Modeling and Predicting Real World Behavior Using Mobile Sensor Data on Patients With Major Depressive Disorder

Modeling and Predicting Real World Behavior Using Mobile Sensor Data on Patients With Major Depressive Disorder: Protocol for a Randomized Controlled Study

The purpose of this study is to validate the effectiveness of using an integrated mobile sensing platform to deliver large-scale data-driven interventions to patients with depression.

This study is a smartphone-based, randomized, single-blind, controlled parallel-

design study with two intervention arms and one control arm. The two intervention arms

will receive in-app messages and phone-based support, which will be triggered by

participant's self-reported surveys and passive behavioral data gathered through a

smartphone app. The study will include a nationwide sample of adult (18 years or older)

smartphone users, who are currently experiencing depressive symptoms. The primary

outcome will be decrease in depression symptom severity, as measured by the 9-item

Patient Health Questionnaire, over 6 months.

Inclusion Criteria:

• Currently suffering from depression (as measured by a PHQ-9 score of 10 or more at the time of screening)
• Own an iPhone or Android smartphone with a mobile voice calling plan with a US carrier
• Fluency in English

Exclusion Criteria:

• Participants with visual or hearing impairment
• Recent history of pregnancy (currently pregnant or those who have given birth within the past four months at the time of screening)
• Recent loss of a loved one (within the past two months at the time of screening)
• Unable or unwilling to accept End User License Agreement, or to provide information regarding their demographic characteristics and mental health history