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PEARL is a longitudinal research study that applies a person-centered approach to understanding heterogeneity in mental health. Our study seeks to understand more about well-being using a variety of ambulatory assessment techniques (e.g., biosensors, passive phone data, and self-report via smartphone) that capture granular, day-to-day variation in a a wide variety of factors related to mental health and well-being.
We plan to use this data to model how dynamic changes within-individuals and within-families contribute to differences in mental health challenges like anxiety and depression and health risk behavior like alcohol and drug use. Because ensuring that people get the care that’s right for them at the right time is critical for mitigating and preventing the debilitating personal, interpersonal, and societal consequences of mental illness, an extension of this work will involve testing the benefits of personalized feedback provided in real-time for guidance of self-directed changes in behavior.
Understand both unique and common origins, trajectories, and outcomes of psychopathology and health risk behavior over the lifespan.
Improve translation of clinical science evidence to case-specific applications (i.e., assessment and intervention across diverse individuals) with maximal personalization and precision.
Advance scalable implementation methods that reduce barriers to effective mental health support (e.g., stigma, affordability, accessibility, need for expert adaptation) at the individual level across diverse communities.