Sleep and Activity Patterns as Transdiagnostic Behavioral Biomarkers in Psychiatry: Initial Insights from the DeeP-DD study (Preprint)

作者：Dylan Hamitouche, Tihare Zamorano, Youcef Barkat, Deven Parekh, Lena Palaniyappan, David Benrimoh · 年份：2025 · DOI：10.2196/preprints.81107 · 被引用次数：3 · 研究领域：Mental Health Research Topics、Sleep and related disorders

BACKGROUND Despite widespread use of symptom rating scales in psychiatry, these tools are limited by reliance on self-report, infrequent administration, and lack of predictive power. This constrains clinicians’ ability to monitor illness trajectories or anticipate adverse outcomes like relapse. Actigraphy, a passive wearable-based method for measuring sleep and physical activity, offers objective, high-resolution behavioral data that may better reflect symptom fluctuations. Prior research has shown associations between actigraphy features and mood or psychosis symptoms, but most studies have focused on narrow diagnostic groups or fixed time windows, limiting clinical translation. OBJECTIVE To examine whether actigraphy-derived sleep and activity features correlate with psychiatric symptom severity in a transdiagnostic psychiatric sample, and to identify which features are most clinically relevant across multiple temporal resolutions. METHODS We present a feasibility case series study analyzing preliminary data from eight outpatients (ages 18–52) enrolled in the Deep Phenotyping and Digitalization at Douglas (DeeP-DD) study, a prospective transdiagnostic study of digital phenotyping. Participants wore wrist-based actigraphy devices (GENEActiv) for up to five months. Symptom severity was measured using a variety of self- and clinician-rated scales. We performed intra-individual Spearman correlations and inter-individual repeated measures correlations across daily, ...