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ABSTRACT: Background
Digital phenotyping and monitoring tools are the most promising approaches to automatically detect upcoming depressive episodes. Especially, linguistic style has been seen as a potential behavioral marker of depression, as cross-sectional studies showed, for example, less frequent use of positive emotion words, intensified use of negative emotion words, and more self-references in patients with depression compared to healthy controls. However, longitudinal studies are sparse and therefore it remains unclear whether within-person fluctuations in depression severity are associated with individuals' linguistic style.Methods
To capture affective states and concomitant speech samples longitudinally, we used an ambulatory assessment approach sampling multiple times a d
SUBMITTER: Hartnagel LM
PROVIDER: S-EPMC11787911 | biostudies-literature | 2025 Mar
REPOSITORIES: biostudies-literature