AWARDEES
IMPACT-MH Awardees
1U24MH136069-01
Data Coordination Center (DCC)
Coordinating Individually Measured Phenotypes to Advance Mental Health Research
Yale University
1U01MH136535-01
PREDiCTOR
Phenotypes REimagined to Define Clinical Treatment and Outcome
Icahn School of Medicine at Mount Sinai
1U01MH136497-01
IMPACT-MH
Clinical and behavioral fingerprints of psychopathology
Yale University
1U01MH136062-01
ACE-D
Accelerating Cognition-guided signatures to Enhance translation in Depression
Stanford University
1U01MH136059-01
JASPer-MH
Jointly Assessed Scalable Phenotypes for Mental Health
Massachusetts General Hospital
1U01MH136025-01
COMPASS
A comprehensive mobile precision approach for scalable solutions in mental health treatment
University of Michigan at Ann Arbor
1U01MH136020-01
PPSN
The Pediatric Precision Sleep Network
University of Pittsburgh at Pittsburgh
1U01MH135970-01
Person-centered diagnostics and prediction for child dysregulatory psychopathology using novel phenotypes
Oregon Health & Science University
1U01MH135901-01
HALO
Developing Data-Driven Clinical Signatures for People Who Experience Hallucinations
University of Washington
1UF1MH136537-01A1
ARTEMIS
Analyses to Reveal Trajectories and Early Markers of Imminent Shifts in Suicidal States
Ohio State University
1UF1MH141632-01
SPARC-XP
Scalable Phenotyping to Assay Risk in Childhood after eXposures in Pregnancy
Massachusetts General Hospital
1UF1MH141129-01
REACH
Behavioral Phenoscreening: Remote Assessment of Child Mental Health
New York University School of Medicine
IMPACT Point People
Connecting the DCC to our research partners
OHSU
Develops ML methods to more precisely predict child mental-health diagnoses and outcomes.
ACE-D
Derives a cognitive-control signature for depression and tests it to guide treatment choice.
ARTEMIS
Identifies imminent shifts in suicide risk—who, which signals, and when—for actionable care.
REACH
Creates remote behavioral screening to catch externalizing problems early and direct support.
SPARC-XP
Builds scalable phenotyping to estimate neurodevelopmental risk from prenatal infection exposure.
COMPASS
Matches patients to digital vs clinic care across episodes for timely, personalized treatment.
JASPer
Models youth trajectories to trigger scalable stepped-care before school/work is derailed.
Duke-PMA
Validates low-burden models predicting adolescent psychiatric risk up to a year ahead.
TRACC-MH
Validates dynamic cognitive phenotypes to better time interventions for serious mental illness.
HALO
Separates dangerous from benign hallucinations to target urgent care only when needed.
PPSN
Uses sleep-based markers to flag pediatric risk earlier in primary care.
Yale IMPACT
Builds multimodal "clinical fingerprints" from EHR, tasks, and speech to forecast symptoms and outcomes.
PREDICTOR
Combines interviews, smartphone passives, and EHR text to predict disengagement, ER use, and hospitalization.