JMIR Publications

ABSTRACT

Background:

Estimates indicate that more than one in eight people live with a mental health disorder, yet less than half of those suffering receive treatment. The prevalence of mental health disorders along with low rates of seeking treatment may be due to poor mental health awareness. Digital health technologies, like wearables and their associated phone- and web-based applications, have the potential to reduce the mental health awareness gap due to their ease of adoption, objective feedback, and high rate of engagement.

Objective:

To characterize the relationships between mental health and objective wearable-derived measures.

Methods:

We examined the longitudinal results of monthly mental health surveys (Patient Health Questionnaire-2, Generalized Anxiety Disorder 2-item, and Perceived Stress Scale) delivered over 13 months to 181,574 individuals wearing a device (WHOOP Inc., Boston, MA) that measures sleep, cardiorespiratory parameters, and physical activity (up to 307,860 survey responses and 7,942,176 days of total wear time). We utilized generalized linear mixed models and intrapersonal scaling to assess interpersonal and intrapersonal associations between wearable-derived metrics and mental health outcomes.

Results:

Results revealed that mental health outcomes improve with age, are better in males than in females, and are at healthier levels for those within the healthy or overweight range of body mass index relative to those in the underweight or obese range. Interpersonal associations between wearable-derived metrics and mental health outcomes indicate that individuals with better sleep characteristics (i.e., longer sleep durations and more consistent wake and sleep times), higher heart rate variabilities (HRV) and lower resting heart rates (RHR), and higher levels of physical activity report lower levels of depression, anxiety, and stress. Intrapersonal associations between wearable-derived metrics and mental health outcomes displayed similar results as the between-person analyses, with higher HRVs, lower RHRs, and more physical activity generally coinciding with improved mental health outcomes. However, intrapersonal wearable-derived sleep metric associations diverged from the interpersonal association findings when specifically looking at sleep duration and depression, whereby increased levels of sleep within an individual were associated with higher levels of depression.

Conclusions:

These results support a role for monitoring physiology and behaviors via wearables in complementing mental healthcare, as they have the potential to be used to track and optimize sleep behavior, cardiorespiratory physiology, and physical activity.