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Digital Health Around Clinical High Risk and First-Episode Psychosis


Purpose of Review

This review aims to examine relapse definitions and risk factors in psychosis as well as the role of technology in relapse predictions and risk modeling.

Recent Findings

There is currently no standard definition for relapse. Therefore, there is a need for data models that can account for the variety of factors involved in defining relapse. Smartphones have the ability to capture real-time, moment-to-moment assessment symptomology and behaviors via their variety of sensors and have high potential to be used to create prediction and risk modeling.


While there is still a need for further research on how technology can predict and model relapse, there are simple ways to begin incorporating technology for relapse prediction in clinical care.

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Fig. 1


Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Correspondence to John Torous.

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Philip Henson, Hannah Wisniewski, and Charles Stromeyer IV each declare no potential conflicts of interest.

John Torous reports grants from Otsuka.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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This article is part of the Topical Collection on Child and Adolescent Disorders

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Henson, P., Wisniewski, H., Stromeyer IV, C. et al. Digital Health Around Clinical High Risk and First-Episode Psychosis. Curr Psychiatry Rep 22, 58 (2020).

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  • First-episode psychosis
  • Relapse
  • Technology
  • Smartphones