Assessing the validity of a digital measure of depression and anxiety: a digital health study

Data easily obtained from Smartphones and hats can provide almost continuous objective information that enables a wide range of physical, behavioral and emotional domains in mental health conditions, including depression and anxiety. The widespread use of digital penotyping can revolutionize the assessment of depression and anxiety in research and clinical care, but the field has lacked strong studies that demonstrate the use of this method. This paper describes the design and implementation of the Digital Mental Health Study (DMHS), which collected up to 12 months of Sensor Data from iPhone and Apple participants on youth, gender and depression severity. In order to be able to use these digital denotypes to search for the severity and heterogeneity of depression and anxiety, and we found stress based on the test to evaluate the factors of depression, anxiety, and physical stress as widely as possible while reducing the burden of measurement on the participant. We report here the strategies used to recruit the DMHS sample, the process used to develop study methods and initial policies that describe signs of high engagement and adherence over a 12-month period.

• † University of California, Los Angeles, Depression Great Challenge
• Washington University in St. Louis
• § University of Arizona
• University of Washington
• †† University of California, Los Angeles, AI & Smart Life Center
• * Equal contribution