Science faces challenges in developing much-needed precision mental health treatments to accurately identify and diagnose mental health problems and the optimal treatment for each individual. Digital twins (DTs) promise to revolutionize the field of mental health, as they are doing in other fields of science, including oncology and cardiology, where they have been successfully deployed. The use of DTs in mental health is yet to be explored. In this Perspective, we lay the conceptual foundations for mental health DTs (MHDT). An MHDT is a virtual representation of an individual’s mental states and processes. It is continually updated from data collected over the lifespan of the individual, and guides mental health professionals in diagnosing and treating patients based on mechanistic models and statistical and machine learning tools. The merits of MHDT are demonstrated through the example of the working alliance between the therapist and the patient, which is one of the most consistent mechanisms predicting treatment outcome.
Bibliographical noteFunding Information:
The writing of this manuscript was supported by the Israel Science Foundation (ISF, Grant no. 395/19 to SZ-M and Grant no. 1755/22 to I. Dattner). The funder has no role in the decision to publish, or preparation of the manuscript.
Copyright © 2023 Spitzer, Dattner and Zilcha-Mano.
- digital twins
- mental health interventions
- personalized medicine
- precision mental health
ASJC Scopus subject areas
- Psychiatry and Mental health