Observational studyJMIR mental health2025
Multimodal Digital Phenotyping Study in Patients With Major Depressive Episodes and Healthy Controls (Mobile Monitoring of Mood): Observational Longitudinal Study.
Observational study in JMIR mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 4 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Digital Markers for Passive Remote Monitoring of Bipolar Disorder: Systematic Review.JMIR mental health · 2026Pooled it
- The Role of Digital Biomarkers in Physiological Signal-Based Depression Assessment: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Sensor-Based Technologies for the Detection of Unwanted Loneliness in Older Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Key Features of Digital Phenotyping for Monitoring Mental Disorders: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Digital phenotyping with large language models to detect depressive state changes in patients.NPJ digital medicine · 2026Article
- Contribution of Longitudinal Mobile Health Measures in the Dynamic Track of Patients With Major Depressive Disorder: Multiple Centers, Prospective Cohort Study Using Functional Data Analysis and Machine Learning.JMIR mHealth and uHealth · 2026Article
- Digital Phenotyping via Passive Network Traffic Monitoring: Prospective Observational Study in University Students.JMIR formative research · 2026Observational
- A review of the application of digital phenotyping in predicting peripartum depressive symptoms.NPJ digital medicine · 2026Article
- Variability in self-reported depression symptomology and associated behavioral markers in digital phenotyping.Scientific reports · 2026Article
- Digital tools for assessing bipolar disorder: A scoping review of the current landscape.Neuroscience applied · 2026Article
- Multimodal Sleep Measurement and Alignment Analysis in Outpatients With Major Depressive Episode: Observational Study.JMIR mHealth and uHealth · 2025Observational
- Predicting and Monitoring Symptoms in Patients Diagnosed With Depression Using Smartphone Data: Observational Study.Journal of medical Internet research · 2024Observational
- Development and validation of a multimodal data collection system for adolescent mental health management.Digital healthArticle
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMood disorders are among the most common mental health conditions worldwide. Wearables and consumer-grade personal digital devices create digital traces that can be collected, processed, and analyzed, offering a unique opportunity to quantify and monitor individuals with mental disorders in their natural living environments.
objectiveThis study comprised (1) 3 subcohorts of patients with a major depressive episode, either with major depressive disorder, bipolar disorder, or concurrent borderline personality disorder, and (2) a healthy control group. We investigated whether differences in behavioral patterns could be observed at the group level, that is, patients versus healthy controls. We studied the volume and temporal patterns of smartphone screen and app use, communication, sleep, mobility, and physical activity. We investigated whether patients or controls exhibited more homogenous temporal patterns of activity when compared with other individuals in the same group. We examined which variables were associated with the severity of depression.
methodsIn total, 188 participants were recruited to complete a 2-phase study. In the first 2 weeks, data from bed sensors, actigraphy, smartphones, and 5 sets of daily questions were collected. In the second phase, which lasted up to 1 year, only passive smartphone data and biweekly 9-item Patient Health Questionnaire data were collected. Survival analysis, statistical tests, and linear mixed models were performed.
resultsSurvival analysis showed no statistically significant difference in adherence. Most participants did not stay in the study for 1 year. Weekday location variance showed lower values for patients (control: mean -10.04, SD 2.73; patient: mean -11.91, SD 2.50; Mann-Whitney U [MWU] test P=.004). Normalized entropy of location was lower among patients (control: mean 2.10, SD 1.38; patient: mean 1.57, SD 1.10; MWU test P=.05). The temporal communication patterns of controls were more diverse compared to those of patients (MWU test P<.001). In contrast, patients exhibited more varied temporal patterns of smartphone use compared to the controls. We found that the duration of incoming calls (β=-0.08, 95% CI -0.12 to -0.04; P<.001) and the SD of activity magnitude (β=-2.05, 95% CI -4.18 to -0.20; P=.02) over the 14 days before the 9-item Patient Health Questionnaire records were negatively associated with depression severity. Conversely, the duration of outgoing calls showed a positive association with depression severity (β=0.05, 95% CI 0.00-0.09; P=.02).
conclusionsOur work shows the important features for future analyses of behavioral markers of mood disorders. However, among outpatients with mild to moderate depressive disorders, the group-level differences from healthy controls in any single modality remain relatively modest. Therefore, future studies need to combine data from multiple modalities to detect more subtle differences and identify individualized signatures. The high dropout rates for longer study periods remain a challenge and limit the generalizability.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.