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| ID | Type | Description | Link |
|---|---|---|---|
| 1R01MH120168-01A1 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of Mental Health (NIMH) | NIH |
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Mood disorders are associated with significant financial and health costs for the United States, partially due to cognitive problems in these patients that can worsen disease course and impair treatment response. This study proposes to use smartphone-based technology to monitor cognitive problems in patients with mood disorders by linking brain network changes with predicted worsening of mood symptoms. The proposed study will provide evidence for using smartphone-based passive sensing as a cost-effective way to predict illness course and treatment response.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Mood disorder group | Participants must meet criteria for one of the following disorders according to Diagnostic and Statistical Manual of Mental Disorders-5 criteria (52): major depressive disorder (MDD), persistent depressive disorder (PDD), bipolar disorder (BD) type I/type II, cyclothymia. Multiple mood disorders are employed, in line with the Research Domain Criteria (RDoC; (53)) framework and the relative imprecision of current symptom diagnostic clusters for tracking treatment responses and course of disease. To ensure adequate representation across diagnostic categories (including controls), the investigators will cap enrollment of major mood disorders (MDD, BD type I/II) to 50%, PDD and cyclothymia to 25% and recruit a healthy comparison group to comprise the remaining 25% of the sample. | ||
| Control group | Participants who do not meet the Diagnostic and Statistical Manual of Mental Disorders-5 criteria for (52): major depressive disorder (MDD), persistent depressive disorder (PDD), bipolar disorder (BD) type I/type II, or cyclothymia. |
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| Measure | Description | Time Frame |
|---|---|---|
| Neuroimaging | a. Neuroimaging based biomarkers of cognitive performance will include Structural brain network Efficiency Interhemispheric Efficiency, Reduced nodal efficiency in ventrolateral prefrontal cortex/altered modularity, Reduced nodal efficiency in anterior cingulate cortex, and Reduced nodal efficiency in salience networks. Neuroimaging will take place while the participant completes the parametric Go/No-go test completed during a functional magnetic resonance imaging after using BiAffect app for 2 weeks, and again after using the BiAffect app for 4 weeks. | Change from week 2 to week 4. |
| BiAffect Metric |
| Measured at the end of week 4 after using the BiAffect app for 4 weeks |
| Clinical symptoms |
| Measured at baseline. |
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Inclusion Criteria:
Exclusion Criteria:
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The investigators will recruit 132 participants (100 with mood disorders, and 32 controls) from the Chicago area, psychiatry clinics at the UIC, and longitudinal studies of Dr. Langenecker (MH091811 and MH 101487). All subjects will be recruited using community outreach efforts, not limited to but including listserv emails, flyers, word of mouth, and health fairs.
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| Name | Affiliation | Role |
|---|---|---|
| Olusola Ajilore, MD, PhD | University of Illinois at Chicago | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Illinois at Chicago | Chicago | Illinois | 60612 | United States |
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| ID | Term |
|---|---|
| D019964 | Mood Disorders |
| D003865 | Depressive Disorder, Major |
| D001714 | Bipolar Disorder |
| D019263 | Dysthymic Disorder |
| D003527 | Cyclothymic Disorder |
| ID | Term |
|---|---|
| D001523 | Mental Disorders |
| D003866 | Depressive Disorder |
| D000068105 | Bipolar and Related Disorders |
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| Cognition |
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| Change from week 2 to week 4 |