Actigraphy Measures of Sleep and Daily Activity May Forecast Depression Relapse
Key Clinical Summary
- Actigraphy measures of sleep regularity, circadian rhythm amplitude, and nocturnal activity were significantly associated with relapse risk in remitted major depression.
- Participants with lower sleep regularity and relative amplitude faced approximately double the relapse hazard over follow-up.
- Digital sleep and rest-activity biomarkers may offer objective relapse risk stratification in outpatient depression care.
A new multicenter observational cohort study assessed whether actigraphy-derived sleep and rest-activity rhythms predict relapse in adults with remitted depression. Results published in JAMA Psychiatry showed that sleep phase variability and daily activity amplitude measured through actigraphy were associated with risk of depression relapse.
These findings may indicate actigraphy as “a potential scalable biomarkers to identify high-risk individuals and enable timely, personalized relapse prevention in [depression],” wrote Andrew C. Tonon, MD, PhD, Department of Psychiatry and Behavioral Neurosciences, McMaster University, Canada, and study co-authors.
Study Findings
The study enrolled 93 adults (mean age 39.1 years; 62% female) with remitted depression (Montgomery-Åsberg Depression Rating Scale [MADRS] ≤14) who contributed about 32,000 actigraphy days of data. Relapse was defined as new or worsening depressive symptoms (MADRS ≥22 for ≥2 weeks), psychiatric hospitalization, emergence of suicidal intent or behavior, or need for antidepressant treatment escalation. Determination of relapse was adjudicated by an independent panel.
Baseline actigraphy metrics independently associated with relapse included lower sleep regularity (hazard ratio [HR] 0.46; 95% CI, 0.28–0.74; P = .002), lower relative amplitude (RA) of rest-activity rhythms (HR 0.45; 95% CI, 0.29–0.70; P < .001), and lower sleep efficiency (HR 0.57; 95% CI, 0.38–0.85; P = .005). Higher wake after sleep onset (HR 1.77; 95% CI, 1.12–2.80; P = .01) and higher nighttime activity (HR 1.86; 95% CI, 1.32–2.62; P < .001) were also associated with increased risk for relapse. In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and persistently lower relative amplitude (RA) (HR, 0.45; 95% CI, 0.21-0.97; P = .046) continued to differentiate individuals who relapsed from those with stable courses.
Clinical Implications
Relapse in depression is common and carries substantial morbidity. Objective longitudinal biomarkers like actigraphy may complement clinical assessment by identifying subtle changes in circadian rest-activity patterns that precede symptomatic relapse. Lower sleep regularity and dampened circadian amplitude reflect disrupted behavioral rhythms that can be difficult to quantify through self-report or infrequent clinical visits alone, raising the possibility of earlier intervention before clinical deterioration.
Digital monitoring tools could enhance personalized follow-up strategies, especially for patients at higher risk due to irregular sleep patterns or nocturnal arousal. As wearable devices proliferate in clinical and consumer settings, standardized protocols and interpretive thresholds will be essential for safe, routine integration of actigraphy data into psychiatric practice. These findings also underscore the importance of sleep and circadian stability management in relapse prevention planning, including consideration of behavioral, pharmacologic, or chronotherapeutic interventions.
Conclusion
Actigraphy-derived measures of sleep and rest-activity rhythms were significantly associated with relapse risk in remitted depression in this Canadian cohort. These findings support further research into digital behavioral biomarkers for proactive depression management and personalized relapse prevention.
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