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

Not Applicable

Completed

• Conditions: Depressive Disorder
• Interventions: Other: Behavioral-data driven support

• Registration Number: NCT02499094
• Lead Sponsor: Ginger.io

Brief Summary

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.

Detailed Description

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.

Study Timeline

• Study Start: 2014-12
• Status Verified: 2015-07
• Primary Completion: 2015-07
• Study First Submitted: 2015-07-14
• Study First Submitted QC: 2015-07-14
• Last Update Submitted: 2015-07-14
• Study First Posted: 2015-07-15
• Last Update Posted: 2015-07-15

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 1004

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

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Intervention A- Heuristic based	Behavioral-data driven support	Behavioral-data driven support, both mobile phone application and phone-based, informed by their self-reported symptom assessment as well as simple heuristic-based behavioral measures
Intervention B- Machine Learning Based	Behavioral-data driven support	Behavioral-data driven support, both mobile phone application and phone-based, informed by their self-reported symptom assessment as well as machine learning model-based behavioral measures

Primary Outcome Measures

Name	Time	Method
Change in depression symptom severity	6 months	Change in the 9-item Patient Health Questionnaire (PHQ-9) score from baseline

Secondary Outcome Measures

Name	Time	Method
Change in patient activation	6 months	Change in the 13-item Patient Activation Measure score from baseline