Friday, April 26, 2024
4/26/2024
PROJECT SUMMARY/ABSTRACT Identifying predictors and indicators of emerging mental illness is a high public health priority. Early intervention will be most effectively implemented if we know who and what to target. Current predictors and risk calculators consist of static measures such as sociodemographics, symptom levels, and cognitive functioning. Yet substantial evidence suggests that the emergence of mental illness occurs in a dynamic interaction with the environment, with both continuity and discontinuity of symptoms over time, and that subtle changes precede most acute episodes. The earliest symptoms are often “nonspecific” as they are precursors to a range of diagnostic outcomes and trajectories. Although there are significant efforts to capture dynamic genetic, structural, electrophysiological, and other brain-based and biological changes accompanying the onset of psychosis, there has been very little characterization of symptom dynamics predicting clinical course, including the temporal sequencing of symptoms during the early phases of major mental illness. The proposed project is a preliminary step in a line of research intended to address this gap of knowledge. The study uses a strategy designed for collecting dynamic data, Experience Sampling Methods (ESM), in a high priority population: adolescents and young adults at elevated risk for psychosis or within the initial five years following a first episode of psychosis (FEP). The aim is to measure a novel target for this population, temporal variability in affect, and examine its relationship to symptoms of particular relevance to poorer outcomes: psychotic-spectrum symptoms and thoughts of self-harm. The proposed study is designed to test initial hypotheses that greater affect variability will be associated with elevations in these symptoms and to explore the potential roles of age and social context in these dynamics. These preliminary data are expected to inform a highly promising line of research into dynamic predictors of critical events and transitions during the early course of major mental illness, features that may also predict long-term trajectories. Early course symptom dynamics are also expected to inform both the understanding of mechanisms of illness progression and novel, including personalized and mobile, interventions to interrupt pathological sequences and improve functional outcomes. Thus the goals of this proposal are consistent with the R21 guidelines emphasizing novelty and innovation, as well as NIMH strategic objectives to chart mental illness trajectories to identify when, where, and how to intervene, and to identify clinically useful dimensions of behavior and behavioral predictors of change.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
