 The study investigates how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time using distributional semantics methods applied to a large corpus of text-based online therapy sessions. The results show that both previously established LIWC markers of depression and the novel linguistic indicators of activation were strongly associated with depression scores and longitudinal patient trajectories, suggesting that emotional tone, pronoun rates, words related to sadness, health, and biology, and BA-related LIWC categories are complementary in explaining more of the variants in the PHQ score together than they do independently. This study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support. This article was authored by Hannah A. Burkhart, George S. Alexopoulos, Michael D. Pullman, and others.