conclusion: These findings suggest that anxiety plays a leading role in driving depressive symptoms during CBT, highlighting the importance of prioritizing early interventions that target anxiety to prevent subsequent depressive episodes. The non-significant cross-lagged effects from depression to anxiety suggest that while depressive symptoms fluctuate, they may not strongly contribute to later anxiety levels in the context of CBT for anxiety. Future research should investigate potential moderators—including individual differences in symptom severity, treatment adherence, and engagement patterns—to optimize outcomes. Additionally, exploring how specific CBT components uniquely influence symptom trajectories may inform the development of more personalized and adaptive interventions. Understanding how engagement levels impact treatment effectiveness could refine best practices for maximizing therapeutic benefits. These insights could contribute to more effective, scalable, and data-driven approaches to improving mental health outcomes across diverse populations.