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Trial record 2 of 3 for:    cogito

Quantified Mobile Sensing for Improving Diagnosis and Measuring Disease Progression

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ClinicalTrials.gov Identifier: NCT02742064
Recruitment Status : Active, not recruiting
First Posted : April 18, 2016
Last Update Posted : July 28, 2017
Sponsor:
Collaborators:
Massachusetts General Hospital
Partners HealthCare
Information provided by (Responsible Party):
Cogito Health Inc

Brief Summary:
The purpose of this study is to determine if a mobile sensing platform can passively and objectively detect the presence of clinically significant mood disorder symptomatology and symptom progression over time. Meeting this goal will allow for improved risk categorization, prediction of relapse, and measurement of disease progression in a lifetime prevalence population.

Condition or disease Intervention/treatment
Depression Bipolar Disorder Other: Cogito Companion Mobile Phone Application

Study Type : Observational
Actual Enrollment : 899 participants
Observational Model: Case-Control
Time Perspective: Prospective
Official Title: Quantified Mobile Sensing for Improving Diagnosis and Measuring Disease Progression
Study Start Date : February 2015
Estimated Primary Completion Date : December 31, 2017
Estimated Study Completion Date : March 31, 2018

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Bipolar Disorder

Group/Cohort Intervention/treatment
MDD-Single Episode
1. Subjects who have experienced 1 episode of major depressive disorder (MDD) in their lifetime.
Other: Cogito Companion Mobile Phone Application
Other Name: Cogito Mobile Sensing Platform

MDD-Recurrent
1. Subjects who have experienced 2 or more episodes of depressive disorder (MDD) in their lifetime.
Other: Cogito Companion Mobile Phone Application
Other Name: Cogito Mobile Sensing Platform

Bipolar Disorder
1. Subjects who have been diagnosed with bipolar disorder in their lifetime.
Other: Cogito Companion Mobile Phone Application
Other Name: Cogito Mobile Sensing Platform




Primary Outcome Measures :
  1. Severity of MDD symptoms as assessed by QIDS SR [ Time Frame: 6 months ]
  2. Severity of Mania symptoms as assessed by ASRM [ Time Frame: 6 months ]


Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Participants will be selected from the MoodNetwork, an online network of individuals with mood disorders, which is hosted by MGH. A subset of participants with mood disorders enrolled in MoodNetwork will download Cogito's mobile sensing platform on their mobile phones.
Criteria

Inclusion Criteria:

  • Age 18 or older
  • Have a smartphone and cell service plan, including voice and data, that meets the device requirements of the Mobile Sensing Platform.
  • Enrolled in the MoodNetwork

Exclusion Criteria:

  • Report positively on the QIDS-SR suicide item during study intake
  • Total score greater than 15 on the QIDS-SR during the screening process

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02742064


Locations
United States, Massachusetts
Massachusetts General Hospital
Boston, Massachusetts, United States, 02114
Sponsors and Collaborators
Cogito Health Inc
Massachusetts General Hospital
Partners HealthCare

Responsible Party: Cogito Health Inc
ClinicalTrials.gov Identifier: NCT02742064     History of Changes
Other Study ID Numbers: 1R44MH107065-01 ( U.S. NIH Grant/Contract )
First Posted: April 18, 2016    Key Record Dates
Last Update Posted: July 28, 2017
Last Verified: July 2017
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

Additional relevant MeSH terms:
Bipolar Disorder
Disease Progression
Bipolar and Related Disorders
Mental Disorders
Disease Attributes
Pathologic Processes