JMIR Publications

ABSTRACT

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, weekly, monthly, and full-duration averages. Longitudinal slopes of actigraphy and symptom trends were also analyzed.

Results:

Intra-individual analyses revealed that later rise times were significantly associated with higher weekly PHQ-9 scores in participant #7 (ρ = 0.74, P=.0003) and participant #4 (ρ = 0.78, P=.022), as well as higher weekly GAD-7 scores in participant #7 (ρ = 0.59, P=.026). While similar trends were observed at daily and monthly timescales, the weekly resolution yielded the most robust significance. Inter-individual analyses showed that weeks with later average rise time correlated with higher PHQ-9 (r = 0.48, P=.0003) and GAD-7 scores (r = 0.38, P=.032), with the PHQ-9 association remaining significant after Bonferroni correction (Bonferroni-corrected P=.015). Increased light physical activity was linked to lower PHQ-9 scores weekly (r = -0.44, P=.001) and monthly (r = -0.53, P=.014). Over the whole duration of the study, increased levels of sedentary activity were associated with lower GAD-7 scores (ρ=0.74; P=8.43x10-23).

Conclusions:

Our findings highlight actigraphy-derived sleep and activity features, particularly rise time and physical activity, as promising transdiagnostic markers of psychiatric symptom burden. Their consistent associations across temporal scales and diagnostic groups underscore their potential utility for scalable, real-world clinical monitoring. Future work should validate these findings in larger cohorts and explore advanced analytical methods to capture circadian rhythmicity and symptom dynamics more precisely.