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Personalized Deep Learning Models of Rapid Changes in Major Depressive Disorder Symptoms using Passive Sensor Data from Smartphones and Wearable Devices

Award Number: R01MH123482
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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ABSTRACT Major depressive disorder (MDD) is highly prevalent and the leading cause of global disease burden. Associated with over 1,000 different symptom profiles, MDD is highly heterogeneous. The majority of MDD symptom change occurs across hours. Consequently, there is a need to increasingly focus MDD research on personalized assessment of these rapid symptom fluctuations. To date, personalized models of MDD have shown promise, but relied solely on self-report measures. There is thus a critical need to develop personalized models of MDD that incorporate objective signals. Passively collected information from smartphones and wearable sensors can continuously and unobtrusively track behavioral and physiological signals related to core disturbances associated with MDD, including psychomotor retardation, sleep disturbances, social contact, behavioral activation, heart rate variability, and screen time. Preliminary data suggest that personalized artificial intelligence (i.e., personally weighted deep learning models) are well suited for creating novel personalized digital biomarkers of these passive indicators, and that these biomarkers can predict rapid changes in MDD symptoms. This proposal will investigate the ability to develop personalized deep learning models of rapid changes in MDD symptoms among a nationally representative sample of 120 treatment seeking adults with MDD across 90 days using passively collected data from smartphones and wearable sensors. This proposal aims to test the accuracy of personalized, subtyped, and cohort-based modeling techniques and uncover personalized digital biomarkers of moment-to-moment changes in MDD symptoms. The project proposes the following innovations: it will (1) conduct the first passive-sensing study of MDD in a nationally-representative cohort; (2) utilize deep learning models to aid in the discovery of novel maintenance factors of MDD symptom changes; and (3) use personalized multimodal assessments of MDD to address the heterogeneity in MDD. In line with the aims of the NIMH Research Domain Criteria (RDoC), this project will study MDD symptom changes across multiple units of analysis and integrate multiple systems. This study will provide a critical step towards uncovering novel personalized maintenance patterns of MDD symptom changes in daily life. Further, it will allow for scalable personalized treatments to be developed using technology to deliver behavioral interventions in the moments immediately preceding rapid MDD symptom changes.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2023 ( Subtotal = $520,321 )
2023	2023	TRUSTEES OF DARTMOUTH COLLEGE	7 LEBANON ST	HANOVER	NH	03755	GRAFTON	USA	Mental Health Research Grants	000	4	6/2/2023	NON-COMPETING CONTINUATION	$520,321
														Subtotal = $520,321

Issue Date FY: 2022 ( Subtotal = $527,777 )
2022	2022	TRUSTEES OF DARTMOUTH COLLEGE	7 LEBANON ST	HANOVER	NH	03755	GRAFTON	USA	Mental Health Research Grants	000	3	5/26/2022	NON-COMPETING CONTINUATION	$527,777
														Subtotal = $527,777

Issue Date FY: 2021 ( Subtotal = $493,784 )
2021	2021	TRUSTEES OF DARTMOUTH COLLEGE	6001 PARKHURST HALL STE 207	HANOVER	NH	03755	GRAFTON	USA	Mental Health Research Grants	000	2	5/26/2021	NON-COMPETING CONTINUATION	$493,784
														Subtotal = $493,784

Issue Date FY: 2020 ( Subtotal = $570,435 )
2020	2020	TRUSTEES OF DARTMOUTH COLLEGE	1 HINMAN DARTMOUTH COLLEGE	HANOVER	NH	03755	GRAFTON	USA	Mental Health Research Grants	000	1	8/5/2020	NEW	$570,435
														Subtotal = $570,435

Grand Total All Awards = $2,112,317

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Personalized Deep Learning Models of Rapid Changes in Major Depressive Disorder Symptoms using Passive Sensor Data from Smartphones and Wearable Devices

Award Number: R01MH123482

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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