Using Smartphone Sensors to Detect Mental Health Trends via Daily Behavior Monitoring

Recent research highlights the potential of smartphone sensors in monitoring and identifying mental health patterns through everyday behaviors. While smartphones are already valuable tools for tracking sleep, physical activity, and heart rate, a new study demonstrates their capability to reveal subtle indicators of psychological well-being.

Published in JAMA Network Open, the study involved 557 adults over a span of 15 days in 2023. Researchers from the University of Michigan, University of Minnesota, and University of Pittsburgh employed smartphone sensors as passive observers, analyzing digital footprints such as movement, sleep routines, phone usage habits, and social interactions. These unobtrusive data streams provided insights into how mental health issues manifest in routine behaviors.

The findings reveal that numerous mental disorders share common behavioral signatures, such as increased time spent at home, late sleeping patterns, infrequent phone charging, reduced physical movement, and diminished social communication. These behaviors are linked to the concept of the "p-factor," which correlates with a broad spectrum of mental health conditions.

According to Aidan Wright, a psychology professor at the University of Michigan, specific behavioral markers like fewer phone calls or decreased walking can correspond to particular problems such as social withdrawal or feeling unwell. The implications of these findings suggest that smartphone sensors could be harnessed as tools for early detection, ongoing symptom monitoring, and potentially guiding treatment strategies for various psychiatric conditions.

Despite the promise, digital psychiatry has faced hurdles, largely due to reliance on heterogeneous diagnostic criteria like DSM-5, which may not always effectively capture distinct behavioral signatures. Additionally, many individuals have multiple diagnoses, complicating behavioral interpretations. Wright emphasizes that current diagnostic approaches are limited in parsing the complexity of mental health disorders.

The study’s innovative approach underscores the importance of behavioral organization in understanding mental illness and aims to enhance early intervention methods. Monitoring via passive sensing could allow clinicians to connect individuals with help before conditions escalate, ultimately improving outcomes, reducing healthcare costs, and lowering stigma associated with mental health issues.

This research marks one of the largest efforts to utilize smartphone sensors for mental health prediction, offering promising avenues for integrating digital tools into psychiatric care and research. As digital mental health monitoring advances, it holds significant potential to transform how mental health issues are detected and managed early in various populations.

Source: https://medicalxpress.com/news/2025-07-smartphone-sensors-reveal-mental-health.html