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Implementing Learning Health System Principles to Advance the Evaluation and Treatment of Clinical High-Risk for Psychosis
Preprint   Open access

Implementing Learning Health System Principles to Advance the Evaluation and Treatment of Clinical High-Risk for Psychosis

Cheryl Y.S. Foo, Lauren Utter, Abigail L. Donovan, Corinne Cather, Daphne J. Holt and Jacqueline A. Clauss
medRxiv
Cold Spring Harbor Laboratory Press, 1.1
05/11/2025
DOI: 10.1101/2025.05.09.25327345
PMCID: PMC12083588
PMID: 40385432
url
https://doi.org/10.1101/2025.05.09.25327345View
Preprint (Author's original) This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

Early intervention for individuals with clinical high-risk for psychosis (CHR-P) aims to prevent the onset of serious mental illnesses like schizophrenia, but models for specialized care remain underdeveloped. We describe the development, feasibility, and value of a CHR-P evaluation and treatment program built on learning health system principles. We demonstrate that referral and intake clinical assessment data can improve the characterization and identification of individuals with CHR-P. The Resilience Evaluation-Social Emotional Training (RE-SET) Program, developed as part of a continuum of psychosis care programs at Massachusetts General Hospital, systematically collects clinical data at referral, intake evaluation, and during treatment. In this study, at referral, providers, caregivers, and/or patients reported on the patient’s psychiatric history. Patients for whom there were concerns for attenuated psychosis were eligible for evaluation. Prior to diagnostic evaluation, patients completed self-report measures of a broad range of psychiatric symptoms. Patients were evaluated with the Structured Interview for Psychosis-Risk Syndromes (SIPS) to determine if they met CHR-P criteria. Using referral and intake data from 118 help-seeking individuals, we performed univariate chi-square or independent samples t-test to identify factors associated with CHR-P syndrome. Ninety-nine (99) individuals with complete referral data were included in the analysis (mean age: 17.8 years; SD: 4). Almost a quarter (24.2%) met CHR-P criteria on the SIPS. Referred individuals presented with high rates of psychiatric comorbidity, previous psychiatric treatment, and functional impairment across multiple domains. Significant predictors (p<.05) of CHR-P syndrome included: history of autism spectrum disorder, endorsing more than one psychotic symptom, reduced sleep duration, and more severe cognitive and behavioral difficulties. Identification of CHR-P may be improved with greater attention to developmental history, psychotic symptoms, sleep disturbance, and cognitive and behavioral difficulties. Integrating routine assessment into clinical care provides data-driven opportunities to improve the identification and treatment of CHR-P.
 Psychiatry and Clinical Psychology

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