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The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 Month Psychotic Conversion Using Machine Learning


The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 Month Psychotic Conversion Using Machine Learning

B B Brodey et al. Schizophr Res.


Introduction: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention.

Methods: Self-report Likert-scale survey items were administered to individuals being screened with the Structured Interview for Psychosis-risk Syndromes (SIPS) and followed at eight early psychosis clinics. An a priori analytic plan included Spectral Clustering Analysis to reduce the item pool, followed by development of Support Vector Machine (SVM) classifiers.

Results: The cross-validated positive predictive value (PPV) of the EPSI at the default cut-off (76.5%) exceeded that of the clinician-administered SIPS (68.5%) at separating individuals who would not convert to psychosis within 12 months from those who either would convert within 12 months or who had already experienced a first episode psychosis (FEP). When used in tandem with the SIPS on clinical high risk participants, the EPSI increased the combined PPV to 86.6%. The SVM classified as FEP/converters only 1% of individuals in non-clinical and 4% of clinical low risk populations. Sensitivity of the EPSI, however, was 51% at the default cut-off.

Discussion: The EPSI identifies, comparably to the SIPS but in less time and with fewer resources, individuals who are either at very high risk to develop a psychotic disorder within 12 months or who are already psychotic. At its default cut-off, EPSI misses 49% of current or future psychotic cases. The cut-off can, however, be adjusted based on purpose. The EPSI is the first validated assessment to predict 12-month psychotic conversion. An online screening system,, is under development.

Keywords: Attenuated psychotic syndrome; First episode psychosis; PQ-B; Prodromal psychosis; SIPS; Schizophrenia.

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