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BACKGROUND Remotely captured spoken language could provide objective, regular indicators of depression symptom severity. However, research to date has largely used non-clinical, cross-sectional written language and complex machine learning (ML) approaches with limited interpretability. METHODS We used linear mixed-ef...
Depression symptom severity was associated with five lexical features, including reductions in word count measures, use of first-person plural pronouns and positive word frequency, andLexical features and vector embeddings did improve prediction accuracy beyond baseline models.
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