JMIR Publications

ABSTRACT

Background:

Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and disease progression of mental health conditions.

Objective:

This virtual 1-year long observational study was designed with the objective of creating a longitudinal dataset combining self-reported health outcomes, healthcare utilization, and quality of life data with activity tracker and app-based behavior data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity.

Methods:

Individuals who were existing members of an online health community (Achievement, Evidation Health Inc., San Mateo CA) and were 18 years and older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year long study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9 and 12. In this analysis we report on baseline characteristics of the sample, including mental health disease severity and healthcare utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and healthcare utilization.

Results:

Of the 1,304 participants enrolled in the study, 1,277 individuals completed the baseline survey and 1,068 individuals had sufficient activity tracker data. Mean age was 33 years (SD: 9 years), and the majority of the study population was female (77%, 994/1,288) and identified as Caucasian (88%, 1,137/1,288). At baseline, 95% (1,211/1,277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively-tracked behavioral traits are associated with more severe forms of anxiety and/or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep.

Conclusions:

These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.