Digital Phenotyping Identifies Depression Monitoring Parameters
A 2026 scoping review in JMIR Mhealth Uhealth by Busshart et al. synthesizes digital phenotyping parameters used to monitor and predict depression from studies published between Jan 1, 2021 and Nov 26, 2025, identifying 19 studies covering 85,193 participants. The authors categorize five parameter groups and 11 common metrics (e.g., step count, heart rate variability, sleep duration, mood ratings), noting multimodal passive and self-report fusion and implications for scalable digital mental-health tools.
Key Points
- 1Maps five parameter categories and 11 common metrics across 19 studies, covering 85,193 participants
- 2Highlights multimodal passive and self-report fusion as predominant approach for individualized symptom tracking
- 3Enables comparability and guides selection of sensors (steps, HRV, sleep, mood) for predictive models
Scoring Rationale
Comprehensive, peer-reviewed synthesis across 85,000 participants increases impact, limited by review-level novelty compared with primary empirical breakthroughs.
Sources
Public references used for this report.
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